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Curve closing by gradient weighted distance transformation applied in automated cervical cancer screening
Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
2009 (English)In: Proceedings SSBA 2009: Symposium on Image Analysis / [ed] Josef Bigun and Antanas Verikas, 2009, 25-28 p.Conference paper, Published paper (Other academic)
Abstract [en]

In this paper, a nuclei segmentation algorithm that uses a gradient weighted distance transform for curve closing is described. Edge detection methods often return broken edges that need to be closed to achieve proper segmentation. Based n a Canny edge result, this method generates a distance map that is dependent on local gradient directions and magnitudes making it possible to promote propagation along edges rather than away from them. Through this procedure, which is a kind of adaptive morphology, it is possible to achieve curve closing even along very weak edges. The method is developed within a larger project  aimed at creating a cervical cancer screening system mainly intended to allow automated screening in developing countries.

Place, publisher, year, edition, pages
2009. 25-28 p.
Keyword [en]
Curve closing, gradient weighted, cervical cancer screening
National Category
Computer Vision and Robotics (Autonomous Systems)
Research subject
Computerized Image Analysis
Identifiers
URN: urn:nbn:se:uu:diva-111507ISBN: 978-91-633-3924-0 (print)OAI: oai:DiVA.org:uu-111507DiVA: diva2:281453
Conference
SSBA
Available from: 2009-12-16 Created: 2009-12-16 Last updated: 2009-12-17Bibliographically approved

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Malm, Patrik

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