DocumentCode :
1419154
Title :
A Novel Metric for Bone Marrow Cells Chromosome Pairing
Author :
Khmelinskii, Artem ; Ventura, Rodrigo ; Sanches, João
Author_Institution :
Inst. for Syst. & Robot., Inst. Super. Tecnico, Lisbon, Portugal
Volume :
57
Issue :
6
fYear :
2010
fDate :
6/1/2010 12:00:00 AM
Firstpage :
1420
Lastpage :
1429
Abstract :
Karyotyping is a set of procedures, in the scope of the cytogenetics, that produces a visual representation of the 46 chromosomes observed during the metaphase step of the cellular division, called mitosis, paired and arranged in decreasing order of size. Automatic pairing of bone marrow cells is a difficult task because these chromosomes appear distorted, overlapped, and their images are usually blurred with undefined edges and low level of detail. In this paper, a new metric is proposed to compare this type of chromosome images toward the design of an automatic pairing algorithm for leukemia diagnostic purposes. Besides the features used in the traditional karyotyping procedures, a new feature, based on mutual information , is proposed to increase the discriminate power of the G-banding pattern dissimilarity between chromosomes and improve the performance of the classifier. The pairing algorithm is formulated as a combinatorial optimization problem where the distances between homologous chromosomes are minimized and the distances between nonhomologous ones are maximized. The optimization task is solved by using an integer programming approach. A new bone marrow chromosome dataset-Lisbon-K1 (LK1) chromosome dataset with 9200 chromosomes---was build for this study. These chromosomes have much lower quality than the classic Copenhagen, Edinburgh, and Philadelphia datasets, and its classification and pairing is therefore more difficult. Experiments using real images from the LK1 and Grisan et al. datasets based on a leave-one-out cross-validation strategy are performed to test and validate the pairing algorithm.
Keywords :
bone; cellular biophysics; diseases; genetics; medical image processing; molecular biophysics; optimisation; G-banding pattern dissimilarity; Lisbon-K1 chromosome dataset; automatic pairing algorithm; bone marrow cell chromosome pairing; bone marrow chromosome dataset; chromosome images; combinatorial optimization problem; cytogenetics; homologous chromosomes; integer programming approach; karyotyping procedure; leave-one-out cross-validation strategy; leukemia diagnostic purposes; mutual information; Bone marrow cells; chromosome pairing; classification; image processing; integer programming; leukemia; mutual information (MI); optical microscopy; optimization; Algorithms; Artificial Intelligence; Bone Marrow Cells; Cells, Cultured; Chromosome Pairing; Chromosomes; Humans; Image Enhancement; Image Interpretation, Computer-Assisted; Karyotyping; Microscopy; Pattern Recognition, Automated; Reproducibility of Results; Sensitivity and Specificity;
fLanguage :
English
Journal_Title :
Biomedical Engineering, IEEE Transactions on
Publisher :
ieee
ISSN :
0018-9294
Type :
jour
DOI :
10.1109/TBME.2010.2040279
Filename :
5415619
Link To Document :
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