Research on Medical Image Segmentation Method

被引：1
|
作者：
Song, Fangfang [1 ]
Tian, Yimin [1 ]
Gao, Xue [1 ]
Yang, Shuai [1 ]
Zheng, Meijun [1 ]
机构：
[1] BIGC, Dept Elect Informat, Beijing, Peoples R China
来源：
2021 3RD INTERNATIONAL CONFERENCE ON MACHINE LEARNING, BIG DATA AND BUSINESS INTELLIGENCE (MLBDBI 2021) | 2021年
基金：
中国国家自然科学基金;
关键词：
medical image; image segmentation; deep learning;
D O I：
10.1109/MLBDBI54094.2021.00115
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Medical image segmentation is one of the key tasks of modern medical computer-aided diagnosis. The purpose is to accurately segment the target area and provide effective help for doctors to diagnose and treat patients. Therefore, the quality of medical image segmentation has a great impact on the doctor's diagnosis of the patient's condition and the subsequent treatment of the patient. Research on medical image segmentation technology at home and abroad, summarized five medical image segmentation methods based on threshold, edge detection, region growth, fuzzy clustering and deep learning, and analyze the performance, summarize the research of modern medical image segmentation specialty.
引用
收藏
页码：577 / 580
页数：4
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