1st Congress of the International Academy of Digital Pathology Quebec City, Canada, August 3–5, 2011. Part IIView this Special Issue
Christopher Malon, Elena Brachtel, Eric Cosatto, Hans Peter Graf, Atsushi Kurata, Masahiko Kuroda, John S. Meyer, Akira Saito, Shulin Wu, Yukako Yagi, "Mitotic Figure Recognition: Agreement among Pathologists and Computerized Detector", Analytical Cellular Pathology, vol. 35, Article ID 385271, 4 pages, 2012. https://doi.org/10.3233/ACP-2011-0029
Mitotic Figure Recognition: Agreement among Pathologists and Computerized Detector
Despite the prognostic importance of mitotic count as one of the components of the Bloom – Richardson grade , several studies ([2, 9, 10]) have found that pathologists’ agreement on the mitotic grade is fairly modest. Collecting a set of more than 4,200 candidate mitotic figures, we evaluate pathologists' agreement on individual figures, and train a computerized system for mitosis detection, comparing its performance to the classifications of three pathologists. The system’s and the pathologists’ classifications are based on evaluation of digital micrographs of hematoxylin and eosin stained breast tissue. On figures where the majority of pathologists agree on a classification, we compare the performance of the trained system to that of the individual pathologists. We find that the level of agreement of the pathologists ranges from slight to moderate, with strong biases, and that the system performs competitively in rating the ground truth set. This study is a step towards automatic mitosis count to accelerate a pathologist's work and improve reproducibility.
Copyright © 2012 Hindawi Publishing Corporation and the authors. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.