Automated Detection of Gastric Cancer by Retrospective Endoscopic Image Dataset Using U-Net R-CNN

Automated Detection of Gastric Cancer by Retrospective Endoscopic Image Dataset Using U-Net R-CNN

Upper gastrointestinal endoscopy is widely performed to detect early gastric cancers. As an automated detection method for early gastric cancer from endoscopic images, a method involving an object detection model, which is a deep learning technique, was proposed. However, there were challenges regar...

Full description

Bibliographic Details
Main Authors: Atsushi Teramoto, Tomoyuki Shibata, Hyuga Yamada, Yoshiki Hirooka, Kuniaki Saito, Hiroshi Fujita
Format: Article
Language:English
Published: MDPI AG 2021-11-01
Series:Applied Sciences
Subjects:
gastric cancer
endoscopy
deep learning
convolutional neural network
Online Access:https://www.mdpi.com/2076-3417/11/23/11275

Similar Items

Similar Items