  Medical image segmentation is particularly critical as a prerequisite for
relevant quantitative analysis in the treatment of clinical diseases. For
example, in clinical cervical cancer radiotherapy, after acquiring subabdominal
MRI images, a fast and accurate image segmentation of organs and tumors in MRI
images can optimize the clinical radiotherapy process, whereas traditional
approaches use manual annotation by specialist doctors, which is time-consuming
and laborious, therefore, automatic organ segmentation of subabdominal MRI
images is a valuable research topic.

Image and Video Processing;Computer Vision and Pattern Recognition;Machine Learning