Segmentation of clustered nuclei based on curvature weighting
2012 (English)In: IVCNZ '12, Proceedings of the 27th Conference on Image and Vision Computing New Zealand, ACM Digital Library, 2012, 49-54 p.Conference paper (Other academic)Text
Cluster of nuclei are frequently observed in thick tissue section images. It is very important to segment overlapping nuclei in many biomedical applications. Many existing methods tend to produce under segmented results when there is a high overlap rate. In this paper, we present a curvature weighting based algorithm which weights each pixel using the curvature information of its nearby boundaries to extract markers, each of which represents an object, from input images. Then we use marker-controlled watershed to obtain the final segmentation. Test results using both synthetic and real cell images are presented in the paper.
Place, publisher, year, edition, pages
ACM Digital Library, 2012. 49-54 p.
Computer Vision and Robotics (Autonomous Systems)
IdentifiersURN: urn:nbn:se:liu:diva-125051DOI: 10.1145/2425836.2425848ISBN: 9781450314732OAI: oai:DiVA.org:liu-125051DiVA: diva2:902713
27th Image and Vision Computing New Zealand IVCNZ'12, Dunedin, New Zealand, November 26-28, 2012