Title :
Evaluation of Two Segmentation Methods on MRI Brain Tissue Structures
Author :
Cai, X. ; Hou, Y. ; Li, C. ; Lee, J.-H. ; Wee, W.G.
Author_Institution :
Dept. of Electr. & Comput. Eng. & Comput. Sci., Cincinnati Univ., OH
fDate :
Aug. 30 2006-Sept. 3 2006
Abstract :
In this paper, we evaluate two segmentation methods on 15 brain tissue structures. One is narrow band level set method and the other is pattern classification method based on maximum a posteriori (MAP) probability framework. Two sets of experiments are conducted on 18 verified MRI brain data sets. Dice Similarity Index (DSI) is used to evaluate the closeness between our segmentation results and the gold standards, which were provided by experienced radiologists. The results for comparison of two methods are given and their potential applicability is discussed. Tissue structures such as left and right lateral ventricle have achieved over 70% DSI, while other structures such as third ventricle, caudate nucleus, globus pallidus, putamen and thalamus have achieved above 60% DSI
Keywords :
biological tissues; biomedical MRI; brain; image segmentation; maximum likelihood estimation; medical image processing; neurophysiology; pattern classification; probability; MAP; MRI; brain tissue structure; caudate nucleus; dice similarity index; globus pallidus; lateral ventricle; maximum a posteriori probability framework; narrow band level set method; pattern classification method; putamen; segmentation method evaluation; thalamus; Biomedical engineering; Brain; Cities and towns; Computer science; Image segmentation; Level set; Magnetic resonance imaging; Narrowband; Pixel; Testing;
Conference_Titel :
Engineering in Medicine and Biology Society, 2006. EMBS '06. 28th Annual International Conference of the IEEE
Conference_Location :
New York, NY
Print_ISBN :
1-4244-0032-5
Electronic_ISBN :
1557-170X
DOI :
10.1109/IEMBS.2006.260725
