Local Concept-Based Medical Image Retrieval with Correlation-Enhanced Similarity Matching Based on Global Analysis

Abstract

A correlation-enhanced similarity matching framework for medical image retrieval is presented in a local concept-based feature space. In this framework, images are presented by vectors of concepts that comprise of local color and texture patches of image regions in a multi-dimensional feature space. To generate the concept vocabularies and represent the images, statistical models are built using a probabilistic multi-class support vector machine (SVM). For the similarity search, the concept correlations in the collection as a whole are analyzed as a global thesaurus-like structure and incorporated in a similarity matching function. The proposed scheme overcomes some limitations of the "bag of concepts" model, such as the assumption of feature independence. A systematic evaluation of image retrieval on a biomedical image collection of different modalities demonstrates the advantages of the proposed retrieval framework in terms of precision-recall.

Cite

Text

Rahman et al. "Local Concept-Based Medical Image Retrieval with Correlation-Enhanced Similarity Matching Based on Global Analysis." IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2010. doi:10.1109/CVPRW.2010.5543452

Markdown

[Rahman et al. "Local Concept-Based Medical Image Retrieval with Correlation-Enhanced Similarity Matching Based on Global Analysis." IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2010.](https://mlanthology.org/cvprw/2010/rahman2010cvprw-local/) doi:10.1109/CVPRW.2010.5543452

BibTeX

@inproceedings{rahman2010cvprw-local,
  title     = {{Local Concept-Based Medical Image Retrieval with Correlation-Enhanced Similarity Matching Based on Global Analysis}},
  author    = {Rahman, Md. Mahmudur and Antani, Sameer K. and Thoma, George R.},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops},
  year      = {2010},
  pages     = {87-94},
  doi       = {10.1109/CVPRW.2010.5543452},
  url       = {https://mlanthology.org/cvprw/2010/rahman2010cvprw-local/}
}