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Segmentation of cell nuclei in tissue by combining seeded watersheds with gradient information
Uppsala University, Interfaculty Units, Centre for Image Analysis. Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
Uppsala University, Interfaculty Units, Centre for Image Analysis. Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
2003 (English)In: Proceedings of SCIA-03: Scandinavian Conference on Image Analysis, 2003, 408-414 p.Conference paper, Published paper (Refereed)
Abstract [en]

This paper deals with the segmentation of cell nuclei in tissue. We present a region-based segmentation method where seeds representing object- and background-pixels are created by morphological filtering. The seeds are then used as a starting point for watershed segmentation of the gradient magnitude of the original image. Over-segmented objects are thereafter merged based on the gradient magnitude between the adjacent objects. The method was tested on a total of 726 cell nuclei in 7 images, and 95% correct segmentation was achieved.

Place, publisher, year, edition, pages
2003. 408-414 p.
National Category
Computer Vision and Robotics (Autonomous Systems)
Identifiers
URN: urn:nbn:se:uu:diva-46181OAI: oai:DiVA.org:uu-46181DiVA: diva2:74089
Available from: 2005-08-26 Created: 2005-08-26 Last updated: 2017-02-08

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http://link.springer.de/link/service/series/0558/papers/2749/27490408.pdf

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Wählby, CarolinaBengtsson, Ewert

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