Analysis of whole slide images of equine tendinopathy

Authors:
M. Toutain;O. Lézoray;F. Audigié;V. Busoni;G. Rossi;F. Parillo;A. Elmoataz
Affiliations:
Université de Caen Basse-Normandie, GREYC UMR CNRS 6072, Caen, France;Université de Caen Basse-Normandie, GREYC UMR CNRS 6072, Caen, France;CIRALE, USC INRA BPLC 957, Ecole Nationale Vétérinaire d'Alfort, Goustranville, France;Service d'imagerie, Faculté de Médecine Vétérinaire, Université de Liège, Liège, Belgium;Dipartimento di Scienze Veterinarie, Universita degli Studi di Camerino, Matelica, Italy;Dipartimento di Scienze Veterinarie, Universita degli Studi di Camerino, Matelica, Italy;Université de Caen Basse-Normandie, GREYC UMR CNRS 6072, Caen, France
Venue:
ICIAR'12 Proceedings of the 9th international conference on Image Analysis and Recognition - Volume Part II
Year:
2012

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Abstract

We present a method for the automatic analysis of whole slide histological images of equine tendinopathy. This computer-aided analysis is a pre-screening tool that helps veterinarians doctors to evaluate the efficacy of new treatments. A set of textural, arrangement, and alignment features are extracted to reproduce visual histological criteria, each of them representing different feature views of the initial data. To efficiently combine these different views of the data for clustering, tensor-based multi-view spectral clustering is considered and provides an unsupervised classification of the tissue zones.