Segmentation of clustered nuclei based on concave curve expansion
2013 (English)In: Journal of Microscopy, ISSN 0022-2720, E-ISSN 1365-2818, Vol. 251, no 1, 57-67 p.Article in journal (Refereed) PublishedText
Segmentation of nuclei from images of tissue sections is important for many biological and biomedical studies. Many existing image segmentation algorithms may lead to oversegmentation or undersegmentation for clustered nuclei images. In this paper, we proposed a new image segmentation algorithm based on concave curve expansion to correctly and accurately extract markers from the original images. Marker-controlled watershed is then used to segment the clustered nuclei. The algorithm was tested on both synthetic and real images and better results are achieved compared with some other state-of-the-art methods.
Place, publisher, year, edition, pages
Wiley-Blackwell, 2013. Vol. 251, no 1, 57-67 p.
Clustered nuclei, concave curve expansion, curvature information, image segmentation, watershed segmentation
Medical Image Processing
IdentifiersURN: urn:nbn:se:liu:diva-125011DOI: 10.1111/jmi.12043ISI: 000320170900008PubMedID: 23692597OAI: oai:DiVA.org:liu-125011DiVA: diva2:902791