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A unified geometric model for 3D confocal image analysis in cytology

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4 Author(s)
Sarti, A. ; Lawrence Berkeley Nat. Lab., California Univ., Berkeley, CA, USA ; Ortiz, C. ; Lockett, S. ; Malladi, R.

In this paper, we use partial differential equation based analysis as a methodology for computer-aided cytology. We wish to accurately extract and classify the shapes of nuclei from noisy confocal microscopy images. This is a prerequisite to an accurate quantitative intranuclear (genotypic and phenotypic) and internuclear (tissue structure) analysis of cancerous and pre-cancerous specimens. We study the use of a geometric-driven scheme for improving the results obtained by a nuclear segmentation method, based on automatic segmentation, followed by object reconstruction and interactive classification. We build a chain of methods that includes an edge-preserving image smoothing mechanism, an automatic (albeit non-regularized) segmentation method, a geometry-driven scheme to regularize the shapes and improve edge fidelity, and an interactive method to split shape clusters and reclassify them

Published in:

Computer Graphics, Image Processing, and Vision, 1998. Proceedings. SIBGRAPI '98. International Symposium on

Date of Conference:

20-23 Oct 1998