DocumentCode
1140573
Title
Automatic Segmentation and Disentangling of Chromosomes in Q-Band Prometaphase Images
Author
Grisan, Enrico ; Poletti, Enea ; Ruggeri, Alfredo
Author_Institution
Dept. of Inf. Eng., Univ. of Padova, Padova, Italy
Volume
13
Issue
4
fYear
2009
fDate
7/1/2009 12:00:00 AM
Firstpage
575
Lastpage
581
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.
Keywords
biomedical optical imaging; cellular biophysics; fluorescence; genetics; image classification; image segmentation; medical image processing; recursive estimation; Q-band prometaphase images; automatic segmentation procedure; chromosome disentanglement; cytogenetics; genetics defects; geometric evidence; hyperfluorescent regions; hypofluorescent regions; image classification; image information; karyotype analysis; microscope-camera setup; recursive estimation; space-variant thresholding scheme; Adjacent chromosomes; chromosome analysis; image segmentation; karyotyping; overlapping chromosomes; Algorithms; Chromosomes, Human; Cluster Analysis; Humans; Image Processing, Computer-Assisted; Karyotyping; Prometaphase;
fLanguage
English
Journal_Title
Information Technology in Biomedicine, IEEE Transactions on
Publisher
ieee
ISSN
1089-7771
Type
jour
DOI
10.1109/TITB.2009.2014464
Filename
4773198
Link To Document