Automatic Breast Cancer Diagnosis Based on K-Means Clustering and Adaptive Thresholding Hybrid Segmentation-Reference-Cited by-同舟云学术

Automatic Breast Cancer Diagnosis Based on K-Means Clustering and Adaptive Thresholding Hybrid Segmentation

Published:2011 Issue: Volume: Page:295-302
ISSN:1867-5662
Container-title:Advances in Intelligent and Soft Computing
language:
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Author:

Filipczuk Paweł,Kowal Marek,Obuchowicz Andrzej

Publisher

Springer Berlin Heidelberg

Link

http://link.springer.com/content/pdf/10.1007/978-3-642-23154-4_33.pdf

Reference25 articles.

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3. Clocksin, W.F.: Automatic segmentation of overlapping nuclei with high background variation using robust estimation and flexible contour models. In: Proc 12th Int. Conf. Image Analysis and Processing, ICIAPŠ 2003, pp. 682–687 (2003)

4. Cloppet, F., Boucher, A.: Segmentation of overlapping/aggregating nuclei cells in biological images. In: Proc. 19th Int. Conf. on Pattern Recognition, ICPR 2003, pp. 1–4 (2008)

5. Filipczuk, P., Kowal, M., Marciniak, A.: Feature selection for breast cancer malignancy classification problem. J. Medical Informatics & Technologies 15, 193–199 (2010)

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