DocumentCode :
3545628
Title :
MRS Based Brain Tumors Diagnosing
Author :
Yanzhen, Han ; Yan, Zhou ; Peng, Yang
Author_Institution :
Hebei Univ. of Eng., Handan, China
fYear :
2009
fDate :
21-22 Nov. 2009
Firstpage :
56
Lastpage :
58
Abstract :
Nuclear magnetic resonance has been successfully used for the grading and typing of brain tumors. Magnetic resonance (MR) or nuclear magnetic resonance (NMR) has been widely used in hospital since the 80´s. Magnetic resonance spectroscopy (MRS) is one of the main fields of MR. Our objective was to propose a classifier to ensures higher reliability and reduces time and expense costs by introducing partial and total rejection. The proposed classifier ensures higher reliability and reduces time and expense costs by introducing partial and total rejection.
Keywords :
NMR spectroscopy; biomedical MRI; biomedical NMR; brain; feature extraction; image classification; medical image processing; tumours; brain tumors; image classifier; image feature extraction; magnetic resonance spectroscopy; nuclear magnetic resonance; partial rejection; reliability; total rejection; tumor diagnosing; Biopsy; Cancer; Cells (biology); Decision support systems; Design automation; Magnetic resonance; Neoplasms; Nuclear magnetic resonance; Spectroscopy; Testing; diagnosing; magnetic resonance spectroscopy;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Information Technology Application Workshops, 2009. IITAW '09. Third International Symposium on
Conference_Location :
Nanchang
Print_ISBN :
978-1-4244-6420-3
Electronic_ISBN :
978-1-4244-6421-0
Type :
conf
DOI :
10.1109/IITAW.2009.84
Filename :
5419497
Link To Document :
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