Mitosis Detection in Breast Cancer Using Superpixels and Ensemble Classifiers

• Autores: César A. Ortiz Toro, Consuelo Gonzalo Martín, Angel Mario García Pedrero, Alejandro Rodríguez González, Ernestina Menasalvas
• Localización: 11th International Conference on Practical Applications of Computational Biology & Bioinformatics / Florentino Fernández Riverola (ed. lit.), 2017, ISBN 978-3-319-60815-0, págs. 137-145
• Idioma: inglés
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• Resumen

  • Determining the severity and potential aggressiveness of breast cancer is an important step in the determination of the treatment options for a patient. Mitosis activity is one of the main components in breast cancer severity grading. Currently, mitosis counting is a laborious, prone to processing errors, done manually by a pathologist.

    This paper presents a novel approach for automatic mitosis detection, where promising candidates are selected from a superpixel segmentation of the image and classified using an ensemble classifier created from a selection from a pool of different color spaces, different features vector