Authors:
Toru Abe
1
;
Chieko Hamada
2
and
Tetsuo Kinoshita
1
Affiliations:
1
Cyberscience Center, Tohoku University, Japan
;
2
Graduate School of Information Sciences, Tohoku University, Japan
Keyword(s):
Chromosome image analysis, region extraction, region classification, local band pattern, subregion search.
Related
Ontology
Subjects/Areas/Topics:
Applications and Services
;
Artificial Intelligence
;
Bioinformatics
;
Biomedical Engineering
;
Biomedical Signal Processing
;
Computer Vision, Visualization and Computer Graphics
;
Data Manipulation
;
Health Engineering and Technology Applications
;
Human-Computer Interaction
;
Medical Image Detection, Acquisition, Analysis and Processing
;
Methodologies and Methods
;
Neurocomputing
;
Neurotechnology, Electronics and Informatics
;
Pattern Recognition
;
Physiological Computing Systems
;
Sensor Networks
;
Soft Computing
Abstract:
To make the visual examination of a chromosome image for various chromosome abnormalities, individual chromosome regions have to be extracted from the subject image and classified into the distinct chromosome types. To improve the accuracy and flexibility in this process, we propose a subregion (local band pattern) based method for recognizing chromosome regions in the image. This method regards each chromosome region as a series of subregions, and iterates a search for subregions in the image consecutively. Consequently, chromosome region classification is performed simultaneously with its extraction for each subregion. Since the dimensions and intensities of chromosome regions vary with every image, effective subregion searches require templates whose dimensions and intensities correspond with those of chromosome regions in the image. To develop an effective subregion search, we also propose a method for adjusting the dimensions of templates to those of chromosome regions in the im
age and adapting the intensities in the image to those of the templates.
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