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

fYear

2006

fDate

Aug. 30 2006-Sept. 3 2006

Firstpage

3029

Lastpage

3032

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;

fLanguage

English

Publisher

ieee

Conference_Titel

Engineering in Medicine and Biology Society, 2006. EMBS '06. 28th Annual International Conference of the IEEE

Conference_Location

New York, NY

ISSN

1557-170X

Print_ISBN

1-4244-0032-5

Electronic_ISBN

1557-170X

Type

conf

DOI

10.1109/IEMBS.2006.260725

Filename

4462435