DocumentCode :
380135
Title :
Automatic segmentation of the encephalic parenchyma using fuzzy techniques
Author :
Aymerich, F.X. ; Sobrevilla, P. ; Rovira, A. ; Gili, J. ; Montseny, E.
Author_Institution :
Unitat de RM Vall d´´Hebron, Inst. de Diagnostic per la Imatge, Barcelona, Spain
Volume :
3
fYear :
2001
fDate :
2001
Firstpage :
2688
Abstract :
This work shows an automatic, fast and reproducible algorithm to segment the encephalic parenchyma in magnetic resonance (MR) images. The algorithm has been implemented following a rule-based schema in which a fuzzy analysis of MR images information has been introduced to deal with the vagueness associated to the images. The obtention of a fuzzy result helps to determine the accuracy of the classification. The evaluation of the results is based on the use of quality indexes, which allow the comparison with previous works.
Keywords :
biomedical MRI; brain; fuzzy logic; image segmentation; medical image processing; automatic fast reproducible algorithm; automatic segmentation; brain imaging; classification accuracy; encephalic parenchyma; fuzzy techniques; image vagueness; magnetic resonance imaging; medical diagnostic imaging; quality indexes; rule-based schema; Algorithm design and analysis; Central nervous system; Image analysis; Image processing; Image segmentation; Information analysis; Magnetic analysis; Magnetic resonance; Magnetic resonance imaging; Uncertainty;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Engineering in Medicine and Biology Society, 2001. Proceedings of the 23rd Annual International Conference of the IEEE
ISSN :
1094-687X
Print_ISBN :
0-7803-7211-5
Type :
conf
DOI :
10.1109/IEMBS.2001.1017337
Filename :
1017337
Link To Document :
بازگشت