SVM-based framework for the robust extraction of objects from histopathological images using color, texture, scale and geometry

Antoine Veillard, Stephane Bressan, Daniel Racoceanu

Producción científica: Capítulo del libro/informe/acta de congresoContribución a la conferenciarevisión exhaustiva

7 Citas (Scopus)

Resumen

The extraction of nuclei from Haematoxylin and Eosin (H&E) stained biopsies present a particularly steep challenge in part due to the irregularity of the high-grade (most malignant) tumors. To your best knowledge, although some existing solutions perform adequately with relatively predictable low-grade cancers, solutions for the problematic high-grade cancers have yet to be proposed. In this paper, we propose a method for the extraction of cell nuclei from H&E stained biopsies robust enough to deal with the full range of histological grades observed in daily clinical practice. The robustness is achieved by combining a wide range of information including color, texture, scale and geometry in a multi-stage, Support Vector Machine (SVM) based framework to replace the original image with a new, probabilistic image modality with stable characteristics. The actual extraction of the nuclei is performed from the new image using Mark Point Processes (MPP), a state-of-the-art stochastic method. An empirical evaluation on clinical data provided and annotated by pathologists shows that our method greatly improves detection and extraction results, and provides a reliable solution with high grade cancers. Moreover, our method based on machine learning can easily adapt to specific clinical conditions. In many respects, our method contributes to bridging the gap between the computer vision technologies and their actual clinical use for breast cancer grading.

Idioma originalInglés
Título de la publicación alojadaProceedings - 2012 11th International Conference on Machine Learning and Applications, ICMLA 2012
Páginas70-75
Número de páginas6
DOI
EstadoPublicada - 2012
Publicado de forma externa
Evento11th IEEE International Conference on Machine Learning and Applications, ICMLA 2012 - Boca Raton, FL, Estados Unidos
Duración: 12 dic. 201215 dic. 2012

Serie de la publicación

NombreProceedings - 2012 11th International Conference on Machine Learning and Applications, ICMLA 2012
Volumen1

Conferencia

Conferencia11th IEEE International Conference on Machine Learning and Applications, ICMLA 2012
País/TerritorioEstados Unidos
CiudadBoca Raton, FL
Período12/12/1215/12/12

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