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A New Family of Distance Functions for Perceptual Similarity Retrieval of Medical Images

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Abstract

A long-standing challenge of content-based image retrieval (CBIR) systems is the definition of a suitable distance function to measure the similarity between images in an application context which complies with the human perception of similarity. In this paper, we present a new family of distance functions, called attribute concurrence influence distances (AID), which serve to retrieve images by similarity. These distances address an important aspect of the psychophysical notion of similarity in comparisons of images: the effect of concurrent variations in the values of different image attributes. The AID functions allow for comparisons of feature vectors by choosing one of two parameterized expressions: one targeting weak attribute concurrence influence and the other for strong concurrence influence. This paper presents the mathematical definition and implementation of the AID family for a two-dimensional feature space and its extension to any dimension. The composition of the AID family with L p distance family is considered to propose a procedure to determine the best distance for a specific application. Experimental results involving several sets of medical images demonstrate that, taking as reference the perception of the specialist in the field (radiologist), the AID functions perform better than the general distance functions commonly used in CBIR.

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Acknowledgments

The authors are grateful to the radiologists from HC-FMRP, Ribeirão Preto, Brazil who participated in the experimental studies and the researchers from the CCIFM-FMRP who provided the images for the experiments. This research has been supported, in part, by the Brazilian National Research Council (CNPq) under grants 52.1685/98-6, 860.068/00-7 and 35.0852/94-4 and by the Sao Paulo State Research Foundation (FAPESP) under grant 04/02215-5.

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Authors and Affiliations

  1. Department of Physics and Mathematics, University of São Paulo, Ribeirão Preto, Brazil

    Joaquim Cezar Felipe

  2. Department of Computer Science, University of São Paulo, São Carlos, Brazil

    Caetano Traina Jr & Agma Juci Machado Traina

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  1. Joaquim Cezar Felipe
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  2. Caetano Traina Jr
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  3. Agma Juci Machado Traina
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Correspondence to Joaquim Cezar Felipe.

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Felipe, J.C., Traina, C. & Traina, A.J.M. A New Family of Distance Functions for Perceptual Similarity Retrieval of Medical Images. J Digit Imaging 22, 183–201 (2009). https://doi.org/10.1007/s10278-007-9084-x

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  • DOI: https://doi.org/10.1007/s10278-007-9084-x

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