Identifying Periampullary Regions in MRI Images Using Deep Learning.

ABSTRACT:

Background

Development and validation of a deep learning method to automatically segment the peri-ampullary (PA) region in magnetic resonance imaging (MRI) images.

Methods

A group of patients with or without periampullary carcinoma (PAC) was included. The PA regions were manually annotated in MRI images by experts. Patients were randomly divided into one training set, one validation set, and one test set. Deep learning methods were developed to automatically segment the PA region in MRI images. The segmentation performance of the methods was compared in the validation set. The model with the highest intersection over union (IoU) was evaluated in the test set.

Results

The deep learning algorithm achieved optimal accuracies in the segmentation of the PA regions in both

SUBMITTER: Tang Y 

PROVIDER: S-EPMC8193851 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature