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  • Bilgisayar Mühendisliği Bölümü / Department of Computer Engineering
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  •   DSpace@Işık
  • 1- Fakülteler | Faculties
  • Mühendislik Fakültesi / Faculty of Engineering
  • Bilgisayar Mühendisliği Bölümü / Department of Computer Engineering
  • MF - Makale Koleksiyonu | Bilgisayar Mühendisliği Bölümü / Department of Computer Engineering
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Assessment of algorithms for mitosis detection in breast cancer histopathology images

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Date

2015-02

Author

Veta, Mitko
Van Diest, Paul J.
Willems, Stefan Martin
Wang, Haibo
Madabhushi, Anant
Cruz-Roa, Angel
Gonzalez, Fabio
Larsen, Anders Boesen Lindbo
Vestergaard, Jacob Schack Chack
Dahl, Anders Bjorholm
Cireşan, Dan Claudiu
Schmidhuber, Jürgen U.
Giusti, Alessandro
Gambardella, Luca M.
Tek, Faik Boray
Walter, Thomas C.
Wang, Chingwei
Kondo, Satoshi
Matuszewski, Bogdan J.
Precioso, Frédéric
Snell, Violet
Kittler, Josef
De Campos, Teofilo E.
Khan, Adnan M.
Rajpoot, Nasir Mahmood
Arkoumani, Evdokia
Lacle, Miangela M.
Viergever, Max A.
Pluim, Josien P W

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Citation

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

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.

Source

Medical Image Analysis

Volume

20

Issue

1

URI

https://hdl.handle.net/11729/577
http://dx.doi.org/10.1016/j.media.2014.11.010

Collections

  • MF - Makale Koleksiyonu | Bilgisayar Mühendisliği Bölümü / Department of Computer Engineering [67]
  • PubMed İndeksli Yayın Koleksiyonu [102]
  • Scopus İndeksli Makale Koleksiyonu [915]
  • WoS İndeksli Makale Koleksiyonu [929]



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