Epilepsy does great harm to the human body, and even threatens human life when it is serious. Therefore, research focused on the diagnosis and treatment of epilepsy holds paramount clinical significance. In this paper, we utilized variational modal decomposition (VMD) and an enhanced grey wolf algorithm to detect epileptic electroencephalogram (EEG) signals. Data were extracted from each patient’s preseizure period and seizure period of 200 s each, with every 2 s as a segment, meaning 100 data points could be obtained for each patient’s health period as well as 100 data points for each patient’s epilepsy period. Variational modal decomposition (VMD) was used to obtain the corresponding intrinsic modal function (VMF) of the data. Then, the differential entropy (DE) and high frequency detection (HFD) of each VMF were extracted as features. The improved grey wolf algorithm is adopted for a selected channel to improve the maximum value of the channel. Finally, the EEG signal samples were classified using a support vector machine (SVM) classifier to achieve the accurate detection of epilepsy EEG signals. Experimental results show that the accuracy, sensitivity and specificity of the proposed method can reach 98.3%, 98.9% and 98.5%, respectively. The proposed algorithm in this paper can be used as an index to detect epileptic seizures and has certain guiding significance for the early diagnosis and effective treatment of epileptic patients. The risk factors of epilepsy include a family history of epilepsy, craniocerebral injury, febrile convulsion, neonatal disease and pregnancy risk factors . At presFor decades, in order to improve the diagnostic performance of EEGs, researchers have extracted effective information from EEG signals from many aspects . The parIn order to improve medical efficiency, automatic epilepsy recognition based on EEG has been widely studied . At the The core problems of the automatic detection of epilepsy can be summarized into two sub-problems: feature extraction and classifier design . Deep leIn this paper, variational modal decomposition and the improved grey wolf algorithm were used to detect epileptic EEG signals. Aiming at the problem of epileptic EEG signals, an improved detection mode is proposed. Firstly, the VMD method is used to extract the features. The improved grey wolf algorithm is used for channel selection . ExperimThis paper consists of five main parts: the first part is the introduction, the second part is the state of the art, the third part is the methodology, the fourth part is the result analysis and discussion and the fifth part is the conclusion.Automated detection of epilepsy is a key component of epilepsy diagnostic and therapeutic research. It involves several complex steps designed to accurately identify epileptic EEG signals. The following is a general summary of the key components involved in the process.(1) Signal Acquisition: Signal acquisition serves as the initial stage in epilepsy detection. EEG abnormalities during epileptic seizures manifest as specific waveforms and patterns. The collected EEG data can be used as input for the automatic detection of epilepsy. (2) Signal Preprocessing: The preprocessing of EEG signals is a crucial step in this process. EEG signals, in their original form, are non-stationary and dynamic, characterized by low amplitudes. Therefore, in order to effectively analyze EEG signals, it is necessary to perform preprocessing such as artifact removal while retaining relevant information. (3) Feature Extraction and Selection: Following signal preprocessing, the next step is feature extraction. Feature extraction aims to comprehensively characterize EEG signal patterns, highlight distinctions between epileptic and normal states, and effectively discriminate epileptic seizures. (4) Classification Model Learning and Evaluation: The final stage involves the use of classification models to learn and evaluate EEG signals for epilepsy detection. These models fall into two main categories: statistical analysis and machine learning.EEG abnormalities in epileptic seizure states are mainly manifested as spike wave, slow spike wave or various rhythms. Spike wave is one of the typical characteristics of epileptic discharge in EEG signal. It is manifested by negative surface deflection caused by cortical surface orientation, steep ascending and descending branches, and the overall shape of thorns like spikes. It has a wave change in the EEG signal caused by abnormal firing of nerve cells in the cortex. The spike wave period is usually 20~70 ms, which is prominent in the background signal. The amplitude is more than 20 μV, which is more than 1.5 times that of the background signal. Epileptic spines and spikes in epileptic seizures are usually extracted clinically. The pathological information related to epilepsy was obtained by analyzing epileptic spines and spikes.EEG signals can be divided into intracranial EEG and scalp EEG. Intracranial EEG is to record electrical activity signals of different parts of the brain by placing strip or mesh electrodes in the epidural area through cranial drilling or craniotomy. Scalp EEG, on the other hand, uses EEG caps to place electrodes at fixed locations on the human scalp and record electrical activity. EEG signals collected by these methods can be used as input signals for the automatic detection of epilepsy.In the current study, part of the data are from the hospital’s non-public patient data, and most of the data are from public datasets. The original EEG signal is non-stationary and dynamic. Scalp EEG itself has a small amplitude, and the acquisition program will be affected by 50 Hz or 60 Hz power frequency signal. In addition, seizures are accompanied by loss of consciousness and body movements, and the acquisition process can easily experience interference due to uncontrollable factors, so the scalp EEG is often random to a certain extent. In order to study and analyze the characteristics of EEG signals in the future. Firstly, it is necessary to remove the artifacts from the original EEG signal without losing the effective information, so as to improve the classification accuracy. The main approach involves three steps. The characteristic values of EEG signals, such as amplitude, area under equivalent curve, etc., are considered abnormal when the signal exceeds a certain threshold. Common artifacts include ocular artifact, myoelectric artifact, electrode shift, emission artifact and diffuse fast sharp alpha wave. Experts’ experience can be used to screen the typical interference characteristics so as to remove the corresponding artifacts. Most of the effective information of EEG is concentrated between 1 Hz and 60 Hz. Therefore, band-pass filtering is a common method for EEG signal preprocessing. The method based on the Kalman filter can enhance the signal-to-noise ratio (SNR) of the EEG signal and improve the detection rate of the peak wave. In addition, half-wave processing is a common EEG signal processing method used to smooth out spikes and burrs in the EEG signal.It is an important step to realize the automatic detection of epilepsy to extract effective features as a classification basis by analyzing the signals. Reasonable and typical epileptic EEG features can comprehensively characterize EEG signal patterns. At the same time, it can effectively describe the difference in EEG signals between epileptic seizure and normal state, highlight the difference between spine wave and background signal and help the classification model to discriminate epileptic seizure effectively. The quality of the feature seriously affects the final classification performance.In general, there are four categories of features used to detect epilepsy: the time domain characteristics of sequence waveform and sequence cross-correlation; the frequency domain feature represented by power spectrum density characterizing signal energy; time-frequency domain features of original EEG signals converted by time-frequency transform method; and the nonlinear characteristics of signal uncertainty measurement such as sample entropy, permutation entropy, Hurst parameter and higher-order spectrum analysis based on nonlinear analysis.The feature matrix can be extracted by singular value decomposition, principal component analysis, independent component analysis and correlation analysis to reduce the feature dimension. In feature selection, one-way analysis of variance (ANOVA) is the most commonly used method.Classification models can be divided into two types: statistical analysis and machine learning. For the statistical analysis model, in addition to directly specifying the threshold value of signal characteristics to judge the attack state, it also includes a distribution test and correlation analysis. Morphological analysis, time-frequency analysis and similar techniques compared the differences in characteristics between the detected signal and the template epileptic seizure signal. This enabled automatic epilepsy detection.With the development of artificial intelligence, machine learning models are becoming widely used in the automatic detection of epilepsy, including traditional machine learning that categorizes manually extracted features directly, deep learning based on a neural network, transfer learning to overcome individual differences in EEG, multi-view learning integrating multiple feature views, integrated learning with multiple base classifiers and active learning with optimized annotation samples.The dataset used in this paper is the CHB-MIT dataset, which is a collection of EEG signals from Boston Children’s Hospital included in the MIT EEG database. The dataset is composed of scalp EEG recordings from children with refractory epilepsy. A total of 23 recordings from 22 subjects were included. All EEGs were acquired using 10–20 international standard electrode positions, and EEGs were recorded using 18/23 leads with a sampling frequency and resolution of 256 Hz and 16 bits, respectively.The VMD method is an adaptive and completely non-recursive modal variational and signal processing method. The VMD method is well suited for feature extraction from EEG signals due to its adaptability in determining the number of modal decompositions, its ability to overcome band aliasing issues and its suitability for positive definite problems, which are important considerations when working with EEG data. These advantages make it a valuable tool in our research for the accurate detection of epileptic EEG signals.