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
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;
Conference_Titel :
Signal Processing in Medicine and Biology Symposium (SPMB), 2012 IEEE
Conference_Location :
New York, NY
Print_ISBN :
978-1-4673-5665-7
DOI :
10.1109/SPMB.2012.6469450