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