A Comprehensive Review for MRF and CRF Approaches in Pathology Image Analysis

by   Chen Li, et al.

Pathology image analysis is an essential procedure for clinical diagnosis of many diseases. To boost the accuracy and objectivity of detection, nowadays, an increasing number of computer-aided diagnosis (CAD) system is proposed. Among these methods, random field models play an indispensable role in improving the analysis 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. Firstly, we introduce the background of two random fields and pathology images. Secondly, we summarize the basic mathematical knowledge of MRFs and CRFs from modelling to optimization. Then, a thorough review of the recent research on the MRFs and CRFs of pathology images analysis is presented. Finally, we investigate the popular methodologies in the related works and discuss the method migration among CAD field.



There are no comments yet.


page 1

page 6

page 7

page 9

page 14

page 15

page 16

page 20


mrf2d: Markov random field image models in R

Markov random fields on two-dimensional lattices are behind many image a...

A Comparative Study of Techniques of Distant Reconstruction of Displacement Fields by using DISTRESS Simulator

Reconstruction and monitoring of displacement and strain fields is an im...

Inference tools for Markov Random Fields on lattices: The R package mrf2d

Markov random fields on two-dimensional lattices are behind many image a...

A two-layer Conditional Random Field for the classification of partially occluded objects

Conditional Random Fields (CRF) are among the most popular techniques fo...

A Review of Statistical Learning Machines from ATR to DNA Microarrays: design, assessment, and advice for practitioners

Statistical Learning is the process of estimating an unknown probabilist...

Spatial Confidence Regions for Combinations of Excursion Sets in Image Analysis

The analysis of excursion sets in imaging data is essential to a wide ra...

On the trade-off between complexity and correlation decay in structural learning algorithms

We consider the problem of learning the structure of Ising models (pairw...
This week in AI

Get the week's most popular data science and artificial intelligence research sent straight to your inbox every Saturday.