Article

A multiple Kernel learning algorithm for cell nucleus classification of renal cell carcinoma

Authors:

Peter Schüffler,

Umberto Castellani,

Vittorio MurinoAuthors Info & Claims

ICIAP'11: Proceedings of the 16th international conference on Image analysis and processing: Part I

Pages 413 - 422

Published: 14 September 2011 Publication History

Abstract

We consider a Multiple Kernel Learning (MKL) framework for nuclei classification in tissue microarray images of renal cell carcinoma. Several features are extracted from the automatically segmented nuclei and MKL is applied for classification. We compare our results with an incremental version of MKL, support vector machines with single kernel (SVM) and voting. We demonstrate that MKL inherently combines information from different input spaces and creates statistically significantly more accurate classifiers than SVMs and voting for renal cell carcinoma detection.

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Cited By

Bicego MUlaş ASchüffler PCastellani UMurino VMartins AAguiar PFigueiredo M(2011)Renal cancer cell classification using generative embeddings and information theoretic kernelsProceedings of the 6th IAPR international conference on Pattern recognition in bioinformatics10.5555/2075619.2075628(75-86)Online publication date: 2-Nov-2011
https://dl.acm.org/doi/10.5555/2075619.2075628

A multiple Kernel learning algorithm for cell nucleus classification of renal cell carcinoma
1. Computing methodologies
  1. Machine learning

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Information

Published In

cover image Guide Proceedings

ICIAP'11: Proceedings of the 16th international conference on Image analysis and processing: Part I

September 2011

709 pages

ISBN:9783642240843

Editors:
Giuseppe Maino
Università di Bologna, Facoltà di Conservazione dei Beni Culturali, Ravenna, Italy
,
Gian Luca Foresti
Università di Udine, Dipartimento di Matematica e Informatica, Udine, Italy

Publisher

Springer-Verlag

Berlin, Heidelberg

Publication History

Published: 14 September 2011

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Cited By

Bicego MUlaş ASchüffler PCastellani UMurino VMartins AAguiar PFigueiredo M(2011)Renal cancer cell classification using generative embeddings and information theoretic kernelsProceedings of the 6th IAPR international conference on Pattern recognition in bioinformatics10.5555/2075619.2075628(75-86)Online publication date: 2-Nov-2011
https://dl.acm.org/doi/10.5555/2075619.2075628

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