A method for detecting ureteral stent encrustations in medical CT images based on Mask-RCNN and 3D morphological analysis.

ABSTRACT:

Objective

To develop and validate a method for detecting ureteral stent encrustations in medical CT images based on Mask-RCNN and 3D morphological analysis.

Method

All 222 cases of ureteral stent data were obtained from the Fifth Affiliated Hospital of Sun Yat-sen University. Firstly, a neural network was used to detect the region of the ureteral stent, and the results of the coarse detection were completed and connected domain filtered based on the continuity of the ureteral stent in 3D space to obtain a 3D segmentation result. Secondly, the segmentation results were analyzed and detected based on the 3D morphology, and the centerline was obtained through thinning the 3D image, fitting and deriving the ureteral stent, and obtaining radial sections. Finally, the abnormal are

SUBMITTER: Hu H 

PROVIDER: S-EPMC11394187 | biostudies-literature | 2024

REPOSITORIES: biostudies-literature