λ is introduced to transform the constrained variational problem into an unconstrained variational problem, and the augmented Lagrange expression in Equation (2) is obtained.First, regarding the structural variational problem, suppose the original signal The alternate direction multiplier iterative algorithm combined with Parseval and Fourier isometric transform was used to optimize the modal components and central frequencies, and the saddle points of the augmented Lagrange function were searched. The expressions of The VMD method overcomes the phenomenon of band aliasing because it minimizes component bandwidth. The principle based on a single channel solution is superior to the ICA method, which is only suitable for positive definite problems. In conclusion, the VMD method can meet the requirements of removing EEG epilepsy in terms of the frequency band separation effect and application conditions.Generally, sample entropy, approximate entropy, fuzzy entropy and energy entropy are often used as the characteristics of EEG signals. However, because the energy distribution of the EEG signal components in epileptic patients is different from that of the normal EEG signal components, the energy entropy method is used in this paper to solve this problem. The energy entropy is calculated according to Equation (6).n VMF component.The EEG signal The energy of the VMF component is shown in Equation (7).The proportion of the VMF energy spectrum to the total energy spectrum is shown in Equation (8).The energy entropy of each VMF component.According to the definition of energy entropy, the more the energy of each frequency band accounts for the total energy, the smaller the energy entropy will be. Because the VMD method has a good frequency band separation function, it can separate the epilepsy component from the EEG signal well.The detailed process of the VMD-VMF method is shown in In this paper, the differential entropy (DE) and Higuchi fractal dimension (HFD) of each VMF are extracted to form the feature set. Then, the calculation process of these two features will be introduced, respectively.(1)The differential entropy (DE)The DE feature of the EEG data was calculated using the short-time Fourier transform (STFT) and a non-overlapping Hamming window (1 s) and averaged across five bands. The differential entropy equation is Equation (10).2).To simplify the calculation, the differential entropy can be simplified as Equation (11), assuming that the EEG signals follow a Gaussian distribution of According to Equations (10) and (11), differential entropy characteristics can be obtained. (2)The Higuchi fractal dimension (HFD)HFD is an algorithm used to calculate the fractal dimension of time series. A time series The curve length z delayed generation sequence curves The total sequence curve length can be approximated by the average length of z, a set of curve data about z and L(z) is obtained, and L Lh(L(z))~Lh(1/z) curves are then drawn. If it is a straight line, L(z) has the following relationship with K: For different values of Lh(L (z)) = FD × Lh(1/z) + C.The fractal dimension of time series can be obtained by the linear fitting of data to get maxz is not specified in the implementation process of the algorithm. In the application of the algorithm, several authors use the method of guessing and trying to determine the value of maxz.The algorithm has high accuracy in calculating the fractal dimension of time series, but the parameter In this paper, we use a support vector machine (SVM) to classify EEG signals, which is a supervised generalized linear classifier. It has now been progressively theorized and has become part of the theoretical foundation of statistics. The main idea of it is based on the structural risk minimization principle. It creates an optimal hyperplane by solving a convex quadratic programming problem so that the intervening edge between positive and negative examples is maximized. In a practical classification problem, for a given training dataset Then, the problem of finding the maximum separated hyperplane is summarized as solving the constrained optimization problem:xth person, and In this paper, In order to accurately classify the EEG signals of epileptic patients, two types of samples are set up here: one is a normal EEG sample from a conscious healthy person; the second is the EEG samples of epileptic patients at the onset of epilepsy. The EEG samples are classified using SVM as a classifier. The accurate detection of epileptic EEG signals was achieved, and the classification graph is shown in According to the traditional method, all channel information of the EEG is directly input into the system classifier. The disadvantage of this is the large amount of data, which will directly affect the efficiency of the SVM classifier. Therefore, the EEG channels are filtered and those containing valid features are retained. 3 is the random vector in the range  and d is the dimension of the search space. Equation (19) is the calculation of the S function.The grey wolf optimization (GWO) algorithm is usually used to solve continuous optimization problems. In this paper, the GWO algorithm is used for channel selection. The position vector carried by each wolf represents a channel, which is an alternative solution. In general, the search range of the continuous algorithm is arbitrary. However, the solution vector of the channel selection problem should be a numeric vector containing only 0 s and 1 s. Therefore, in the binarization algorithm, the search range of each dimension of the alternative solution is restricted to the interval . In order to binarize the grey wolf position, it must be converted to a binary vector for position updating. The calculation procedure is Equation (18).I1, I2 and I3 were calculated. The grey wolf position is updated by Equation (18). Then, the fitness values of grey wolves were calculated, and the positions of α, β and δ were updated. The algorithm is repeated until the termination condition is satisfied. In order to improve the efficiency of the algorithm while guaranteeing the classification accuracy, five channels are finally selected as the input of the SVM classifier in this paper.The binarization method of GWO is called the binary grey wolf optimization. First, the wolves are randomly initialized (0 or 1). Secondly, the classification accuracy of the KNN classifier  is used The data in this paper were extracted from each patient’s preseizure period and seizure period of 200 s each, with every 2 s as a segment, meaning 100 data points of each patient’s health period and 100 data points of each patient’s epilepsy period could be obtained. Variational modal decomposition and the improved grey wolf algorithm were used to classify epileptic EEG signals. In processing the EEG, 5 of the 23 channels were finally selected as inputs to the SVM classifier by the grey wolf algorithm. In order to make the algorithm performance fully verified, 10-fold cross-validation was used in the experiments.In the seizure detection of epilepsy, EEG examination is of great value to the judgment of its etiology and seizure type. The most common is scalp electroencephalography, which places electrodes on the scalp to record changes in the electrical potential of brain cells as they move.In this paper, the public EEG data are used for the CHB-MIT dataset. First, VMD decomposition is performed on the raw EEG data to obtain VMFs. Then, extraction features are performed, i.e., the differential entropy (DE) and Higuchi fractal dimension (HFD) of each VMF are extracted as features. The channels of the EEG signals are selected by the grey wolf optimization algorithm. Finally, the EEG signals are classified by the SVM classifier. The overall flowchart of the algorithm in this paper is shown in In order to further evaluate the experimental performance of the method, sensitivity, specificity and area under the curve (AUC) were introduced as evaluation indexes. One crucial aspect of evaluating the performance of a classifier is to analyze its AUC value. The AUC is a valuable metric in assessing the classifier’s ability to discriminate between different classes. The higher AUC values signify that the KNN classifier is better at distinguishing between different classes or categories within a dataset . Equation (20) is the sensitivity expression:Equation (21) is the expression of specificity:When DE and HFD were used as the feature input, 98.3% of the classification accuracy, 98.5% of the specificity, 98.9% of the sensitivity and 0.991 of the AUC value were achieved. This shows that the classification method has a good classification effect. The comparative experimental data are shown in The accuracy is compared with the classification task of full channels (23 channels) and the classification task of 5 channels obtained using only the GWO algorithm. The results of the comparison are shown in The method proposed in this paper is compared with Method A , Method In this paper, variational modal decomposition and an improved grey wolf algorithm were used to detect epileptic EEG signals. The VMD method can reduce the nonstationarity of time series with high complexity and strong nonlinearity, so as to obtain relatively stationary subseries with multiple different frequency scales. Meanwhile, this method overcomes the problems of endpoint effects and modal component aliasing in the EMD method. The grey wolf optimization algorithm can be used to solve continuous optimization problems. The experimental data were extracted from each patient’s preseizure and seizure periods of 200 s, with every 2 s as a segment, meaning 100 data points were obtained for each patient’s health period as well as 100 data points for each patient’s epilepsy period. The results show that the proposed method has the highest accuracy (98.3%), the highest sensitivity (98.9%) and the highest specificity. The public dataset of CHB-MIT was selected for verification, and the final classification accuracy reached 98.3%. In order to make the algorithm performance fully verified, 10-fold cross-validation was used in the experiments. This verified that the results are consistent.This study, as an automatic seizure detection approach, achieved effective classification results. It also highlighted significant differences in EEG signal complexity between the pre-seizure stage and the actual seizure stage. During epileptic seizures, the DE values decreased and HFD values increased, indicating changes in brain activity complexity. This difference may manifest as cognitive impairment in patients with epilepsy. The algorithm proposed in this paper can be used as an index to detect epileptic seizures and has certain guiding significance for the early diagnosis and effective treatment of epileptic patients. The method presented in this paper has high accuracy and sensitivity in the detection of epileptic EEG signals. While the proposed algorithm has yielded promising results in the classification of EEG signals, there are still limitations in visual representation, particularly in showcasing raw signals and artifact removal. In our forthcoming research endeavors, we are committed to procuring additional data resources and enhancing the performance of our method in visual presentation. In addition, collaboration with medical experts for clinical trials and real-time assay optimization is also on our research agenda, with the aim of improving the effectiveness of epilepsy diagnosis and treatment.


