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Analytical Cellular Pathology
Volume 23, Issue 2, Pages 75-88
http://dx.doi.org/10.1155/2001/683747

Prognostic Classification of Early Ovarian Cancer Based on very Low Dimensionality Adaptive Texture Feature Vectors from Cell Nuclei from Monolayers and Histological Sections

Birgitte Nielsen,1,2 Fritz Albregtsen,1 Wanja Kildal,2 and Håvard E. Danielsen2,3

1Department of Informatics, University of Oslo, P.O.Box 1080 Blindern, N‐0316 Oslo, Norway
2Division of Digital Pathology, The Norwegian Radium Hospital, Montebello, N‐0310 Oslo, Norway
3Division of Genomic Medicine, The University of Sheffield, Sheffield, S102TN, England

Accepted 13 November 2001

Copyright © 2001 Hindawi Publishing Corporation. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

How to Cite this Article

Birgitte Nielsen, Fritz Albregtsen, Wanja Kildal, and Håvard E. Danielsen, “Prognostic Classification of Early Ovarian Cancer Based on very Low Dimensionality Adaptive Texture Feature Vectors from Cell Nuclei from Monolayers and Histological Sections,” Analytical Cellular Pathology, vol. 23, no. 2, pp. 75-88, 2001. https://doi.org/10.1155/2001/683747.