Please use this identifier to cite or link to this item: http://hdl.handle.net/1959.13/917027
- Automated and domain knowledge-based brain extraction from CT head scans
Jin, Jesse S.;
Nowinski, Wieslaw L.
- The University of Newcastle. Faculty of Science & Information Technology, School of Design, Communication and Information Technology
- 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.
- International Journal of Computer Aided Engineering and Technology Vol. 1, Issue 4, p. 480-493
- Publisher Link
- Inderscience Publishers
- Resource Type
- journal article