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MACHINE INTELLIGENCE APPROACH FOR OPTIMIZATION OF CRANIAL TUMOR IMAGE

Tamsekar P.B.1, Gomase V.S.2*
1School of Technology, S.R.T.M. University, Sub-Centre, Latur, 413512, India
2School of Technology, S.R.T.M. University, Sub-Centre, Latur, 413512, India
* Corresponding Author : Mailvirusgene1@yahoo.co.in

Received : -     Accepted : -     Published : 21-12-2009
Volume : 1     Issue : 2       Pages : 50 - 54
Int J Mach Intell 1.2 (2009):50-54
DOI : http://dx.doi.org/10.9735/0975-2927.1.2.50-54

Keywords : High-throughput analysis, optimization, cancer, SVM, MRF, CRF
Conflict of Interest : None declared

Cite - MLA : Tamsekar P.B. and Gomase V.S. "MACHINE INTELLIGENCE APPROACH FOR OPTIMIZATION OF CRANIAL TUMOR IMAGE." International Journal of Machine Intelligence 1.2 (2009):50-54. http://dx.doi.org/10.9735/0975-2927.1.2.50-54

Cite - APA : Tamsekar P.B. , Gomase V.S. (2009). MACHINE INTELLIGENCE APPROACH FOR OPTIMIZATION OF CRANIAL TUMOR IMAGE. International Journal of Machine Intelligence, 1 (2), 50-54. http://dx.doi.org/10.9735/0975-2927.1.2.50-54

Cite - Chicago : Tamsekar P.B. and Gomase V.S. "MACHINE INTELLIGENCE APPROACH FOR OPTIMIZATION OF CRANIAL TUMOR IMAGE." International Journal of Machine Intelligence 1, no. 2 (2009):50-54. http://dx.doi.org/10.9735/0975-2927.1.2.50-54

Copyright : © 2009, Tamsekar P.B. and Gomase V.S., Published by Bioinfo Publications. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution and reproduction in any medium, provided the original author and source are credited.

Abstract

High-throughput image analysis is very important aspect of modern post-genomics and proteomics research. Image optimization technology is the driving force of this revolution and technology, which allows the simultaneous monitoring of expression for thousands of images. The need for accurate and reproducible research has driven the development of robust analysis frameworks for maximizing the information content of cancer pathological data. Image optimization is a powerful tool has multiple applications both in clinical and cellular and molecular biology arenas. Image analysis technology has shown new advancements in the field of biomedical research and diagnosis, it allows studying and understanding tumor activities and interactions in malignancies or diseases; therefore, it has great potential for clinical diagnostics in the future.

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