Semi-Supervised Segmentation Framework for Gastrointestinal Lesion Diagnosis in Endoscopic Images

Semi-Supervised Segmentation Framework for Gastrointestinal Lesion Diagnosis in Endoscopic Images

Background: Accurate gastrointestinal (GI) lesion segmentation is crucial in diagnosing digestive tract diseases. An automatic lesion segmentation in endoscopic images is vital to relieving physicians’ burden and improving the survival rate of patients. However, pixel-wise annotations are highly int...

Full description

Bibliographic Details
Main Authors: Zenebe Markos Lonseko, Wenju Du, Prince Ebenezer Adjei, Chengsi Luo, Dingcan Hu, Tao Gan, Linlin Zhu, Nini Rao
Format: Article
Language:English
Published: MDPI AG 2023-01-01
Series:Journal of Personalized Medicine
Subjects:
gastrointestinal disease diagnosis
gastrointestinal lesion segmentation
endoscopic images
semi-supervised learning
computer-aided diagnosis
generative adversarial learning
Online Access:https://www.mdpi.com/2075-4426/13/1/118

Internet

https://www.mdpi.com/2075-4426/13/1/118

Similar Items