TY - GEN
T1 - Consistent 4D cortical thickness measurement for longitudinal neuroimaging study
AU - Li, Yang
AU - Wang, Yaping
AU - Xue, Zhong
AU - Shi, Feng
AU - Lin, Weili
AU - Shen, Dinggang
PY - 2010
Y1 - 2010
N2 - Accurate and reliable method for measuring the thickness of human cerebral cortex provides powerful tool for diagnosing and studying of a variety of neuro-degenerative and psychiatric disorders. In these studies, capturing the subtle longitudinal changes of cortical thickness during pathological or physiological development is of great importance. For this purpose, in this paper, we propose a 4D cortical thickness measuring method. Different from the existing temporal-independent methods, our method fully utilizes the 4D information given by temporal serial images. Therefore, it is much more resistant to noises from the imaging and pre-processing steps. The experiments on longitudinal image datasets from the Alzheimer's Disease Neuroimaging Initiative (ADNI) show that our method significantly improves the longitudinal stability, i.e. temporal consistency, in cortical thickness measurement, which is crucial for longitudinal study. Power analysis of the correlation between cortical thickness and Mini-Mental-Status-Examination (MMSE) score demonstrated that our method generates statistically more significant results when comparing with the 3D temporal-independent thickness measuring methods.
AB - Accurate and reliable method for measuring the thickness of human cerebral cortex provides powerful tool for diagnosing and studying of a variety of neuro-degenerative and psychiatric disorders. In these studies, capturing the subtle longitudinal changes of cortical thickness during pathological or physiological development is of great importance. For this purpose, in this paper, we propose a 4D cortical thickness measuring method. Different from the existing temporal-independent methods, our method fully utilizes the 4D information given by temporal serial images. Therefore, it is much more resistant to noises from the imaging and pre-processing steps. The experiments on longitudinal image datasets from the Alzheimer's Disease Neuroimaging Initiative (ADNI) show that our method significantly improves the longitudinal stability, i.e. temporal consistency, in cortical thickness measurement, which is crucial for longitudinal study. Power analysis of the correlation between cortical thickness and Mini-Mental-Status-Examination (MMSE) score demonstrated that our method generates statistically more significant results when comparing with the 3D temporal-independent thickness measuring methods.
UR - http://www.scopus.com/inward/record.url?scp=84857035441&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-15745-5_17
DO - 10.1007/978-3-642-15745-5_17
M3 - Conference contribution
C2 - 20879308
AN - SCOPUS:84857035441
SN - 3642157440
SN - 9783642157448
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 133
EP - 142
BT - Medical Image Computing and Computer-Assisted Intervention, MICCAI2010 - 13th International Conference, Proceedings
T2 - 13th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2010
Y2 - 20 September 2010 through 24 September 2010
ER -