A recent evaluation of the published data regarding the PCOS topic has highlighted a paradox in the definition of this condition. Even though the name of the syndrome refers to ovarian dysfunction, it seems that patients diagnosed with PCOS are more likely affected by an endocrine and metabolic issue. The term PCOS might not be appropriate to indicate the phenotypes described by the Rotterdam criteria, since the only phenotype with a gynecological issue alone is PCOS phenotype D. This novel perspective regarding how PCOS is currently defined leads the way to a reinterpretation of the entire pathological context and the treatment prescribed, such as inositols. A new point of view on the etiopathogenesis of the disease completely changes the current meaning of PCOS and consequently the therapeutic rationale evaluated to date. Polycystic ovary syndrome (PCOS) is a widespread reproductive, metabolic, and psychological condition that impacts 5 to 18% of women across their lifespans , to dateA diagnosis of PCOS is made according to the Rotterdam criteria encompassing all possible combinations of the following features: clinical or biochemical evidence of hyperandrogenism, evidence of oligo-anovulation, and ultrasonographic identification of polycystic ovary morphology (PCOM) . The appIt seems clear that a condition of hyperandrogenism is frequently observed in women with PCOS and is a common feature of three out of four possible PCOS phenotypes . HyperanConsidering that the majority of women with PCOS exhibit insulin resistance (IR) ,9 or othThis new perspective supporting the central role of a metabolic imbalance in the ovary in the PCOS scenario could radically change the way the disease is currently understood.The hypothesis of “metabolic hyperandrogenism” leads to a paradox regarding the term PCOS and its meaning. Indeed, the definition of a woman presenting with a polycystic ovary implies that she has a gynecological disorder. Specifically, the disorder affects the reproductive system, leading to an alteration in ovarian function and the formation of typical ovarian cysts. On the other hand, the term “syndrome” in the medical field indicates a group of symptoms representing the expression of a disease without indicating possible causes or the mechanism of onset . All thiIt seems that the real meaning of PCOS mainly refers to an endocrine–metabolic disorder, and the widespread presence of the IR phenomenon in these patients further confirms the pivotal involvement of insulin signaling in this syndrome.On these premises, several authors and endocrine or gynecological societies support the use of different criteria for PCOS diagnosis by questioning the suitability of the application of the Rotterdam criteria. For example, the Androgen Excess and Polycystic Ovary Syndrome Society (AE-PCOS) suggests using otherwise unexplained hyperandrogenism with either oligo-anovulation or PCOM as a criterion . AccordiThese indications further highlight that PCOS, in its current meaning, entails an endocrine–metabolic disorder regardless of ovarian dysfunction. A compelling aspect in this regard is represented by the exclusion of IR from the criteria adopted in the diagnosis of PCOS. Even though about 75% of women with PCOS exhibit IR , it is nConditions such as hyperinsulinemia or IR in the context of the female reproductive apparatus allow the introduction of another concept, appropriately indicated as the ovarian paradox. Indeed, as the ovaries remain sensitive to insulin signaling, hyperinsulinemia due to systemic IR may contribute to increased androgen secretion  and leadConsidering the primary importance of metabolic alterations in this syndrome, it might be questioned whether the phenotypes based on the Rotterdam criteria are appropriate to describe a condition originating from ovarian dysfunction. Hence, women with PCOS phenotype B (hyperandrogenic anovulation) lack evidence of PCOM and do not exhibit a clear gynecological issue, while the presence of hyperandrogenism in phenotypes A (classic PCOS) and C (ovulatory PCOS) suggests a plausibly imbalanced metabolism that may or may not co-exist with an ovary issue.In light of this consideration, it seems reasonable that phenotype D identifies the only gynecological condition and an actual ovarian syndrome .As previously discussed, factors such as insulin signaling and IR are involved in androgen excess and in the development of hyperandrogenism. In a study by Moghetti and colleagues , differeThe findings of this study demonstrate the differences in the metabolic background of the various PCOS phenotypes. The characteristics of non-hyperandrogenic phenotype D PCOS appear in a separate group within the syndrome and include a metabolic profile very similar to that of healthy women. Indeed, the syndrome in these patients seems not to derive from or be associated with metabolic deregulation . As phenRecently, an in vitro study revealed that the stimulation of 3D follicles from mouse models with insulin-like growth factor-1 (IGF-1) causes the arrest of follicle growth when excessive IGF-1 amounts were used . The autGiven that women with phenotype D PCOS seem to be the only group exhibiting a disease of gynecological origin, it might be questioned whether the definition of PCOS really applies to the other phenotypes with a metabolic syndrome. If not, what should we consider as an alternative classification?Hyperandrogenic PCOS is frequently associated with hirsutism, acne, alopecia, or excessive weight gain, but these symptoms seem more likely to be epiphenomena of a metabolic alteration, which leads to gynecological issues. These canonical features do not represent the origin of the problem of PCOS, since they refer to the manifestation of the pathology rather than identify a polycystic morphology of the ovary. If we indicate the condition of the polycystic ovary, it might be argued that PCOS is not a comprehensive definition, particularly as it is understood in the scientific community.Supporting evidence for this view can be found in a recent definition of “male PCOS” published by several authors . The terOn these premises, the definition of “PCOS” should be appropriate only to indicate women with phenotype D, while the remaining phenotypes should be indicated as different types of an “endocrine-metabolic syndrome”. An innovative classification might also be proposed, defined by different criteria and parameters that could describe the PCOS phenotypes as defined today, with new feature combinations considered for the diagnosis and a new nomenclature for these phenotypes .This aspect completely changes the perception of the etiopathogenesis of the PCOS condition as it is defined today and implies the need to revise the diagnostic assessment and the therapeutic approach. Indeed, if this new vision of an endocrine–metabolic syndrome applies, it could also be postulated that the term PCOS does not properly indicate a gynecological pathology and a gynecologist should not be the referred specialist. As alterations in the ovary region are not involved in the generation of the phenotypes described by the Rotterdam criteria, except for phenotype D, the presence of an endocrine–metabolic imbalance suggests that a diagnosis of PCOS in its current meaning should be made by an endocrinologist or, alternatively, by a gynecologist specializing in endocrinological gynecology.To date, the therapeutic approaches commonly recommended for PCOS patients are (1) lifestyle changes to increase physical activity and correct caloric intake; (2) the use of oral combined pills (OCPs) to reverse the hormonal imbalance; (3) the use of insulin sensitizers, such as metformin or inositols, to improve the metabolic profile ,21.However, in this novel view of phenotypes A, B, and C as endocrine–metabolic syndromes, the current therapeutic rationale should be revised, as a misunderstanding of the disease etiology leads to incorrect therapeutic indications. If we are dealing with metabolic deregulation, there is no need to intervene by targeting the ovary. This new point of view regarding PCOS means that evaluating therapeutic approaches that may act at the metabolic level is mandatory.Frequently, the first-line medical treatment for women with PCOS is OCPs . They arIt is also important to recall that there are also many concerns regarding the safety of the long-term use of these pills , and evaIn this context, the first remedy to be evaluated and recommended should always be a lifestyle intervention . UsuallySince the described metabolic alterations, particularly IR, impact a large portion of PCOS subjects, insulin-sensitizing agents are a therapeutic option . For exaAlternative insulin sensitizers have been evaluated, and several authors have described significant improvements in PCOS parameters with inositol administration .Two stereoisomers, myo-inositol (myo-Ins) and D-chiro-inositol (D-chiro-Ins), are naturally present in the ovaries and in the follicular fluid and participate in follicular development by mediating hormonal activities, including insulin signaling. Despite the chemical similarities and their synergistic effect on insulin sensitivity, they exert different effects on the ovary .The rationale supporting the importance of inositols in the PCOS scenario relies on the demonstration that specific myo-Ins/D-chiro-Ins ratios maintain reproductive functions, while alterations lead to an aberrant ovulation process and to androgen overproduction. Oral supplementation with inositols, indeed, represents a valid approach to counteracting the signs of PCOS by improving metabolic alterations in patients and reducing the manifestations of hyperandrogenism ,39.In particular, in overweight–obese women, a formulation with both stereoisomers, based on the physiological ratio of myo-Ins/D-chiro-Ins 40:1) observed in the plasma, can restore the cellular content of myo-Ins in the ovary while maintaining the correct ratio with D-chiro-Ins :1 observ,42.Interestingly, D-chiro-Ins elicits positive activity in the ovary when used at the right concentrations for a brief treatment period by regulating steroidogenic enzyme genes in human granulosa cells, lowering the expression of both aromatase and cytochrome P450, and