Automatic segmentation and disentangling of chromosomes in Q-band prometaphase images

Authors:
Enrico Grisan;Enea Poletti;Alfredo Ruggeri
Affiliations:
Department of Information Engineering, University of Padova, Padova, Italy;Department of Information Engineering, University of Padova, Padova, Italy;Department of Information Engineering, University of Padova, Padova, Italy
Venue:
IEEE Transactions on Information Technology in Biomedicine - Special section on biomedical informatics
Year:
2009

Citing 8
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Geometric Separation of Partially Overlapping Nonrigid Objects Applied to Automatic Chromosome Classification

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A classification-driven partially occluded object segmentation(CPOOS) method with application to chromosome analysis

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Toward a completely automatic neural-network-based human chromosomeanalysis

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A modular framework for the automatic classification of chromosomes in Q-band images

Computer Methods and Programs in Biomedicine
A review of thresholding strategies applied to human chromosome segmentation

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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. We propose an automatic procedure to obtain the separated chromosomes, which are then ready for a subsequent classification step. The segmentation is carried out by means of a space-variant thresholding scheme, which proved to be successful even in presence of hyper- or hypofluorescent regions in the image. Then, the tree of choices to resolve touching and overlapping chromosomes is recursively explored, choosing the best combination of cuts and overlaps based on geometric evidence and image information. We show the effectiveness of the proposed method on routine data acquired with different microscope-camera setup at different laboratories: from 162 images of 117 cells totaling 6683 chromosomes, 94% of the chromosomes were correctly segmented, solving 90% of the overlaps and 90% of the touchings. In order to provide the scientific community with a public dataset, the data used in this paper are available for public download.