Advertisement

Analysis of Whole Slide Images of Equine Tendinopathy

  • M. Toutain
  • O. Lézoray
  • F. Audigié
  • V. Busoni
  • G. Rossi
  • F. Parillo
  • A. Elmoataz
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7325)

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.

Keywords

Voronoi Diagram Local Binary Pattern Singular Vector Delaunay Triangulation Spectral Cluster 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    McIlwraith, C.: Diseases of joints, tendons, ligaments and related structures. In: Stashak, T. (ed.) Adams’ Lameness in Horses, 4th edn., pp. 339–485. Lippincott Williams and Wilkins (2002)Google Scholar
  2. 2.
    Bloom, W., Fawcett, D.: A textbook of histology, 10th edn. W.B. Saunders (1975)Google Scholar
  3. 3.
    Denoix, J., Audigié, F., Hinchcliff, K., Kaneps, A., Geor, R.: Imaging of the musculoskeletal system in horses. Equine sports medicine and surgery: basic and clinical sciences of the equine athlete, 161–187 (2004)Google Scholar
  4. 4.
    Crovace, A., Lacitignola, L., Rossi, G., Francioso, E.: Histological and immunohistochemical evaluation of autologous cultured bone marrow mesenchymal stem cells and bone marrow mononucleated cells in collagenase-induced tendinitis of equine superficial digital flexor tendon. Vet. Med. Int. (2010)Google Scholar
  5. 5.
    Roullier, V., Lézoray, O., Ta, V., Elmoataz, A.: Multi-resolution graph-based analysis of histopathological whole slide images: application to mitotic cell extraction and visualization. Computerized Medical Imaging and Graphics 35, 603–615 (2011)CrossRefGoogle Scholar
  6. 6.
    Ruifrok, A., Johnston, D.: Quantification of histochemical staining by color deconvolution. Analytical and Quantitative Cytology and Histology 23, 291–299 (2001)Google Scholar
  7. 7.
    Ojala, T., Pietikäinen, M., Mäenpää, T.: Multiresolution gray-scale and rotation invariant texture classification with local binary patterns. IEEE Trans. Pattern Anal. Mach. Intell. 24, 971–987 (2002)CrossRefGoogle Scholar
  8. 8.
    Doyle, S., Agner, S., Madabhushi, A., Feldman, M., Tomaszewski, J.: Automated grading of breast cancer histopathology using spectral clustering with textural and architectural image features. In: 5th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, pp. 496–499 (2008)Google Scholar
  9. 9.
    Vanegas, M.C., Bloch, I., Inglada, J.: Searching Aligned Groups of Objects with Fuzzy Criteria. In: Hüllermeier, E., Kruse, R., Hoffmann, F. (eds.) IPMU 2010. LNCS, vol. 6178, pp. 605–613. Springer, Heidelberg (2010)CrossRefGoogle Scholar
  10. 10.
    Rüping, S., Scheffer, T. (eds.): ICML Workshop on Learning with Multiple Views (2005)Google Scholar
  11. 11.
    DeLathauwer, L., DeMoor, B., Vandewalle, J.: A multilinear singular value decomposition. SIAM J. Matrix Anal. Appl. 21, 1253–1278 (2000)MathSciNetCrossRefGoogle Scholar
  12. 12.
    Liu, X.: Learning from multi-view data: clustering algorithm and text mining application. PhD thesis, Katholieke Universiteit Leuven (2011)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • M. Toutain
    • 1
  • O. Lézoray
    • 1
  • F. Audigié
    • 2
  • V. Busoni
    • 3
  • G. Rossi
    • 4
  • F. Parillo
    • 4
  • A. Elmoataz
    • 1
  1. 1.Université de Caen Basse-Normandie, GREYC UMR CNRS 6072CaenFrance
  2. 2.CIRALE, USC INRA BPLC 957, Ecole Nationale Vétérinaire d’AlfortGoustranvilleFrance
  3. 3.Service d’imagerie, Faculté de Médecine VétérinaireUniversité de LiègeLiègeBelgium
  4. 4.Dipartimento di Scienze VeterinarieUniversita degli Studi di CamerinoMatelicaItaly

Personalised recommendations