increasing testosterone levels in theca cells ,44. ConvMyo-Ins, in particular, plays a pivotal role in sustaining the entire reproduction process  and imprRecent data also demonstrate that the combination of inositols, especially myo-Ins, with probiotic molecules such as α-lactalbumin enhances intestinal adsorption, improves the gastric environment, reduces the inflammatory state, and enhances the beneficial activity of myo-Ins in the PCOS condition ,52.The efficacy of inositol supplementation in PCOS scenarios has been endorsed worldwide for more than 20 years , but intThis aspect regarding a sub-group of PCOS patients raises questions concerning the best clinical approach to be considered for the treatment of this condition . CurrentMoreover, the hypothesis of a redefinition of PCOS also suggests the need for a reinterpretation of the literature evidence published. Among a huge number of scientific articles on PCOS, reports on the differentiation of the subject phenotypes are very rare. Patients enrolled in clinical studies, for instance, are not divided into sub-groups according to their phenotypes or other PCOS features. As a result, the various phenotypes are mixed together in the study groups: hyperandrogenic patients are included together with non-androgenic patients, or ovulatory and anovulatory subjects are included in the same group. The heterogeneity of study groups might alter the results of those studies and might change the effectiveness of the treatment investigated.In light of these considerations, the existence of a paradox regarding the definition of PCOS, where a gynecologic etiology could be ruled out, appears evident, and the blurred edges of the pathology and therapy have yet to be properly defined.


In the past, the primary treatment for MRKH syndrome (Mayer-Rokitansky-Küster-Hauser syndrome) with a functional primordial uterus was surgical removal of the functional primordial uterus. In rare instances, the endometrium of the functional primordial uterus is well developed, and surgical preservation of the functional primordial uterus provides the possibility of preserving reproductive function for these patients.A 14-year-old female was diagnosed with type I MRKH syndrome with a functional primordial uterus through physical examination and imaging investigations. We freed the functional primordial uterus through laparoscopic surgery and excised a portion of the lower myometrium to create an outlet at a lower uterine segment, which we then intermittently anastomosed to the tip of the artificial vagina. The patient recovered well after the surgery, and a re-examination showed no significant abnormalities.We were successful in preserving the functional primordial uterus using laparoscopic surgery in a patient with MRKH syndrome and connecting it to an artificial vagina through reconstructive surgery to ensure unobstructed menstrual drainage and preserve the reproductive potential of the patient.The online version contains supplementary material available at 10.1186/s12905-023-02741-1. MRKH syndrome (Mayer-Rokitansky-Küster-Hauser syndrome) is a rare reproductive tract malformation in females caused by embryonic bilateral paramesonephric duct hypoplasia or bilateral paramesonephric duct tail dysplasia, and patients generally seek medical consultation due to primary amenorrhea in adolescence or dyspareunia after marriage . Common A small number of patients have a functional primordial uterus where the primordial uterus has a developed endometrium. In this condition, patients often experience recurrent abdominal pain, and the basic treatment in the past consisted of surgical removal of the functional primordial uterus. In a very small number of patients, the functional primordial uterus has a well-developed endometrium and a large uterine cavity, and since the patients have normal ovaries and fallopian tubes, surgical preservation of the functional primordial uterus allows for the preservation of reproductive function in these patients.A patient with MRKH syndrome with a functional primordial uterus was recently admitted to our hospital, and we performed laparoscopic surgery to preserve the functional primordial uterus on the left side and performed uterovaginal reconstruction with positive results. We present details of the case in the following sections.The patient was a 14-year-old female who was admitted to our hospital mainly due to “periodic lower abdominal pain for one year”. The patient was delivered normally at full term, and her mother had no history of exposure to drugs, toxic substances during pregnancy, or radioactive substances. The patient started developing breasts at the age of 12 and had not had a menstrual cycle to date. One year ago, she started to have lower abdominal pain, which was recurrent (around every 28–30 days) and relieved spontaneously after about a week. At this time, she visited another hospital and underwent a magnetic resonance imaging (MRI) examination, which showed a “bilateral primordial uterus, with the left side being larger (containing a little endometrium); an undeveloped cervix and middle and upper vaginal segments; a left ovarian cyst, with chocolate cyst unable to be excluded”.Findings of the physical examination on admission: abdominal examination showed no significant abnormality, and no obvious mass was palpated. The gynecological examination showed a young female vulva with normal development and a small amount of pubes. The hymen was normal, and the swab could enter about 2 cm from the hymen. The cervix and uterus were not palpated on rectal abdominal examination. A cystic solid mass with a diameter of about 5 cm was palpated in the left adnexal region with pain on mild pressing, while no obvious mass was palpated in the right adnexal region.MR scanning Figs.  and 2 suThe bowel preparation was done one day before surgery, and the patient was instructed to remain fast without food or water on the day of surgery. The procedure was done with the patient placed in the lithotomy position under general anesthesia. Laparoscopic exploration of the pelvic and abdominal cavities Fig.  showed aA bilateral cholecystectomy was performed first, during which chocolate-like fluid outflow was seen from the left ovary  and blood outflow was seen from the right ovary. After the operation, the bilateral ovaries were sutured and shaped. The left pelvic funnel ligament was freed, and the left round ligament and the anterior and posterior lobes of the broad ligament were severed. The left uterine artery and ureter were further freed, the superior branch of the left uterine artery was severed.The fibrous cord tissues of the lower uterine segment, which did not develop into the cervix, were excised .The left parametrium was freed downward to free the left functional primordial uterus as far down as possible in preparation for subsequent anastomosis .Under laparoscopic monitoring, a cavity was bluntly punched inward along the external vaginal orifice in the middle of the vulvar vestibule, parallel to the urethra and rectum, until the pelvic floor peritoneum in the interstitial space between the bladder and rectum, while saline was injected intermittently to form a water cushion. Oval forceps were placed in the cavity to open the pelvic floor peritoneum, which was incised to create an artificial vaginal tunnel that could accommodate two fingers. The peritoneum on the posterior wall of the bladder was freed completely, with an area of about 6 cm × 6 cm. The freed peritoneum was attached to the mold surface, and a drainage tube was placed through the opening at the top of the mold. The mold was placed into the artificial vaginal tunnel while carrying the peritoneum and drainage tube .The distal peritoneum was intermittently sutured and anastomosed to the “natural vaginal mucosa” of the lower vaginal segment, and the proximal peritoneum was sutured and fixed to the tip of the artificial vaginal tunnel . The uterine cavity was exposed by a full incision of the freed left functional primordial uterus near the vagina, and the endometrial tissues could be seen inside the uterine cavity without significant blood accumulation . A portion of the myometrium tissues, approximately two cm in diameter, were removed, and the intima at the defective area was intermittently evaginated and sutured to the serous layer so that it would be like a “bowl” and serve as the outlet of the lower uterine segment . Finally, absorbable sutures were used to intermittently anastomose the artificial outlet of the lower uterine segment and the tip of the artificial vagina .The operation was successful, with an operation duration of 2 h and an intraoperative bleeding amount of 30 ml. The patient was administered antibiotics to prevent infection, the vaginal mold was replaced every other day, iodophor solution was used to disinfect and irrigate the vagina, and the vaginal drainage tube was removed two days after the surgery. The ovarian cysts were confirmed as endometriosis cysts by post-operative pathological examination. The patient recovered well post-surgery without any complications and was successfully discharged with the mold six days after the operation.During the follow-up period, the patient had a menstrual cycle in the first month post-surgery, which lasted for about three days with minimal bleeding, unblocked discharge of menstrual blood, and no abdominal pain. Subsequently, the patient had regular menstrual cycles every month without abdominal pain. The pelvic MR did not show any abnormal mass six months after the surgery, and the functional primordial uterus was connected to the artificial vagina. The postoperative outcome was good.In 1961, the Swiss scholar Hauser systematically described the pathogenesis and clinical manifestations of MRKH syndrome, summarizing previous reports . For a lMost patients with MRKH syndrome have no clinically significant symptoms as the primordial uterus does not have a functional endometrium. However, if the primordial uterus has a functional endometrium, also known as a functional primordial uterus, clinical symptoms such as abdominal pain are more likely to occur, and patients are more likely to consult a clinician and get diagnosed earlier. In the retrospective