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A Comprehensive Review of Markov Random Field and Conditional Random Field Approaches in Pathology Image Analysis
Li, Yixin1; Li, Chen1; Li, Xiaoyan2; Wang K(王锴)3; Rahaman, Md Mamunur1; Sun, Changhao1; Chen, Hao4; Wu, Xinran1; Zhang, Hong5; Wang, Qian2
Department工业控制网络与系统研究室
Source PublicationArchives of Computational Methods in Engineering
ISSN1134-3060
2022
Volume29Issue:1Pages:609-639
Indexed BySCI ; EI
EI Accession number20211910339885
WOS IDWOS:000644755000001
Contribution Rank3
Funding OrganizationNational Natural Science Foundation of China (No. 61806047) ; Fundamental Research Funds for the Central Universities (No. N2019003) ; China Scholarship Council (No. 2018GBJ001757)
Abstract

Pathology image analysis is an essential procedure for clinical diagnosis of numerous diseases. To boost the accuracy and objectivity of the diagnosis, nowadays, an increasing number of intelligent systems are proposed. Among these methods, random field models play an indispensable role in improving the investigation performance. In this review, we present a comprehensive overview of pathology image analysis based on the Markov Random Fields (MRFs) and Conditional Random Fields (CRFs), which are two popular random field models. First of all, we introduce the framework of two random field models along with pathology images. Secondly, we summarize their analytical operation principle and optimization methods. Then, a thorough review of the recent articles based on MRFs and CRFs in the field of pathology is presented. Finally, we investigate the most commonly used methodologies from the related works and discuss the method migration in computer vision.

Language英语
WOS SubjectComputer Science, Interdisciplinary Applications ; Engineering, Multidisciplinary ; Mathematics, Interdisciplinary Applications
WOS KeywordRETINAL VESSEL SEGMENTATION ; CLASSIFICATION ; MODEL
WOS Research AreaComputer Science ; Engineering ; Mathematics
Funding ProjectNational Natural Science Foundation of China[61806047] ; Fundamental Research Funds for the Central Universities[N2019003] ; China Scholarship Council[2018GBJ001757]
Citation statistics
Document Type期刊论文
Identifierhttp://ir.sia.cn/handle/173321/28861
Collection工业控制网络与系统研究室
Corresponding AuthorLi, Chen; Li, Xiaoyan
Affiliation1.Microscopic Image and Medical Image Analysis Group, College of Medicine and Biological Information Engineering, Northeastern University, Shenyang, China
2.Department of Pathology, Liaoning Cancer Hospital and Institute, Shengyan, China
3.Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang, China
4.School of Nanjing University of Science and Technology, Nanjing, China
5.Shengjing Hospital of China Medical University, Shenyang, China
Recommended Citation
GB/T 7714
Li, Yixin,Li, Chen,Li, Xiaoyan,et al. A Comprehensive Review of Markov Random Field and Conditional Random Field Approaches in Pathology Image Analysis[J]. Archives of Computational Methods in Engineering,2022,29(1):609-639.
APA Li, Yixin.,Li, Chen.,Li, Xiaoyan.,Wang K.,Rahaman, Md Mamunur.,...&Wang, Qian.(2022).A Comprehensive Review of Markov Random Field and Conditional Random Field Approaches in Pathology Image Analysis.Archives of Computational Methods in Engineering,29(1),609-639.
MLA Li, Yixin,et al."A Comprehensive Review of Markov Random Field and Conditional Random Field Approaches in Pathology Image Analysis".Archives of Computational Methods in Engineering 29.1(2022):609-639.
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