TY - GEN
T1 - 76-space analysis of grey matter diffusivity
T2 - 8th International Conference on Medical Image Computing and Computer-Assisted Intervention - MICCAI 2005
AU - Liu, Tianming
AU - Young, Geoffrey
AU - Huang, Ling
AU - Chen, Nan Kuei
AU - Wong, Stephen T.C.
N1 - Funding Information:
This research work is supported by a grant to Dr. Wong from the Harvard Center for Neurodegeneration and Repair (HCNR), Harvard Medical School. The normal control datasets are from the NIH sponsored NAMIC (National Alliance of Medical Image Computing) data-repository and are provided by the Laboratory of Neuroscience, Department of Psychiatry, Boston VA Healthcare System and Harvard Medical School, which is supported by following grants: NIMH R01 MH50740 (Shenton), NIH K05 MH01110 (Shenton), NIMH R01 MH52807 (McCarley), NIMH R01 MH40799 (McCarley), VA Merit Awards (Shenton; McCarley) and VA Research Enhancement Award Program (REAP: McCarley). We would like to thank Ms. Yi-ru Lin of HCNR Center for Bioinformatics for manual labeling of selected datasets, Dr. Susumu Mori of the Johns Hopkins University for sharing his DTI datasets, Dr. Noor Kabani of the Montreal Neurological Institute for sharing the brain atlas and Dr. Kelvin Wong for helpful discussions in the revision of this paper.
PY - 2005
Y1 - 2005
N2 - Diffusion Weighted Imaging (DWI) and Diffusion Tensor Imaging (DTI) are widely used in the study and diagnosis of neurological diseases involving the White Matter (WM). However, many neurological and neurodegenerative diseases (e.g., Alzheimer's disease and Creutzfeldt-Jakob disease) are generally considered to involve the Grey Matter (GM). Investigation of GM diffusivity of normal aging and pathological brains has both scientific significance and clinical applications. Most of previous research reports on quantification of GM diffusivity were based on the manually labeled Region of Interests (ROI) analysis of specific neuroanatomic regions. The well-known drawbacks of ROI analysis include inter-rater variations, irreproducible results, tediousness, and requirement of a priori definition of interested regions. In this paper, we present a new framework of automated 76-space analysis of GM diffusivity using DWI/DTI. The framework will be evaluated using clinical data, and applied for study of normal brain, Creutzfeldt-Jakob disease and Schizophrenia.
AB - Diffusion Weighted Imaging (DWI) and Diffusion Tensor Imaging (DTI) are widely used in the study and diagnosis of neurological diseases involving the White Matter (WM). However, many neurological and neurodegenerative diseases (e.g., Alzheimer's disease and Creutzfeldt-Jakob disease) are generally considered to involve the Grey Matter (GM). Investigation of GM diffusivity of normal aging and pathological brains has both scientific significance and clinical applications. Most of previous research reports on quantification of GM diffusivity were based on the manually labeled Region of Interests (ROI) analysis of specific neuroanatomic regions. The well-known drawbacks of ROI analysis include inter-rater variations, irreproducible results, tediousness, and requirement of a priori definition of interested regions. In this paper, we present a new framework of automated 76-space analysis of GM diffusivity using DWI/DTI. The framework will be evaluated using clinical data, and applied for study of normal brain, Creutzfeldt-Jakob disease and Schizophrenia.
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U2 - 10.1007/11566465_19
DO - 10.1007/11566465_19
M3 - Conference contribution
C2 - 16685840
AN - SCOPUS:33744788931
SN - 3540293272
SN - 9783540293279
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 148
EP - 155
BT - Medical Image Computing and Computer-Assisted Intervention - MICCAI 2005 - 8th International Conference, Proceedings
PB - Springer-Verlag
Y2 - 26 October 2005 through 29 October 2005
ER -