cohort study conducted by the University of Michigan (USA) in 2013 , MRI conClinicians mainly chose surgical removal of the functional primordial uterus followed by vaginal reconstruction, for patients with MRKH syndrome with a functional primordial uterus associated with severe abdominal pain. This surgery is relatively simple and effective in relieving abdominal pain, but the patient will permanently lose menstruation and reproductive function post-surgery, and this can have a significant psychological impact on the patient. It is for this reason that there are efforts to preserve the functional primordial uterus and reconstruct it with an artificial vagina through surgery so that menstrual blood can flow out smoothly through the artificial vagina, thus preserving the physiological function and potential reproductive function.As early as 1938, a successful treatment of cervical atresia through uterovaginal reconstruction was reported . Zarou eIn 2008, Raudrant et al.  successfIn our study, the patient had a left ovarian endometriosis cyst, so we first performed the left oophorocystectomy and then freed the left functional primordial uterus as much as possible for subsequent downward traction and anastomosis with artificial vaginal, which was one of the key steps of the procedure. We chose the surface peritoneum of the posterior bladder wall for the peritoneal vaginoplasty as it has a sufficient area of peritoneum and is easy to obtain. In previous uterovaginal reconstruction procedures, a small hole was mainly made at the lower end of the uterus to serve as an outflow tract, and a drainage tube was placed into the uterine cavity through this hole, followed by anastomosis of artificial vaginal and primordial uterus.However, in our case, the size of the primordial uterus was relatively large, so we creatively excised part of the myometrium at the lower end of the uterus, which was about 2 cm in diameter , until the uterine cavity was fully exposed, and then we intermittently evaginated the endometrium and sutured it to the serous layer to make a “bowl”, which was equivalent to creating a relatively wide outlet at the lower uterine segment; this was another key step of the surgery. Then, the artificial outlet at the lower uterine segment was intermittently anastomosed with the tip of the artificial vagina.Such a surgery has two advantages. First, the short-term advantage: it eliminates the need for prolonged use of a “uterine drainage tube” post-surgery and requires just a routine change of the vaginal mold, which makes short-term postoperative care easier and can be assigned to the patient’s family. Second, the long-term advantage: the outlet at the lower uterine segment is relatively wide, and this reduces the possibility of adhesion or even obstruction of the outlet at the lower uterine segment due to postoperative inflammation and scarring and avoids reoperation.The smooth postoperative recovery of the patient also confirmed the advantages of the surgery; the vaginal drainage tube was removed two days after the surgery, and the patient was discharged with the mold six days after the procedure. In the first month post-surgery, the patient had a menstrual cycle with unblocked discharge of menstrual blood and no abdominal pain. Afterwards, the patient had regular menstrual cycles every month without abdominal pain. There was no significant abnormality on re-examination six months after the surgery; no abnormal mass was seen on pelvic MR, and the functional primordial uterus was connected to the artificial vagina.We treated this case entirely by laparoscopic operation with minimal surgical trauma, and the patient recovered quickly after the operation. Reconstructive surgery enabled the preservation of the functional primordial uterus and its connection with the artificial vagina, ensuring unblocked menstrual drainage and relieving the stress of the patient and her family. In addition, the fertility potential of the patient was also preserved. The long-term impact and reproductive function are yet to be observed through follow-up.Below is the link to the electronic supplementary material.Supplementary Material 1


Robust and precise visual localization over extended periods of time poses a formidable challenge in the current domain of spatial vision. The primary difficulty lies in effectively addressing significant variations in appearance caused by seasonal changes  and diverse lighting conditions . With the rapid development of related technologies, more and more relevant datasets have emerged, which has also promoted the progress of 6-DOF visual localization in both directions of autonomous vehicles and handheld devices.This manuscript endeavors to rectify the existing limitations of the current public benchmark for long-term visual localization, especially in the part on the autonomous vehicle challenge. Taking into account that autonomous vehicle datasets are primarily captured by multi-camera rigs with fixed extrinsic camera calibration and consist of serialized image sequences, we present several proposed modifications designed to enhance the rationality and comprehensiveness of the evaluation algorithm. We advocate for standardized preprocessing procedures to minimize the possibility of human intervention influencing evaluation results. These procedures involve aligning the positions of multiple cameras on the vehicle with a predetermined canonical reference system, replacing the individual camera positions with uniform vehicle poses, and incorporating sequence information to compensate for any failed localized poses. These steps are crucial in ensuring a just and accurate evaluation of algorithmic performance. Lastly, we introduce a novel indicator to resolve potential ties in the Schulze ranking among submitted methods. The inadequacies highlighted in this study are substantiated through simulations and actual experiments, which unequivocally demonstrate the necessity and effectiveness of our proposed amendments. Estimating the Six-Degree-of-Freedom 6-DOF) pose of robot devices with respect to a known 3D model of the scene is a key technology in spacial vision. It serves as the basis for various applications in 3D scene, including augmented reality , visual -DOF poseTo achieve the aforementioned objectives, researchers have experimented with various techniques to minimize the fluctuation in feature expression while still maintaining the integrity of local image features. These methods include introducing more robust learning-based features ,14,15, iIn order to impartially assess the localization capabilities of current methods and encourage further research in this field, the long-term visual localization benchmark  is propoWhile the emergence of the benchmark offers a convenient platform for comparing various algorithms, it is crucial to acknowledge, based on our extensive experience with its usage, that current evaluation systems may possess potential limitations for improvement.To be specific, firstly, the existing benchmark evaluation method is reasonable and accurate in principle, which can accurately reflect the localization success rate of each camera, but it has an important premise; that is, the evaluated localization results are directly from the output of the visual localization algorithm, original and unmodified. This is natural for datasets captured by hand-held cameras, but for datasets captured by one or more cameras mounted on the vehicle, the extrinsic camera calibration information and the sequence relationship between the images are easily obtained from the dataset, and the existing benchmark cannot determine whether the submitted location results are original, which leaves room for introducing human intervention.Secondly, the ranking method used by the existing benchmark is a Condorcet method , which mIn order to establish a research environment that is equitable and conducive to the advancement of relevant fields, in this work, we propose several modifications to improve the two limitations mentioned above.As for the evaluation method, we advocate a unified process for preprocessing the submitted localization results and then evaluate the accuracy of the processed localization results. The preprocessing involves two main components. Firstly, for datasets captured by multi-camera rigs, the localization results of multiple cameras are aligned with a predetermined canonical reference system, and the resulting unified vehicle poses are utilized for evaluation, replacing the multiple individual camera poses. Secondly, for datasets containing sequence information, any failed localized poses are supplemented by interpolating with several successful localized poses associated with them.For the ranking method, we introduce a novel index designed specifically for visual localization algorithms, which is used to provide the basis for resolving potential ties in the existing ranking methods, considering the accuracy and robustness of the evaluated algorithms comprehensively. In view of the above, we believe that addressing these limitations can greatly enhance the effectiveness and overall acceptance of the benchmark.Through rigorous experimentation, we identify two limitations in the existing public benchmark for long-term visual localization evaluation: the inability of the evaluation method to eliminate human intervention, and the lack of judging basis for ranking methods when faced with tied ranking results. These limitations have the potential to hinder the accurate measurement of the localization capabilities of the methods submitted.In light of the limitations, we propose a unified process of preprocessing to the current evaluation method employed for localizing methods conducted on multi-camera datasets. Without compromising the practical significance of the autonomous vehicle localization problem, it provides another dimension for the dataset evaluation, which improves the fairness and reliability of the existing benchmark.We enhance the current ranking methodology to assist the benchmark in mitigating any potential confusion that may arise from deadlock scenarios when there is a tie between candidates during the ranking calculation process.In general, our contributions can be