DocumentCode
3082518
Title
Automated segmentation of spinal diffusion tensor MR imaging
Author
Younis, Akmal A. ; Ramirez, Nelson ; Pattany, Pradip M. ; Burns, Robert J. ; Sharawy, Mohamed I.
Author_Institution
Dept. of Electr. & Comput. Eng., Miami Univ., FL, USA
fYear
2005
fDate
8-10 April 2005
Firstpage
187
Lastpage
192
Abstract
A novel automated segmentation technique is presented for the delineation of white matter and gray matter regions in diffusion tensor magnetic resonance imaging of the spine. The technique involves an automated method for the extraction of the spinal cord regions from the diffusion tensor imaging data and relies on the fuzzy means clustering approach, which is inherently robust. Experimental results obtained for the segmentation of in vitro spinal cord sections of varying ages from 48 to 80 years demonstrate the viability of the automated segmentation technique. Statistical comparison with manually delineated white matter regions indicates the potential of the automated technique for the investigation and analysis of white matter abnormalities in diffusion tensor magnetic resonance imaging of the spine.
Keywords
biomedical MRI; fuzzy systems; image segmentation; medical image processing; neurophysiology; pattern clustering; statistical analysis; automated segmentation; diffusion tensor magnetic resonance imaging; fuzzy means clustering; spinal cord region extraction; spinal diffusion tensor MR imaging; spinal gray matter regions; spinal white matter regions; Data mining; Diffusion tensor imaging; Image analysis; Image segmentation; In vitro; Magnetic analysis; Magnetic resonance imaging; Robustness; Spinal cord; Tensile stress;
fLanguage
English
Publisher
ieee
Conference_Titel
SoutheastCon, 2005. Proceedings. IEEE
Print_ISBN
0-7803-8865-8
Type
conf
DOI
10.1109/SECON.2005.1423243
Filename
1423243
Link To Document