Prior knowledge snake segmentation of ultrasound images denoised by J-divergence anisotropy diffusion.
BACKGROUND
Applying transrectal ultrasound to robot-assisted laparoscopic radical prostatectomy has attracted attention in recent years, and it is considered as a proper method to provide real-time subsurface anatomic features. A precise registration between the ultrasound equipment and robotic surgical system is necessary, which usually requires a fast and accurate recognition of the registration tool in the ultrasound image.


METHODS
Tissue forceps are chosen as the registration tool. J-divergence anisotropy diffusion and prior knowledge snake segmentation are proposed for the automatic recognition of forceps in ultrasound images.


RESULTS
Simulation, gel tissue phantom experiments and in vitro experiments are carried out. Several evaluation indices are calculated to compare results under different methods.


CONCLUSIONS
The proposed methods are proved to be practicable, reliable and superior to existing ones, with reduced calculation time and higher accuracy.
['Yan|Jiawen|J|http://orcid.org/0000-0002-5554-8650', 'Pan|Bo|B|', 'Qi|Yunfeng|Y|', 'Ben|Jin|J|', 'Fu|Yili|Y|']
D000465:Algorithms D016880:Anisotropy D006801:Humans D008297:Male D019047:Phantoms, Imaging D011468:Prostatectomy D011471:Prostatic Neoplasms D025321:Surgery, Computer-Assisted D014463:Ultrasonography
prior knowledge snake segmentation ultrasound image anisotropy diffusion denoising