Morphological multiscale shape analysis of light micrographs

Volker H. Metzler; Thomas Martin Lehmann; Til Aach

doi:10.1117/12.379396

3 March 2000 Morphological multiscale shape analysis of light micrographs

Volker H. Metzler, Thomas Martin Lehmann, Til Aach

Proceedings Volume 3961, Nonlinear Image Processing XI; (2000) https://doi.org/10.1117/12.379396
Event: Electronic Imaging, 2000, San Jose, CA, United States

Abstract

Shape analysis of light-micrographs of cell populations is important for cytotoxicity evolution. This paper presents a morphological method for quantitative analysis of shape deformations of cells in contact to a biomaterial. After illumination normalization, a morphological multiscale segmentation yields separated cells. Shape deformation, and hence, toxicity of the substance under scrutiny, is quantified by means of compactness distribution and pattern spectrum of the population. Since the logarithmic image model is applicable to transmitted light, illumination normalization is achieved by removing the illumination component from the log- image by a tophat transform utilizing a large reconstruction filter. Subsequent thresholding and noise filtering yields connected binary cells, which are segmented by a marker-based, multiscale approach. For this, size-specific marker scales are generated removing noise and false markers. Each cell is now represented by an isolated marker. Converse integration of marker scales is performed by successive reconstruction of the original cell shapes, preventing merging of markers. Our method yields reasonable cell segmentations that go along with cell morphology even for differently sized and very distinct shapes. The obtained quantitative data is significantly correlated to the toxicity of the substance to be evaluated. Currently, the method is used for extensive biocompatibility tests.

Citation Download Citation

Volker H. Metzler, Thomas Martin Lehmann, and Til Aach "Morphological multiscale shape analysis of light micrographs", Proc. SPIE 3961, Nonlinear Image Processing XI, (3 March 2000); https://doi.org/10.1117/12.379396

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