DocumentCode
3438381
Title
Vascular segmentation in magnetic resonance angiography: A modified region growing approach
Author
Almi´ani, M.M. ; Barkana, Buket D.
Author_Institution
Dept. of Comput. Sci. & Eng., Univ. of Bridgeport, Bridgeport, CT, USA
fYear
2012
fDate
1-1 Dec. 2012
Firstpage
1
Lastpage
5
Abstract
A modified region growing algorithm is proposed to extract cerebral vessels using a magnetic resonance angiography (MRA) database. To improve the performance of the image segmentation method, as a pre-processing step, image enhancement methods are applied by the gamma correction technique and spatial operations. This step improves the detection of gray-level discontinuities in MRA images. The traditional region growing method is modified by extending the neighborhood as 24 pixels and by defining a filling protocol to label vascular structure. The performance of the proposed algorithm is compared with that of the traditional region growing method and four other segmentation methods. The minimum and maximum errors of the modified region growing algorithm is calculated as zero and 1.11%, respectively while the traditional region growing method has 0.2% and 7.81%.
Keywords
biomedical MRI; blood vessels; brain; feature extraction; image enhancement; image segmentation; medical image processing; MRA; cerebral vessel extraction; gamma correction; gray-level discontinuities; image enhancement method; magnetic resonance angiography; magnetic resonance angiography database; modified region growing algorithm; spatial operations; vascular segmentation; Angiography; Blood vessels; Educational institutions; Image segmentation; Magnetic resonance; Magnetic resonance angiography (MRA); block-by-block operation; image segmentation; point detection; region growing method;
fLanguage
English
Publisher
ieee
Conference_Titel
Signal Processing in Medicine and Biology Symposium (SPMB), 2012 IEEE
Conference_Location
New York, NY
Print_ISBN
978-1-4673-5665-7
Type
conf
DOI
10.1109/SPMB.2012.6469450
Filename
6469450
Link To Document