MRI-based automatic identification and segmentation of extrahepatic cholangiocarcinoma using deep learning network.

ABSTRACT:

Background

Accurate identification of extrahepatic cholangiocarcinoma (ECC) from an image is challenging because of the small size and complex background structure. Therefore, considering the limitation of manual delineation, it's necessary to develop automated identification and segmentation methods for ECC. The aim of this study was to develop a deep learning approach for automatic identification and segmentation of ECC using MRI.

Methods

We recruited 137 ECC patients from our hospital as the main dataset (C1) and an additional 40 patients from other hospitals as the external validation set (C2). All patients underwent axial T1-weighted imaging (T1WI), T2-weighted imaging (T2WI), and diffusion-weighted imaging (DWI). Manual delineations were performed and served as the gro

SUBMITTER: Yang C 

PROVIDER: S-EPMC10636947 | biostudies-literature | 2023 Nov

REPOSITORIES: biostudies-literature