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Evaluation of automated and semi-automated skull-stripping algorithms using similarity index and segmentation error
- Source :
-
Computers in Biology & Medicine . Nov2003, Vol. 33 Issue 6, p495-507. 13p. - Publication Year :
- 2003
-
Abstract
- The skull-stripping in the MR brain image appears to be a key issue in neuroimage analysis. In this paper, we evaluated the accuracy and efficiency of both automated and semi-automated skull-stripping methods. The evaluation was performed on both simulated and real data with the ground truth in skull-stripping. Although automated method showed better efficient results, it should require additional intervention. In contrast to that, semi-automated method showed better accurate results, but it was time consuming and prone to operator bias. Therefore, it might be practical that the semi-automated method was used as the post-processing of the automated one. [Copyright &y& Elsevier]
Details
- Language :
- English
- ISSN :
- 00104825
- Volume :
- 33
- Issue :
- 6
- Database :
- Academic Search Index
- Journal :
- Computers in Biology & Medicine
- Publication Type :
- Academic Journal
- Accession number :
- 10319928
- Full Text :
- https://doi.org/10.1016/S0010-4825(03)00022-2