Chromosome classification using dynamic time warping

Authors:
Benoít Legrand;C. S. Chang;S. H. Ong;Soek-Ying Neo;Nallasivam Palanisamy
Affiliations:
Department of Electrical and Computer Engineering, National University of Singapore, Singapore 117576, Singapore;Department of Electrical and Computer Engineering, National University of Singapore, Singapore 117576, Singapore;Department of Electrical and Computer Engineering, Division of Bioengineering, National University of Singapore, Singapore 117576, Singapore;Genome Institute of Singapore, 60 Biopolis Street, Singapore 138672, Singapore;Genome Institute of Singapore, 60 Biopolis Street, Singapore 138672, Singapore
Venue:
Pattern Recognition Letters
Year:
2008

Citing 3
Cited 5

Fundamentals of speech recognition

Fundamentals of speech recognition
Automatic locating the centromere on human chromosome pictures

CBMS'03 Proceedings of the 16th IEEE conference on Computer-based medical systems
Toward a completely automatic neural-network-based human chromosomeanalysis

IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics

Faster retrieval with a two-pass dynamic-time-warping lower bound

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

Computer Methods and Programs in Biomedicine
A chromosome image recognition method based on subregions

ACCV'09 Proceedings of the 9th Asian conference on Computer Vision - Volume Part III
Time series classification by class-specific Mahalanobis distance measures

Advances in Data Analysis and Classification
LocateMe: Magnetic-fields-based indoor localization using smartphones

ACM Transactions on Intelligent Systems and Technology (TIST) - Survey papers, special sections on the semantic adaptive social web, intelligent systems for health informatics, regular papers

Quantified Score

Hi-index	0.10

Visualization

Abstract

A classifier based on dynamic time warping (DTW) has been developed to perform the classification of human chromosomes. DTW is used in speech recognition applications to compare two time-sequences. This paper describes a method to adapt the DTW technique in order to deal with the length and the density profile, which are common features used in classifying chromosomes. The DTW classifier is able to compare chromosomes with different elongations. Since chromosomes are non-rigid objects, the proposed classifier has the main advantage of requiring only a small training set in comparison with the conventional methods based on Bayesian classifiers or neural networks. For the same classification accuracy of 81.0%, we achieve a reduction of 88% of the size of the training set in comparison with a Bayesian classifier.