Segmentation of Cell Nuclei from Confocal Microscope Images of Thick Tissue Samples

C. Ortiz de Solorzano, A. Sarti, E. Garcia Rodriguez, A. Jones, D. Sudar, D. Pinkel, J. W. Gray, R. Malladi, S. J. Lockett

Research output: Contribution to conferencePaperpeer-review

Abstract

We present a segmentation method for cell nuclei in 3D confocal images of tissue specimens, and discuss some new approaches that could substantially improve its performance. The current method combines automatic segmentation algorithms with graphic visualization and interactive classification to achieve fast and accurate segmentation. However, the edge fidelity is low for some nuclei and other nuclei are so tightly clustered that they can not be segmented. An approach based on curvature-based flow is proposed for improving edge fidelity and an approach based on the Hough transform is proposed for segmenting clusters of nuclei.

Original languageEnglish (US)
Pages187-190
Number of pages4
StatePublished - 1998
Externally publishedYes
Event4th International Conference on Computer Science and Informatics, JCIS 1998, 1st International Workshop on High Performance, 1st International Workshop on Computer Vision, Pattern Recognition and Image Processing Volume 4 - Research Triangle Park, NC, United States
Duration: Oct 23 1998Oct 28 1998

Other

Other4th International Conference on Computer Science and Informatics, JCIS 1998, 1st International Workshop on High Performance, 1st International Workshop on Computer Vision, Pattern Recognition and Image Processing Volume 4
Country/TerritoryUnited States
CityResearch Triangle Park, NC
Period10/23/9810/28/98

ASJC Scopus subject areas

  • General Computer Science

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