Title: Automated and domain knowledge-based brain extraction from CT head scans

Authors: Guoyu Qian, Suhuai Luo, Jesse S. Jin, Mira Park, Wieslaw L. Nowinski

Addresses: The School of Design Communication and IT, The University of Newcastle, University Drive, Callaghan NSW 2308, Australia; Biomedical Imaging Lab, Agency for Science, Technology and Research, 30 Biopolis Street, S(138671), Singapore. ' The School of Design Communication and IT, The University of Newcastle, University Drive, Callaghan NSW 2308, Australia. ' The School of Design Communication and IT, The University of Newcastle, University Drive, Callaghan NSW 2308, Australia. ' The School of Design Communication and IT, The University of Newcastle, University Drive, Callaghan NSW 2308, Australia. ' Biomedical Imaging Lab, Agency for Science, Technology and Research, 30 Biopolis Street, S(138671), Singapore

Abstract: 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.

Keywords: image segmentation; brain extraction; computed tomography; CT head scans; brain anatomy; image acquisition.

DOI: 10.1504/IJCAET.2009.028553

International Journal of Computer Aided Engineering and Technology, 2009 Vol.1 No.4, pp.480 - 493

Published online: 18 Sep 2009 *

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