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Colorectal segmentation in medical images

Colorectal cancer is one of the digestive tract malignant tumors in life. In recent years, the incidence rate of rectal cancer has increased significantly in China. The segmentation of CT images of colorectal tumors is a tedious, time-consuming and expensive job.When diagnosing rectal cancer, it would be helpful to accurately segment the rectal tumor region from CT images so that doctors could make more accurate diagnoses and thus have better results for the disease. Based on the literature review, this paper presents medical image segmentation algorithms, including traditional algorithms based on energy minimization, and evaluates them according to the metrics used. The paper also describes the public datasets available for use in the study. In this paper, various segmentation methods are analyzed in detail. Their theoretical and practical characteristics are described for each group of methods, and the most advanced and promising methods are proposed. This paper can help understand the available colorectal segmentation methods, making developing new and more effective and improving existing methods easier. The method is simple to interact with, robust and accurate, and can effectively assist physicians in achieving diagnosis and surgical planning.