A review of automatic liver tumor segmentation based on computed tomography.
10.7507/1001-5515.201708009
- Author:
Meiyan YUE
1
;
Qianyue WEI
1
;
Wei DENG
2
;
Tianfu WANG
1
;
Yun DENG
1
;
Bingsheng HUANG
1
Author Information
1. School of Biomedical Engineering, Shenzhen University, Shenzhen, Guangdong 518060, P.R.China.
2. Department of Radiology, Guangzhou Panyu Central Hospital, Guangzhou 511400, P.R.China.
- Publication Type:Journal Article
- Keywords:
automatic segmentation;
computed tomography;
liver cancer;
machine learning
- From:
Journal of Biomedical Engineering
2018;35(3):481-487
- CountryChina
- Language:Chinese
-
Abstract:
Liver cancer is a common type of malignant tumor in digestive system. At present, computed tomography (CT) plays an important role in the diagnosis and treatment of liver cancer. Segmentation of tumor lesions based on CT is thus critical in clinical diagnosis and treatment. Due to the limitations of manual segmentation, such as inefficiency and subjectivity, the automatic and accurate segmentation based on advanced computational techniques is becoming more and more popular. In this review, we summarize the research progress of automatic segmentation of liver cancer lesions based on CT scans. By comparing and analyzing the results of experiments, this review evaluate various methods objectively, so that researchers in related fields can better understand the current research progress of liver cancer segmentation based on CT scans.
