Please use this identifier to cite or link to this item: http://hdl.handle.net/1959.13/917027

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Title
Automated and domain knowledge-based brain extraction from CT head scans
Author/Creator
Qian, Guoyu;  Luo, Suhuai;  Jin, Jesse S.;  Park, Mira;  Nowinski, Wieslaw L.
Institution
The University of Newcastle. Faculty of Science & Information Technology, School of Design, Communication and Information Technology
Description
A fully automated approach is presented to extract brain efficiently from computed tomography (CT) head scans. Domain knowledge, including Hounsfield unit ranges, brain anatomy and image acquisition parameters, is applied. Regions of interest are first set in each slice by applying thresholding and region growing. Next, the brain candidates are extracted by using three-dimensional region growing with a variable, anatomy and acquisition-dependent structuring element. The proposed method has been applied automatically to 27 normal and pathological CT scans. The average processing time is four seconds for CT scans with 17–47 slices on a standard personal computer and the average sensitivity, specificity and Dice’s index for five cases are 99.6%, 99.4% and 98.7%, respectively.
Relation
International Journal of Computer Aided Engineering and Technology Vol. 1, Issue 4, p. 480-493
Publisher Link
http://dx.doi.org/10.1504/IJCAET.2009.028553
Date
2009
Publisher
Inderscience Publishers
Keyword(s)
image segmentation;  brain extraction;  computed tomography;  CT;  brain anatomy
Resource Type
journal article
Identifier
http://hdl.handle.net/1959.13/917027
Identifier
ISSN:1757-2657
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Subject
"International Journal of Computer Aided Engineering and Technology"
 
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