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A geometric model for 3-D confocal image analysis

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

The authors use partial-differential-equation-based filtering as a preprocessing and post processing strategy for computer-aided cytology. They wish to accurately extract and classify the shapes of nuclei from confocal microscopy images, which is a prerequisite to an accurate quantitative intranuclear (genotypic and phenotypic) and internuclear (tissue structure) analysis of tissue and cultured specimens. First, the authors study the use of a geometry-driven edge-preserving image smoothing mechanism before nuclear segmentation. They show how this filter outperforms other widely-used filters in that it provides higher edge fidelity. Then they apply the same filter with a different initial condition, to smooth nuclear surfaces and obtain sub-pixel accuracy. Finally the authors use another instance of the geometrical filter to correct for misinterpretations of the nuclear surface by the segmentation algorithm. Their prefiltering and post filtering nicely complements their initial segmentation strategy, in that it provides substantial and measurable improvement in the definition of the nuclear surfaces.

Published in:

IEEE Transactions on Biomedical Engineering  (Volume:47 ,  Issue: 12 )