Data Labeling Impact on Deep Learning Models in Digital Pathology: a Breast Cancer Case Study-Reference-Cited by-同舟云学术

Data Labeling Impact on Deep Learning Models in Digital Pathology: a Breast Cancer Case Study

Published:2022 Issue: Volume: Page:117-129
ISSN:2730-6437
Container-title:Studies in Autonomic, Data-driven and Industrial Computing
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Author:

Benaggoune K.,Al Masry Z.,Devalland C.,Valmary-degano S.,Zerhouni N.,Mouss L. H.

Publisher

Springer Nature Singapore

Link

https://link.springer.com/content/pdf/10.1007/978-981-16-7771-7_10

Reference27 articles.

1. Abubakar M, Howat WJ, Daley F, Zabaglo L, McDuffus LA, Blows F, Coulson P, Raza Ali H, Benitez J, Milne R et al (2016) High-throughput automated scoring of KI67 in breast cancer tissue microarrays from the breast cancer association consortium. J Pathol Clin Res 2(3):138–153

2. Bankhead P, Loughrey MB, Fernández JA, Dombrowski Y, McArt DG, Dunne PD, McQuaid S, Gray RT, Murray LJ, Coleman HG et al (2017) Qupath: open source software for digital pathology image analysis. Sci Rep 7(1):1–7

3. Bayramoglu N, Kannala J, Heikkilä J (2016) Deep learning for magnification independent breast cancer histopathology image classification. In: 2016 23rd International conference on pattern recognition (ICPR). IEEE, pp 2440–2445

4. Bengio Y, Courville A, Vincent P (2013) Representation learning: a review and new perspectives. IEEE Trans Pattern Anal Mach Intell 35(8):1798–1828

5. Buslaev A, Parinov A, Khvedchenya E, Iglovikov VI, Kalinin AA (2018)Albumentations: fast and flexible image augmentations. arXiv preprint arXiv:1809.06839

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