TY - GEN
T1 - Direct classification of human G-banded chromosome images using support vector machines
AU - Mashadi, Narges Tabatabaey
AU - Seyedin, Seyed Alireza
N1 - ©2007 IEEE
PY - 2008/6/27
Y1 - 2008/6/27
N2 - Automatic classification of chromosome images used in karyotyping has been of interest for many years. Regardless of the efforts put into this field, due to the complexity of the matter, still the functional accuracy of current automated systems is much lower than a human operator. Since the interdiction of SVM and its proven efficacy in pattern recognition both in theory and application, we decided to test it's efficacy on G-banded chromosomal images. The results were significantly more favorable. The recognition rate in chromosomal subgroups averaged at 95.9%. Furthermore, alongside this study an unmatched database of chromosomal images with about 42000 items was created which can be used as a reference database for further research in this field.
AB - Automatic classification of chromosome images used in karyotyping has been of interest for many years. Regardless of the efforts put into this field, due to the complexity of the matter, still the functional accuracy of current automated systems is much lower than a human operator. Since the interdiction of SVM and its proven efficacy in pattern recognition both in theory and application, we decided to test it's efficacy on G-banded chromosomal images. The results were significantly more favorable. The recognition rate in chromosomal subgroups averaged at 95.9%. Furthermore, alongside this study an unmatched database of chromosomal images with about 42000 items was created which can be used as a reference database for further research in this field.
KW - Humans
KW - Biological cells
KW - Support vector machines
KW - Support vector machine classification
KW - Pattern recognition
KW - Image databases
KW - Testing
KW - Microscopy
KW - Feature Extraction
KW - Neural network
UR - http://www.scopus.com/inward/record.url?scp=51549087648&partnerID=8YFLogxK
U2 - 10.1109/ISSPA.2007.4555561
DO - 10.1109/ISSPA.2007.4555561
M3 - Conference contribution
AN - SCOPUS:51549087648
SN - 9781424407781
T3 - 2007 9th International Symposium on Signal Processing and its Applications, ISSPA 2007, Proceedings
BT - 2007 9th International Symposium on Signal Processing and its Applications, ISSPA 2007, Proceedings
CY - United States of America
T2 - 2007 9th International Symposium on Signal Processing and its Applications, ISSPA 2007
Y2 - 12 February 2007 through 15 February 2007
ER -