TY - GEN
T1 - Mesh quality analysis of MRI content-adaptive FE head models for neuro-electromagnetic imaging
AU - Lee, W. H.
AU - Kim, T. S.
AU - Kim, Y. H.
AU - Lee, S. Y.
PY - 2007
Y1 - 2007
N2 - Realistic finite element (FE) head models for neuro-electromagnetic imaging are getting more attention due to their analytic advantages over conventional models. To improve the numerical efficiency, we have previously developed a novel mesh generation scheme that produces FE head models automatically that are content-adaptive to given MR images. MRI content-adaptive FE meshes (cMeshes) represent the electrically conducting domain more effectively with less number of nodes and elements, thus lessen the computational loads. In general, the cMesh generation is affected by the selection of feature maps derived from MRI. In this study, we have tested the effects of various feature maps on the generation of cMesh FE head models. Also we have evaluated the quality of cMesh FE head models to check their suitability for neuro-electromagnetic imaging using EEG and MEG. The results suggest that the cMesh FE head models with properly selected feature maps do show acceptable quality to be used in neuro-electromagnetic imaging.
AB - Realistic finite element (FE) head models for neuro-electromagnetic imaging are getting more attention due to their analytic advantages over conventional models. To improve the numerical efficiency, we have previously developed a novel mesh generation scheme that produces FE head models automatically that are content-adaptive to given MR images. MRI content-adaptive FE meshes (cMeshes) represent the electrically conducting domain more effectively with less number of nodes and elements, thus lessen the computational loads. In general, the cMesh generation is affected by the selection of feature maps derived from MRI. In this study, we have tested the effects of various feature maps on the generation of cMesh FE head models. Also we have evaluated the quality of cMesh FE head models to check their suitability for neuro-electromagnetic imaging using EEG and MEG. The results suggest that the cMesh FE head models with properly selected feature maps do show acceptable quality to be used in neuro-electromagnetic imaging.
UR - http://www.scopus.com/inward/record.url?scp=34548732539&partnerID=8YFLogxK
U2 - 10.1109/CNE.2007.369658
DO - 10.1109/CNE.2007.369658
M3 - Conference contribution
AN - SCOPUS:34548732539
SN - 1424407923
SN - 9781424407927
T3 - Proceedings of the 3rd International IEEE EMBS Conference on Neural Engineering
SP - 248
EP - 251
BT - Proceedings of the 3rd International IEEE EMBS Conference on Neural Engineering
T2 - 3rd International IEEE EMBS Conference on Neural Engineering
Y2 - 2 May 2007 through 5 May 2007
ER -