summarized as follows:The rest of the paper is organized as follows. The benchmark datasets for long-term visual localization ought to encompass query images captured under distinct conditions compared to the database images. This facilitates the analysis of the influence of varying conditions on the accuracy of localization. Nevertheless, it presents challenges in terms of feature matching for the generation of reliable ground truth.This presents considerable challenges for benchmarking 6-DOF visual localization in changing conditions. On the one hand, datasets with varying environmental conditions ,12,23,24Recently, Sattler et al.  developeThe benchmark evaluates the localization ability of a method by measuring its pose accuracy by the deviation between the estimated and the ground truth pose. The pose accuracy is determined by position error and orientation error. The position error is evaluated by the Euclidean distance as:The datasets included in the benchmark can be divided into two categories. They differ by how the images are captured: for the first category, images are captured by one or more cameras mounted on a vehicle, and the camera(s) will mostly undergo movement in a plane. Typical representatives are CMU-Seasons dataset ,32 and RThe CMU-Seasons dataset used in the benchmark is a subset of the CMU Visual localization dataset by Badino et al. . It showThe RobotCar Seasons dataset is another typical collection of images captured by a camera rig mounted on a vehicle. It is based on a subset of the Oxford RobotCar dataset , depictsThe Aachen Day-Night datasets are based on the original Aachen dataset , depictsThe ranking of the benchmark is performed using the Schultze method from . It is aDue to its numerous positive axiomatic attributes, the Schultze method is extensively utilized in database evaluation. A notable feature is that the Schulze method is a Condorcet method. This indicates that if a candidate is preferred by a majority over every other candidate in pairwise comparisons, then that candidate will emerge as the victor. This characteristic renders the Schultze method highly interpretable and compelling.However, in certain circumstances, a scenario may occur commonly known as the Condorcet cycle, in which there exists no Condorcet winner. This situation can be likened to a tie, as each candidate emerges victorious in a game, resulting in an equal number of victories for multiple candidates. In this particular situation, it is necessary to establish a metric in order to resolve the tie.Xm and The localization ability of a method is reflected by the benchmark for long-term visual localization  based onPrecisely in view of the differences between the above two categories of datasets mentioned in While the current benchmark is doing a great job handling these two challenges, our experience with its usage has shown that there are some areas we can improve. Firstly, the evaluation method is unable to completely eliminate human intervention. It is not feasible to determine whether the localization results of uploads with a uniform format have been artificially corrected or supplemented. In the case of autonomous vehicle datasets, obtaining extrinsic parameters of camera rigs or sequence information between images is relatively straightforward from the datasets. Consequently, this vulnerability may result in an unfair comparison between methods utilizing this correlation and pure visual localization methods that operate on individual images. Secondly, the ranking method occasionally produces ties, resulting in some entries appearing to have a higher rank than others, despite being ranked the same according to the ranking method.As a means of evaluating numerous mainstream methods, the benchmark must possess objectivity and impartiality in order to effectively demonstrate the localization capabilities of all methods. This will ultimately contribute to the advancement of long-term visual localization. In light of this, we present our proposed modifications.As previously stated, the existing benchmark evaluation method relies on the percentage of query images successfully localized within the three defined thresholds. However, it is important to note that this method primarily assesses the localization results of handheld devices. In the case of autonomous vehicles, the objective of visual localization is to ascertain the precise position and orientation of the vehicle itself within the environment. Hence, we assert that the evaluation process should incorporate the localization results obtained from multiple cameras installed on the vehicle. In essence, the localization outcomes of these multiple cameras ought to be consolidated into a single vehicle pose to accurately calculate the overall accuracy, rather than being assessed individually.This modification is absolutely necessary, since datasets with numerous cameras are frequently utilized and extrinsic camera calibration between the cameras used in the dataset can also be retrieved through given extrinsic files  or 3However, when dealing with datasets such as CMU-Seasons that lack intrinsic camera calibration, the utilization of the rig constraint becomes challenging. Submitters are left with no choice but to manually extract the rig information from the reference 3D model, as demonstrated in our own experiment in Moreover, given the presence of query image sequences for autonomous vehicles, it becomes possible to estimate the pose of certain fail-localized images within these sequences through interpolation between the two nearest successfully localized images. Concerning the interpolation technique, linear interpolation stands as the most straightforward approach , weather (sunny/rain/snow), and seasons (summer/winter), the localization results in each condition are also evaluated separately. This brings difficulties to comprehensive ranking. We studied the Schultze method employed by Sattler’s benchmark  and founIn the event of a deadlock, the Schulze Proportional Ranking method  effectivTo this end, we introduce a secondary indicator w so that alternative Our idea comes from the Resolvability  of the SThe secondary indicator Apparently, With the relaxation of the threshold, the percentage results increase monotonically, while the overall goal of visual localization is to obtain a fine-precision pose, so we believe that the coarse-precision threshold percentage reflects the basic localization ability of an evaluated algorithm. On this basis, under the same condition, a more precise algorithm has a higher fine-precision threshold percentage. Meanwhile, under the same accuracy threshold, a more robust algorithm has a smaller percentage difference between different conditions. The impact of the above secondary indicator on the ranking results can be seen in This section presents a series of experiments conducted using both simulated and real data to validate the deficiencies of the benchmark evaluation and ranking methods previously proposed. It aims to demonstrate the improvements achieved by implementing our proposed modifications.We build two meticulously crafted simulation datasets for the purpose of localization testing. Each dataset comprises 200 reference positions derived from 100 acquisition points, replicating the scenario of two front-facing cameras installed on a vehicle. These cameras are positioned at a 45-degree angle to the left or right side of the vehicle, as demonstrated in the CMU-Seasons dataset ,32.The primary objective of these datasets is to accurately simulate the localization process during the movement of a vehicle along both straight and curved routes. In the case of the straight route, the true trajectory follows an “S”-shaped path, consisting of five consecutive straight lines, each measuring 10 m in length. These lines are vertically connected to one another, as depicted in the left half of On the other hand, the curved route resembles an “S”-shaped path formed by two three-quarters circles with a radius of 5 m. As illustrated in the right half of It should be noted that the path settings of the two simulation datasets are applied to the trajectory of the left camera. According to rig information, the right camera of the vehicle automatically generates its own trajectory based on the left camera’s known trajectory. The route discrepancies between the cameras on both sides are highlighted by this configuration.Each camera rises equally 1.5 m above the ground.All acquisition points are evenly distributed according to the camera on the left to conform to the image acquisition method of most data sets. As a result, the distance between every two connected blue points in the left half of The localization success rate of the simulated query images in the tested method is 70%.The orientation error of all simulation query images can be disregarded, thus the determination of the localization result’s interval is solely contingent upon the position error.For the purpose of clarity, we proceed by establishing the following assumptions:The localization results of two simulation experiments are generated by adding Gaussian noise with a mean value of We, respectively, evaluate the localization results of the simulated method by the current benchmark evaluation method and by our improved method. Each experiment contains three modes: Basic, Basic_rig, and Basic_rig_seq, which separately represent the basic results of the simulation method, the supplemented results with extrinsic camera calibration information, and the supplemented results with both rig information and sequence interpolation.If both cameras of the rig are successfully localized, the pose of the right camera is compensated to the left. The average of their poses is then regarded as the vehicle’s pose.If only the left camera is successfully localized, its pose will be regarded as the pose of the vehicle.If only the right camera is successfully localized, the subsequent compensated result of the pose to the left is regarded as the vehicle’s pose.If no camera is successfully localized, the vehicle is regarded as fail-localized.The rig and seq supplementation are executed in accordance with the methodology outlined in The table demonstrates that both the Straight