DocumentCode
3093664
Title
Brain MR Image Tumor Segmentation with Ventricular Deformation
Author
Xiao, Kai ; Hassanien, Aboul Ella ; Sun, Yan ; Ng, Edwin Kit Keong
Author_Institution
Sch. of Software, Shanghai Jiao Tong Univ., Shanghai, China
fYear
2011
fDate
12-15 Aug. 2011
Firstpage
297
Lastpage
302
Abstract
This paper addresses the issue of the weak association between brain MRI intensity value and anatomical meaning of MR image pixels. By investigating the deformation on brain lateral ventricles and compression from tumor, the correlation between them is quantified and utilized. With the proposed feature extraction component, lateral ventricular deformation is transformed into an additional feature for brain tumor segmentation. Some comparative experiments using both supervised and unsupervised pattern recognition segmentation methods show the improved tumor segmentation accuracy in some image cases.
Keywords
biomedical MRI; brain; feature extraction; image resolution; image segmentation; medical image processing; tumours; MR image pixels; anatomical meaning; brain MR image tumor segmentation; brain MRI intensity value; brain lateral ventricles deformation; brain tumor segmentation; feature extraction component; lateral ventricular deformation; supervised pattern recognition segmentation method; unsupervised pattern recognition segmentation method; Biomedical imaging; Deformable models; Feature extraction; Image segmentation; Magnetic resonance imaging; Shape; Tumors; MR image; MRI; brain tumor; deformation; feature; lateral ventricles; medical image analysis; segmentation;
fLanguage
English
Publisher
ieee
Conference_Titel
Image and Graphics (ICIG), 2011 Sixth International Conference on
Conference_Location
Hefei, Anhui
Print_ISBN
978-1-4577-1560-0
Electronic_ISBN
978-0-7695-4541-7
Type
conf
DOI
10.1109/ICIG.2011.141
Filename
6005572
Link To Document