Karyotype analysis is a widespread procedure in cytogenetics to assess the possible presence of genetics defects. The procedure is lengthy and repetitive, so that an automatic analysis would greatly help the cytogeneticist routine work. Still, automatic segmentation and full disentangling of chromosomes are open issues. The first step in every automatic procedure, is the segmentation of the chromosomes, as either single entities or in clusters, in the image. The better the segmentation step, the easier the subsequent disentanglement. We propose for the segmentation step a region based level set algorithm that is able to address the variability in the image background due to the presence of hyper- or hypo-fluorescent regions in the image. We compare its performance with other algorithms proposed in the literature for the segmentation of chromosomes, over a set of 11 manually annotated images. We show the superiority of the proposed approach both in terms of pixel sensitivity, and in terms of number of separate clusters with respect to the manual segmentation. The images used in the paper are available for public download.

An Improved Segmentation of Chromosomes in Q-Band Prometaphase Images Using a Region Based Level Set

GRISAN, ENRICO;POLETTI, ENEA;RUGGERI, ALFREDO
2009

Abstract

Karyotype analysis is a widespread procedure in cytogenetics to assess the possible presence of genetics defects. The procedure is lengthy and repetitive, so that an automatic analysis would greatly help the cytogeneticist routine work. Still, automatic segmentation and full disentangling of chromosomes are open issues. The first step in every automatic procedure, is the segmentation of the chromosomes, as either single entities or in clusters, in the image. The better the segmentation step, the easier the subsequent disentanglement. We propose for the segmentation step a region based level set algorithm that is able to address the variability in the image background due to the presence of hyper- or hypo-fluorescent regions in the image. We compare its performance with other algorithms proposed in the literature for the segmentation of chromosomes, over a set of 11 manually annotated images. We show the superiority of the proposed approach both in terms of pixel sensitivity, and in terms of number of separate clusters with respect to the manual segmentation. The images used in the paper are available for public download.
IFMBE Proceedings of the World Congress 2009 in Medical Physics and Biomedical Engineering
9783642038822
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11577/2440631
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