A Comprehensive Review of Markov Random Field and Conditional Random Field Approaches in Pathology Image Analysis
نویسندگان
چکیده
Pathology image analysis is an essential procedure for clinical diagnosis of many diseases. To boost the accuracy and objectivity detection, nowadays, increasing number computer-aided (CAD) system proposed. Among these methods, random field models play indispensable role in improving performance. In this review, we present a comprehensive overview pathology based on markov fields (MRFs) conditional (CRFs), which are two popular models. Firstly, introduce background images. Secondly, summarize basic mathematical knowledge MRFs CRFs from modelling to optimization. Then, thorough review recent research images presented. Finally, investigate methodologies related works discuss method migration among CAD field.
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ژورنال
عنوان ژورنال: Archives of Computational Methods in Engineering
سال: 2021
ISSN: ['1886-1784', '1134-3060']
DOI: https://doi.org/10.1007/s11831-021-09591-w