route and the Curved route exhibit the same tendency. Under each precision threshold in the current evaluation approach, rig operation and seq operation can significantly increase the localization algorithm’s accuracy. The rig operations of the two simulation experiments cannot, however, affect the basic results after substituting the improved method for the original one. Meanwhile, the improvement in the final results is much lessened even with the inclusion of seq operations (7.7% vs. 53.7% improvement for fine-precision threshold on Straight Route and 12.2% vs. 58.3% improvement for that on Curved route).Results show that such a modification can entirely suppress the rig operation’s influence and lessen the seq operation’s level of influence.To authenticate the influence of rig and seq supplementation on the localization results of real datasets, we conduct the ensuing experiment by utilizing the results of a prior study  on the CFor the rig supplementation, it should be noted that the CMU-Seasons dataset ,32 does For the seq supplementation, on the basis of the known poses, we look for fail-localized images and estimate their poses using linear interpolation between the two nearest successfully localized images.The percentage results augmented by rig and seq options significantly outperform the basic results, as shown in the table, in practically all scenarios and across all thresholds. As a result, even without any optimization to the localization algorithm, we can significantly improve the evaluation results, especially for fine-precision percentages and the most difficult park scene that is most susceptible to appearance changes in the CMU-Seasons dataset ,32. ThisThe experiment in this section aims to validate the efficacy of our ranking improvement method in making a distinction where the Schultze method yields tied results. Within the benchmark leaderboard, each threshold for every condition corresponds to a distinct “voter” as per the Schultze method. For instance, one such voter is denoted as “fine-precision for night images” in the Aachen Day-Night dataset ,29, whilUnlike most electoral systems, as an evaluation system for visual localization algorithms, the number of “voters” is usually less than the number of “candidates”. This configuration increases the likelihood of encountering a deadlock situation, particularly in cases where the dataset portrays a limited number of scenes or when different methods yield equal percentages.We use the data from the leaderboard of the Aachen Day-Night v1.1 dataset ,29,39 onIn the first experiment, we employ the Schultze method on the ranking data in To break the ties, another ballot that combines the Intra-condition Balance (Take the tie of Method 3 and Method 4 in the third place in For Method 3:For Method 4:Then, the seventh “voter” will come forward and say that he prefers Method 4, which determines the final order in the tie. Except for the case where the data of Method 10 and Method 11 are exactly the same, our method produces a strict partial order of all methods. Compared with the original ranking in The objective of this simulation experiment is to replicate the impact of rig operation and seq operation on the evaluation results of a specific localization method, and to substantiate, to a certain degree, whether the influence of these two operations is mitigated after implementing the proposed enhancement method. Due to the unavailability of the real benchmark’s test datasets, we are limited to utilizing two common path patterns, namely straight line and curve, to observe the implementation specifics of these two operations. Although there are evident disparities between the simulated scenarios and the actual environment, encompassing path morphology, distribution of simulated data, and the success rate of the localization method, the experimental findings adequately reflect the issue at hand. Specifically, operations resembling rig and seq have a significant impact on the localization results of the method, and, to some extent, this impact may even surpass the accuracy improvement achieved through the overall framework optimization of the algorithm. By adopting the proposed enhancements, the benchmark will experience a reduction in the magnitude of this impact.The objective of this actual dataset experiment is to authenticate the dependability of the aforementioned simulation experiment. It is hard to ascertain if other submission techniques employ rig and seq operations, and it is not feasible to alter the assessment algorithm of the benchmark . As a reAll we can do is perform reverse validation using the intervention methods mentioned above. Without incorporating our modifications into the existing benchmark, if human intervention is employed to complement the original results generated by the localization algorithm—specifically, using rig information to supplement the individual pose of certain fail-localized cameras, and subsequently using seq information to further complete the trajectory of each individual camera—what will be the extent of its impact on the evaluation results? The experiment results indicate that, at least in the context of our prior research , after iThe objective of this ranking experiment is to replicate a potential deadlock situation and assess whether the inclusion of new indicators can yield logical ranking outcomes to resolve the deadlock dilemma. In order to accomplish this, the experimental data employed is sourced directly from the leaderboard of the Aachen Day-Night v1.1 dataset ,29,39 onAdmittedly, the amendments mentioned in this article make the benchmark more complex and unintuitive, and the rig and seq operations involved are more specific to autonomous vehicles. For datasets obtained from a solitary camera and datasets lacking sequence information, the consideration of the Canonical Reference setting is unnecessary. The current evaluation methods utilized in the benchmark are deemed satisfactory for these cases.Furthermore, substituting camera rig localization results for multiple camera localization results does result in a reduction in evaluation sensitivity. This is evident in the fact that, at a specific location, the localization results are deemed successful as long as one camera in the rig is successfully located, regardless of any other camera localization failures. This makes it impossible to highlight some methods with a high success rate of individual localization. For this reduction, our view is that, since the existing benchmark has separated the evaluation into challenges for autonomous vehicles and handheld devices, the focus of autonomous vehicle localization should be on determining the posture of the vehicle itself, rather than the individual cameras.Given the rapid advancements in autonomous driving and SLAM technology, visual localization is now encountering numerous instances of multi-sensor fusion and serialized images in real-world scenarios. Consequently, it becomes imperative to establish standardized evaluation criteria for localizing this specific subset of data. Our modification presents an additional dimension for evaluating datasets containing camera rigs and serialization information while maintaining the practical significance of the localization problem faced by autonomous vehicles. Such standardization will foster a fair and equitable environment for algorithmic competitions, ultimately leading to the emergence of more refined localization techniques that closely align with practical applications.Changes related to benchmarks are potentially important as the benchmark is widely adopted for structure from motion, data association, and 6-DoF tracking/relocalization, etc. It may help to improve the benchmark to better measure the quality of a proposed matching/localization method. Therefore, it should also be treated with greater caution.The inspiration for this endeavor was derived from our meticulous examination of prior work. Upon establishing a comprehensive framework for visual localization algorithms, we discovered that actions such as rigging and sequencing can significantly impact the algorithm’s performance on the benchmark. Although this influence may not dramatically alter the performance of the localization algorithm, it possesses sufficient potency to distinguish it from algorithms of comparable levels. Consequently, this phenomenon may impede researchers from identifying avenues that harbor genuine potential for groundbreaking advancements. It is precisely due to this rationale that we believe that only through the uniform treatment of marginal operations at the benchmark level can we genuinely ensure that researchers’ focus remains directed towards the development and exploration of algorithmic subjects.The modification scheme proposed in this paper may not be flawless. For instance, during the compensation of the pose of multiple cameras to a pre-defined reference system of the vehicle, the camera extrinsic parameters utilized are obtained from the published data of the dataset, which typically contains an error. Consequently, the cameras apart from the canonical camera may exhibit additional noise during evaluation. How to avoid this effect might be worthy of future research.In this paper, we present a series of proposed modifications to enhance the current benchmark for long-term visual localization. To accurately assess the localization ability of a submitted method on datasets comprising images captured by multiple cameras mounted on the vehicle, we suggest employing the compensated vehicle pose as an evaluation metric. Additionally, for datasets containing sequence information, we suggest performing a preprocessing step of standardized interpolation for a submitted method.Moreover, we introduce an indicator based on existing data that provides a comprehensive reflection of a localization method’s cross-condition robustness and intra-condition fine-precision ratio. This indicator serves to mitigate any potential confusion arising from ties during ranking calculations.The extensive experiments performed on both simulated and actual datasets confirm the deficiencies we discovered, thus demonstrating the necessity as well as the effectiveness of our modifications.


