TY - GEN
T1 - Feature-based VS. Intensity-based brain image registration
T2 - 2007 4th IEEE International Symposium on Biomedical Imaging: From Nano to Macro; ISBI'07
AU - Teverovskiy, L. A.
AU - Carmichael, O. T.
AU - Aizenstein, H. J.
AU - Lazar, N.
AU - Liu, Y.
PY - 2007
Y1 - 2007
N2 - We propose a mutual information-based method for quantitative evaluation of the deformable registration algorithms at three levels: global, voxel-wise and anatomical structure. We compare two fully deformable registration algorithms: feature-based HAMMER and a set of intensity-based algorithms (FEMDemons) in the ITK package. Evaluation is carried out using the AAL template image with 116 labeled anatomical structures and a set of 59 MR brain images: 20 normal controls (CTL), 20 Alzheimer's disease patients (AD) and 19 mild cognitive impairment patients (MCI). We show that both HAMMER and FEM-Demons perform significantly better than an affine registration algorithm, FLIRT, at all three levels. At the global level, FEM-Demons outperforms HAMMER on the images of AD and MCI patients. At the local and anatomical levels, FEM-Demons and HAMMER dominate each other on different brain regions.
AB - We propose a mutual information-based method for quantitative evaluation of the deformable registration algorithms at three levels: global, voxel-wise and anatomical structure. We compare two fully deformable registration algorithms: feature-based HAMMER and a set of intensity-based algorithms (FEMDemons) in the ITK package. Evaluation is carried out using the AAL template image with 116 labeled anatomical structures and a set of 59 MR brain images: 20 normal controls (CTL), 20 Alzheimer's disease patients (AD) and 19 mild cognitive impairment patients (MCI). We show that both HAMMER and FEM-Demons perform significantly better than an affine registration algorithm, FLIRT, at all three levels. At the global level, FEM-Demons outperforms HAMMER on the images of AD and MCI patients. At the local and anatomical levels, FEM-Demons and HAMMER dominate each other on different brain regions.
UR - http://www.scopus.com/inward/record.url?scp=36348949082&partnerID=8YFLogxK
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U2 - 10.1109/ISBI.2007.356917
DO - 10.1109/ISBI.2007.356917
M3 - Conference contribution
AN - SCOPUS:36348949082
SN - 1424406722
SN - 9781424406722
T3 - 2007 4th IEEE International Symposium on Biomedical Imaging: From Nano to Macro - Proceedings
SP - 576
EP - 579
BT - 2007 4th IEEE International Symposium on Biomedical Imaging
Y2 - 12 April 2007 through 15 April 2007
ER -