Review of Medical Image Segmentation Methods

Abstract

Medical image is one of the key factors in the process of medical diagnosis and treatment. By analyzing the medical image obtained, doctors make judgments on the patient's condition and plan the next treatment process. Medical image segmentation is the process of segmenting areas of interest in medical images according to specific needs, which is a key step in medical image processing and analysis. With the great improvement of computer processing power, how to quickly and effectively segment huge image data and mining valuable information is the research hotspot of segmentation algorithm at present. This paper introduces several traditional medical image segmentation methods such as threshold method and region method, as well as convolutional neural network and Transformer segmentation method based on deep learning technology. Finally, this paper makes a summary and prospects for future development.