Biomedical image representation approach using visualness and spatial information in a concept feature space for interactive region-of-interest-based retrieval

Md. Mahmudur Rahman; Sameer K. Antani; Dina Demner-Fushman; George R. Thoma

doi:10.1117/1.JMI.2.4.046502

30 December 2015 Biomedical image representation approach using visualness and spatial information in a concept feature space for interactive region-of-interest-based retrieval

Md. Mahmudur Rahman, Sameer K. Antani, Dina Demner-Fushman, George R. Thoma

Author Affiliations +

Journal of Medical Imaging, Vol. 2, Issue 4, 046502 (December 2015). https://doi.org/10.1117/1.JMI.2.4.046502

Abstract

This article presents an approach to biomedical image retrieval by mapping image regions to local concepts where images are represented in a weighted entropy-based concept feature space. The term “concept” refers to perceptually distinguishable visual patches that are identified locally in image regions and can be mapped to a glossary of imaging terms. Further, the visual significance (e.g., visualness) of concepts is measured as the Shannon entropy of pixel values in image patches and is used to refine the feature vector. Moreover, the system can assist the user in interactively selecting a region-of-interest (ROI) and searching for similar image ROIs. Further, a spatial verification step is used as a postprocessing step to improve retrieval results based on location information. The hypothesis that such approaches would improve biomedical image retrieval is validated through experiments on two different data sets, which are collected from open access biomedical literature.

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Md. Mahmudur Rahman, Sameer K. Antani, Dina Demner-Fushman, and George R. Thoma "Biomedical image representation approach using visualness and spatial information in a concept feature space for interactive region-of-interest-based retrieval," Journal of Medical Imaging 2(4), 046502 (30 December 2015). https://doi.org/10.1117/1.JMI.2.4.046502

Published: 30 December 2015

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