An efficient transportation algorithm for automatic chromosome karyotyping
Pattern Recognition Letters
A hybrid method for automatic chromosome karyotyping
Pattern Recognition Letters
New features for automatic classification of human chromosomes: A feasibility study
Pattern Recognition Letters
WISB '06 Proceedings of the 2006 workshop on Intelligent systems for bioinformatics - Volume 73
A novel algorithm for straightening highly curved images of human chromosome
Pattern Recognition Letters
Automated classification of metaphase chromosomes: Optimization of an adaptive computerized scheme
Journal of Biomedical Informatics
Supervised parametric and non-parametric classification of chromosome images
Pattern Recognition
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Automated chromosome classification has been an important pattern recognition problem for decades. Numerous attempts were made in the past to characterize chromosome band patterns as part of the feature description vector. In this paper, we describe a recent study to employ wavelet packets as basis function sets to compute chromosome band pattern features. 28 wavelet packet basis function sets were evaluated in this study. The experimental results are presented and compared with those of currently best-performing method on two benchmark chromosome datasets.