Title :
A deformable surface model based automatic rat brain extraction method
Author :
Li, Jiehua ; Liu, Xiaofeng ; Zhuo, Jiachen ; Gullapalli, Rao P. ; Zara, Jason M.
Author_Institution :
Dept. of Electr. & Comput. Eng., George Washington Univ., Washington, DC, USA
fDate :
March 30 2011-April 2 2011
Abstract :
The extraction of the brain portion of a neurological image is often necessary prior to tissue segmentation or image registration. While MR Imaging studies on the rat have gained much interest lately, an automatic and robust rat brain extraction tool is still lacking. In this paper, we present a deformable surface model-based rat brain extraction method which extends the popular human brain extraction tool (BET) by incorporating the brain geometry and MRI tissue characteristics of the rat into consideration for more robust extraction. Our method was demonstrated on T2-weighted MR images for five rats and compared with other rat brain extraction methods. Results showed that our method can reliably and robustly extract the rat brain with high accuracy (>;92% volume overlap).
Keywords :
biomechanics; biomedical MRI; brain models; deformation; feature extraction; image registration; image segmentation; medical image processing; neurophysiology; MRI tissue characteristics; T2-weighted MR images; automatic rat brain extraction method; deformable surface model; human brain extraction tool; image parameters; image registration; neurological image; tissue segmentation; Brain modeling; Force; Geometry; Humans; Rough surfaces; Surface roughness; Automatic brain extraction; deformable model; rat brain;
Conference_Titel :
Biomedical Imaging: From Nano to Macro, 2011 IEEE International Symposium on
Conference_Location :
Chicago, IL
Print_ISBN :
978-1-4244-4127-3
Electronic_ISBN :
1945-7928
DOI :
10.1109/ISBI.2011.5872742
