Visual Pattern Analysis in Histopathology Images Using Bag of Features

Authors:
Angel Cruz-Roa;Juan C. Caicedo;Fabio A. González
Affiliations:
Bioingenium Research Group, Universidad Nacional de Colombia,;Bioingenium Research Group, Universidad Nacional de Colombia,;Bioingenium Research Group, Universidad Nacional de Colombia,
Venue:
CIARP '09 Proceedings of the 14th Iberoamerican Conference on Pattern Recognition: Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications
Year:
2009

Citing 2
Cited 1

Histopathology Image Classification Using Bag of Features and Kernel Functions

AIME '09 Proceedings of the 12th Conference on Artificial Intelligence in Medicine: Artificial Intelligence in Medicine
A pattern similarity scheme for medical image retrieval

IEEE Transactions on Information Technology in Biomedicine - Special section on biomedical informatics

Histology image indexing using a non-negative semantic embedding

MCBR-CDS'11 Proceedings of the Second MICCAI international conference on Medical Content-Based Retrieval for Clinical Decision Support

Quantified Score

Hi-index	0.00

Visualization

Abstract

This paper presents a framework to analyse visual patterns in a collection of medical images in a two stage procedure. First, a set of representative visual patterns from the image collection is obtained by constructing a visual-word dictionary under a bag-of-features approach. Second, an analysis of the relationships between visual patterns and semantic concepts in the image collection is performed. The most important visual patterns for each semantic concept are identified using correlation analysis. A matrix visualization of the structure and organization of the image collection is generated using a cluster analysis. The experimental evaluation was conducted on a histopathology image collection and results showed clear relationships between visual patterns and semantic concepts, that in addition, are of easy interpretation and understanding.