The effect of the re-segmentation method on improving the performance of rectal cancer image segmentation models.
Journal:
Technology and health care : official journal of the European Society for Engineering and Medicine
Published Date:
Jan 1, 2024
Abstract
BACKGROUND: Rapid and accurate segmentation of tumor regions from rectal cancer images can better understand the patientâs lesions and surrounding tissues, providing more effective auxiliary diagnostic information. However, cutting rectal tumors with deep learning still cannot be compared with manual segmentation, and a major obstacle to cutting rectal tumors with deep learning is the lack of high-quality data sets.