Title

Homologue Matching Using the Choquet Integral

Abstract

Automated Giemsa-banded chromosome image research has been largely restricted to classification schemes associated with isolated chromosomes within metaphase spreads. In normal human metaphase spreads, there are 46 chromosomes occurring in homologous pairs for the autosomal classes, 1-22, and X chromosome for females. For optimizing automated human chromosome image analysis, many existing techniques assume cell normalcy. With many genetic abnormalities directly linked to structural and numerical aberrations of chromosomes within the metaphase spread, the two chromosome per class assumption may not be appropriate for anomaly analysis. At the University of Missouri, a data-driven homologue matching approach has been developed to identify all normal chromosomes within a metaphase spread from a selected class. Chromosome assignment to a specific class is initially based on neural networks, followed by banding pattern and centromeric index criteria checking, and concluding with homologue matching utilizing a density profile-based classifier, a shape profile-based classifier, and a binary band profile-based classifier. Based on preliminary results for the profile-based classifiers assigning chromosome 17, the Choquet integral is presented as an extension to the homologue matching approach. Experimental results are presented comparing the extended homologue matching approach to the transportation algorithm for identifying chromosome 21 within normal metaphase spreads.

Meeting Name

35th Annual Rocky Mountain Bioengineering Symposium & 35th International ISA Biomedical Sciences Instrumentation Symposium (1998: Apr. 17-19, Copper Mountain, CO)

Department(s)

Electrical and Computer Engineering

Keywords and Phrases

Algorithms; Fuzzy Sets; Genetic Engineering; Image Analysis; Integral Equations; Neural Networks; Automated Karyotyping; Choquet Integrals; Homologue Matching; Medical Imaging; Artificial Neural Network; Chromosome 17; Chromosome 21; Chromosome Aberration; Chromosome Identification; Chromosome Structure; Gene Assignment; Image Processing; Mathematical Analysis; Metaphase; Methodology; X Chromosome; Fuzzy Logic; Human Chromosomes

International Standard Serial Number (ISSN)

0067-8856

Document Type

Article - Conference proceedings

Document Version

Citation

File Type

text

Language(s)

English

Rights

© 1997 ISA - Instrumentation, Systems, and Automation Society, All rights reserved.

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