Assessment of algorithms for mitosis detection in breast cancer histopathology images
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Publication date
2015-02-01
Authors
Veta, Mitko
van Diest, Paul J
Willems, S. M.
Madabhushi, Anant
Cruz-Roa, Angel
Gonzalez, Fabio
Larsen, Anders B L
Vestergaard, Jacob S.
Dahl, Anders B.
Cireşan, Dan C.
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Article
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taverne
Abstract
The proliferative activity of breast tumors, which is routinely estimated by counting of mitotic figures in hematoxylin and eosin stained histology sections, is considered to be one of the most important prognostic markers. However, mitosis counting is laborious, subjective and may suffer from low inter-observer agreement. With the wider acceptance of whole slide images in pathology labs, automatic image analysis has been proposed as a potential solution for these issues. In this paper, the results from the Assessment of Mitosis Detection Algorithms 2013 (AMIDA13) challenge are described. The challenge was based on a data set consisting of 12 training and 11 testing subjects, with more than one thousand annotated mitotic figures by multiple observers. Short descriptions and results from the evaluation of eleven methods are presented. The top performing method has an error rate that is comparable to the inter-observer agreement among pathologists. (C) 2014 Elsevier B.V. All rights reserved.
Keywords
Breast cancer, Whole slide imaging, Digital pathology, Mitosis detection, Cancer grading, COUNTING MITOSES, SECTIONS, FEASIBILITY, Taverne, Computer Graphics and Computer-Aided Design, Computer Vision and Pattern Recognition, Radiology Nuclear Medicine and imaging, Health Informatics, Radiological and Ultrasound Technology, Comparative Study, Journal Article, Research Support, Non-U.S. Gov't
Citation
Veta, M, van Diest, P J, Willems, S M, Madabhushi, A, Cruz-Roa, A, Gonzalez, F, Larsen, A B L, Vestergaard, J S, Dahl, A B, Cireşan, D C, Schmidhuber, J, Giusti, A, Gambardella, L M, Tek, F B, Walter, T, Wang, C W, Kondo, S, Matuszewski, B J, Precioso, F, Snell, V, Kittler, J, de Campos, T E, Khan, A M, Rajpoot, N M, Arkoumani, E, Lacle, M M, Viergever, M A & Pluim, JPW 2015, 'Assessment of algorithms for mitosis detection in breast cancer histopathology images', Medical Image Analysis, vol. 20, no. 1, pp. 237-248. https://doi.org/10.1016/j.media.2014.11.010