Resumen

AREVALO, JOHN; CRUZ-ROA, ANGEL  y  GONZALEZ O., FABIO A.. HISTOPATHOLOGY IMAGE REPRESENTATION FOR AUTOMATIC ANALYSIS: A STATE-OF-THE-ART REVIEW. rev.fac.med [online]. 2014, vol.22, n.2, pp.79-91. ISSN 0121-5256.

This paper presents a review of the state-of-the-art in histopathology image representation used in automatic image analysis tasks. Automatic analysis of histopathology images is important for building computer-assisted diagnosis tools, automatic image enhancing systems and virtual microscopy systems, among other applications. Histopathology images have a rich mix of visual patterns with particularities that make them difficult to analyze. The paper discusses these particularities, the acquisition process and the challenges found when doing automatic analysis. Second an overview of recent works and methods addressed to deal with visual content representation in different automatic image analysis tasks is presented. Third an overview of applications of image representation methods in several medical domains and tasks is presented. Finally, the paper concludes with current trends of automatic analysis of histopathology images like digital pathology.

Palabras clave : Histopathology; image analysis; computer-assisted; pattern recognition system; informatics computing; medical; state-of-the-art review.

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