Assessment of algorithms for mitosis detection in breast cancer histopathology images

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Tarih

2015-02

Dergi Başlığı

Dergi ISSN

Cilt Başlığı

Yayıncı

Elsevier Science BV

Erişim Hakkı

info:eu-repo/semantics/closedAccess

Araştırma projeleri

Organizasyon Birimleri

Dergi sayısı

Özet

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.

Açıklama

Anahtar Kelimeler

Breast cancer, Whole slide imaging, Digital pathology, Mitosis detection, Cancer grading, Counting Mitoses, Sections, Feasibility

Kaynak

Medical Image Analysis

WoS Q Değeri

Q1
Q1

Scopus Q Değeri

Q1

Cilt

20

Sayı

1

Künye

Veta, M., van Diest, P. J., Willems, S. M., Wang, H., Madabhushi, A., Cruz-Roa, A., . . . Pluim, J. P. W. (2015). Assessment of algorithms for mitosis detection in breast cancer histopathology images. Medical Image Analysis, 20(1), 237-248. doi:10.1016/j.media.2014.11.010