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  Identifying histological elements with convolutional neural networks

Malon, H., Miller, M., Burger, H., Cosatto, E., & Graf, H. (2008). Identifying histological elements with convolutional neural networks. In R. Chbeir, Y. Badr, A. Abraham, D. Laurent, M. Köppen, F. Ferri, et al. (Eds.), CSTST '08: Proceedings of the 5th international conference on Soft computing as transdisciplinary science and technology (pp. 450-456). New York, NY, USA: ACM Press.

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 Creators:
Malon, H, Author
Miller, M, Author
Burger, HC1, Author              
Cosatto, E, Author
Graf, HP, Author
Affiliations:
1External Organizations, ou_persistent22              

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 Abstract: Histological analysis on stained biopsy samples requires recognizing many kinds of local and structural details, with some awareness of context. Machine learning algorithms such as convolutional networks can be powerful tools for such problems, but often there may not be enough training data to exploit them to their full potential. In this paper, we show how convolutional networks can be combined with appropriate image analysis to achieve high accuracies on three very different tasks in breast and gastric cancer grading, despite the challenge of limited training data. The three problems are to count mitotic figures in the breast, to recognize epithelial layers in the stomach, and to detect signet ring cells.

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 Dates: 2008-10
 Publication Status: Published in print
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: -
 Identifiers: DOI: 10.1145/1456223.1456316
BibTex Citekey: MalonMBCG2008
 Degree: -

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Title: 5th International Conference on Soft Computing as Transdisciplinary Science and Technology (CSTST '08)
Place of Event: Cergy-Pontoise, France
Start-/End Date: 2008-10-28 - 2008-10-31

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Title: CSTST '08: Proceedings of the 5th international conference on Soft computing as transdisciplinary science and technology
Source Genre: Proceedings
 Creator(s):
Chbeir, R, Editor
Badr, Y, Editor
Abraham, A, Editor
Laurent, D, Editor
Köppen, M, Editor
Ferri, F, Editor
Zadeh, LA, Editor
Ohsawa, Y, Editor
Affiliations:
-
Publ. Info: New York, NY, USA : ACM Press
Pages: - Volume / Issue: - Sequence Number: - Start / End Page: 450 - 456 Identifier: ISBN: 978-1-60558-046-3