Research progress of computer aided diagnosis system for pulmonary nodules in CT images.
BACKGROUND AND OBJECTIVE
Since CAD (Computer Aided Diagnosis) system can make it easier and more efficient to interpret CT (Computer Tomography) images, it has gained much attention and developed rapidly in recent years. This article reviews recent CAD techniques for pulmonary nodule detection and diagnosis in CT Images.


METHODS
CAD systems can be classified into computer-aided detection (CADe) and computer-aided diagnosis (CADx) systems. This review reports recent researches of both systems, including the database, technique, innovation and experimental results of each work. Multi-task CAD systems, which can handle segmentation, false positive reduction, malignancy prediction and other tasks at the same time. The commercial CAD systems are also briefly introduced.


RESULTS
We have found that deep learning based CAD is the mainstream of current research. The reported sensitivity of deep learning based CADe systems ranged between 80.06% and 94.1% with an average 4.3 false-positive (FP) per scan when using LIDC-IDRI dataset, and between 94.4% and 97.9% with an average 4 FP/scan when using LUNA16 dataset, respectively. The overall accuracy of deep learning based CADx systems ranged between 86.84% and 92.3% with an average AUC of 0.956 reported when using LIDC-IDRI dataset.


CONCLUSIONS
We summarized the current tendency and limitations as well as future challenges in this field. The development of CAD needs to meet the rigid clinical requirements, such as high accuracy, strong robustness, high efficiency, fine-grained analysis and classification, and to provide practical clinical functions. This review provides helpful information for both engineering researchers and radiologists to learn the latest development of CAD systems.
['Wang|Yu|Y|', 'Wu|Bo|B|', 'Zhang|Nan|N|', 'Liu|Jiabao|J|', 'Ren|Fei|F|', 'Zhao|Liqin|L|']
D006801:Humans D008168:Lung D008175:Lung Neoplasms D011857:Radiographic Image Interpretation, Computer-Assisted D015203:Reproducibility of Results D012680:Sensitivity and Specificity D003074:Solitary Pulmonary Nodule D014057:Tomography, X-Ray Computed
Pulmonary nodules computer-aided detection (CADe) multi-task CAD computer-aided diagnosis 
(CADx)