The aim of this study was to investigate a possible relation between skeletal phenotypes and virtual mounting data in orthognathic surgery patients. A retrospective cohort study including 323 female (26.1 ± 8.7 years) and 191 male (27.9 ± 8.3 years) orthognathic surgery patients was conducted. A k-means cluster analysis was performed on the mounting parameters: the angle  In the pre-digital era, orthognathic surgery was generally planned using plaster models. These were placed in mean value or semi-adjustable articulators and allowed a more or less individual position of the jaws in relation to the hinge axis, with equal pro-, latero- and opening movements. The mounting of the models can be carried out either by using a facebow or by using the averages of the Bonwill triangle and Balkwill angle. Bonwill described an equilateral triangle of 101.6 mm connecting the midpoints of the condyles and the contact point of the lower central incisors, based on the measurements of 4000 skulls and 6000 living individuals ,3,4,5. BWith the continuous evolution of CAD/CAM technologies in dentistry, different ideas have been introduced to virtually create a patient-specific situation of the facial and masticatory apparatus. Two main procedures are described: (a) the direct workflow with a virtual facebow, and (b) an indirect workflow with a desktop laboratory scanner that transfers a mechanical articulator to a virtual articulator . The tecAlthough planning in orthognathic surgery has conventionally always been performed in the articulator, new methods do not use the virtual articulator approach, but focus on simulating osteotomies using CBCT . The majThe simulation of rotational movements around the hinge axis is essential during orthognathic surgery planning. For this reason, we have developed a three-dimensional planning system for orthognathic surgery based on the principles of a virtual articulator: the Digital Münster Model Surgery (DMMS) system. The methodology of the DMMS has been published elsewhere , but forThe DMMS was developed based on conventional plaster surgery described by Ehmer et al. ,15,16. SA retrospective analysis of the marked radiographs showed that the position of the maxillary dentition in relation to the axis orbital plane (AOP) can be calculated using four landmarks: deepest point on the lower border of the meatus acusticus externus , nasal support of the face-bow (Ns), upper incisor edge (Ie), and distobuccal cusp of the first permanent upper molar (Dc) . Based oite fork ,13.The software ImageJ  can be uThe aim of the study was, therefore, to investigate a possible relationship between preoperative cephalometric measurements and virtual mounting values in a large group of patients who underwent the digital orthognathic surgery workflow.This retrospective cohort study received approval from the Ethics Commission of the Medical Faculty of the University of Münster, Germany (2021-120-f-S). The study took place at the Dental School of the University Hospital, Münster, Germany. All cases included in the study were planned with the DMMS in the Department of Orthodontics and underwent orthognathic surgery in the Department of Cranio-Maxillofacial Surgery between February 2018 and December 2022. A further inclusion criterion was the completeness of the preoperative planning documents, i.e., the mounting values , preoperDue to the large number of medical records that needed to be screened, the initial step was to write Python scripts to automatically read out the relevant data and to check for completeness. In the next step, the data were aggregated on a patient-by-patient basis to perform a cluster analysis. Subsequently, the patients assigned to each cluster were evaluated with respect to their skeletal configuration to identify cluster-specific skeletal phenotypes. Finally, the mounting values were compared with the Bonwill and Balkwill averages, assuming that one arm of the Bonwill triangle can be compared with the distance Ie-Ax  and the A k-means cluster analysis was performed to group similar data points (clusters) of the mounting variables  and 191 male (mean age 27.9 ± 8.3 years) patients. The male patients were significantly older than the female patients  and vertical distances (AxV), significantly larger values were measured in males  test revealed that only 9 of 22 cephalometric variables were statistically different between each cluster . Other vThe nine included variables are representative for the entire cephalometric analysis: three variables describe the mandible, two the maxilla, one the maxillo-mandibular relation, and three individual values characterize the facial type, the dental area and the soft tissue profile. It is noticeable that only one angle  describes the vertical pattern. Other important vertical variables, such as lower facial height or mandibular plane, were not suitable to differentiate between all three clusters.The most prominent cluster is cluster 2. In this cluster, predominantly female patients were included, and seven of nine variables indicate a vertical face combined with skeletal class II. There were also more female patients in cluster 3 but with variables indicating a horizontal face combined with skeletal class III . It appears that all patients who are not clearly skeletal class II or III are grouped in cluster 1. Seven of nine variables in cluster 1 are classified as balanced, one indicates class II, and one class III. The main difference in relation to the other clusters is that more male than female patients are represented here, and thus, larger values for AxH and AxV are present.The distance Ie-Ax as an approximation of the Bonwill arm and the calculation of the Balkwill angle is given in The principles of an analogue or virtual articulator, i.e., the spatial assembly of the maxilla, mandible and hinge axis to perform movements of the mandible in relation to the maxilla, remains an indispensable tool in dentistry. Regardless of all the controversies about the existence of a pure rotational movement  within tIn orthognathic surgery, the situation is different from non-surgical oral rehabilitations that require planning in a  articulator, because the hinge axis determined preoperatively has a different importance than that determined in the postoperative situation. When planning an orthognathic procedure, the rotation of the mandible around the hinge axis is not only necessary for the fabrication of a surgical splint, but also when working with the concept of autorotation . In a feAlthough an accurate determination of the maxillo-mandibular relation is mandatory in orthognathic surgery planning, this relation is lost during the surgical procedure. By separating the mandible into proximal joint-bearing segments and a distal tooth-bearing segment, maintaining a physiological joint position seems to be complex. The condyles adopt a new position during surgery , and theExtracting the hinge axis and its corresponding distance to the upper jaw from the lateral cephalogram is a separate process that contributes to the overall planning time. To save this step and to facilitate the mounting of intraoral scans in virtual space, a search for corresponding patterns in patients who had undergone orthognathic surgery was conducted. We could identify three patient groups with significantly different mounting values, which also differ in terms of the skeletal parameters .Based on the results, we concluded that the virtual maxilla of vertical face class II  patients can be arbitrarily mounted at an angle of (rounded) sor edge . The appThe results of this study show that the Bonwill and Balkwill averages are not suitable to arbitrarily mount the jaws of a group of patients in need of orthognathic surgery. It can be assumed that these patients differ from the average study participants of Bonwill and Balkwill due to their skeletal malocclusion. A study regarding Bonwill and Balkwill averages in 120 randomly selected CBCT datasets of patients who did not undergo orthognathic surgery supports our findings . The autArticulators have been used for decades in orthognathic surgery planning with excellent clinical success ,29. The The decision to use a planning system based on a physical articulator, a virtual articulator or a CBCT is not a decision relating to accuracy, as all systems provide similar results  and remaThe present study has several limitations. First of all, it is important to mention the retrospective nature of the study and the specific patient cohort, which may vary from clinic to clinic. The values determined in this study can therefore only be transferred to other cohorts to a limited extent. The evaluated records are taken from routine patient care, so that an inter-individual magnitude of error must be assumed in the analysis of the radiographs, both for cephalometry and for virtual mounting. However, a strength of the study can be seen in the high number of included patients. This ensures that different skeletal malocclusions are represented in large numbers.This is the first study to provide arbitrary values to virtually mount intraoral scans for orthognathic surgery planning. The obtained data on the position of the hinge axis can be applied to any digital planning in orthognathic surgery using CBCT or a virtual articulator, provided that the case to be planned can be clearly assigned to one of the clusters. Bonwill and Balkwill averages are not suitable for orthognathic surgery planning.


Negative symptoms (NS) represent an unmet need of treatment in schizophrenia (SCZ). As a result, these symptoms pose a significant burden on patients, their families, and the health care system. In the last decade, the conceptualization model that has received the most support from the literature has described 2 domains of NS: the expressive deficit (EXP), which includes blunted affect and alogia, and the motivational deficit (MAP), which includes avolition, asociality, and anhedonia. However, different confirmatory factor-analytic studies suggest that the bi-dimensional model may not capture the complexity of this construct, which could be better defined by the 5-factor model. To date no study exploiting innovative tools and state of the art assessment instruments has yet been conducted to evaluate the NS structure stability over time.The aim of this study was to investigate the stability of the latent structure of NS in subjects with SCZ.NS were assessed in 612 subjects with SCZ using the Brief Negative Symptom Scale (BNSS) at the baseline and after 4-year follow-up. A network invariance analysis was conducted for the data collected longitudinally.Results showed that the BNSS’ items aggregated to form 5 distinct domains . The result of the network invariance test indicated that the network structure remained unchanged over time  while its overall strength decreased significantly .The results of this study show how the construct of NS can be better explained by the 5 individual negative symptoms and that this model is almost stable over time. Therefore the 2-dimensional model may be insufficient to describe the characteristics of NS. This data is of important relevance with consequent implications in the study of pathophysiological mechanisms and the development of targeted treatments for NS.None Declared