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2009
IEEE

A medical image retrieval framework in correlation enhanced visual concept feature space

9 years 5 months ago
A medical image retrieval framework in correlation enhanced visual concept feature space
This paper presents a medical image retrieval framework that uses visual concepts in a feature space employing statistical models built using a probabilistic multi-class support vector machine (SVM). The images are represented using concepts that comprise color and texture patches from local image regions in a multi-dimensional feature space. A major limitation of concept feature representation is that the structural relationship or spatial ordering between concepts are ignored. We present a feature representation scheme as visual concept structure descriptor (VCSD) that overcomes this challenge and captures both the concept frequency similar to a color histogram and the local spatial relationships of the concepts. A probabilistic framework makes the descriptor robust against classification and quantization errors. Evaluation of the proposed image retrieval framework on a biomedical image dataset with different imaging modalities validates its benefits.
Md. Mahmudur Rahman, Sameer Antani, George R. Thom
Added 02 Sep 2010
Updated 02 Sep 2010
Type Conference
Year 2009
Where CBMS
Authors Md. Mahmudur Rahman, Sameer Antani, George R. Thoma
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