Combination of UNet++ and ResNeSt to classify chronic inflammation of the choledochal cystic wall in patients with pancreaticobiliary maljunction.

Objectives: The aim of this study was to establish an automatic classification model for chronic inflammation of the choledoch wall using deep learning with CT images in patients with pancreaticobiliary maljunction (PBM).

Methods: CT images were obtained from 76 PBM patients, including 61 cases assigned to the training set and 15 cases assigned to the testing set. The region of interest (ROI) containing the choledochal lesion was extracted and segmented using the UNet++ network.