Paper Info
Title
Parametric mapping of brain tissues from diffusion kurtosis tensor.
Abstract
Diffusion kurtosis imaging (DKI) is a new diffusion magnetic resonance imaging (MRI) technique to go beyond the shortages of conventional diffusion tensor imaging (DTI) from the assumption that water diffuse in biological tissue is Gaussian. Kurtosis is used to measure the deviation of water diffusion from Gaussian model, which is called non-Gaussian, in DKI. However, the high-order kurtosis tensor in the model brings great difficulties in feature extraction. In this study, parameters like fractional anisotropy of kurtosis eigenvalues (FAek) and mean values of kurtosis eigenvalues (Mek) were proposed, and regional analysis was performed for 4 different tissues: corpus callosum, crossing fibers, thalamus, and cerebral cortex, compared with other parameters. Scatterplot analysis and Gaussian mixture decomposition of different parametric maps are used for tissues identification. Diffusion kurtosis information extracted fromkurtosis tensor presented a more detailed classification of tissues actually as well as clinical significance, and the FAek of D-eigenvalues showed good sensitivity of tissues complexity which is important for further study of DKI.
Year
DOI
Venue
2012
10.1155/2012/820847
COMPUTATIONAL AND MATHEMATICAL METHODS IN MEDICINE
Keywords
Field
DocType
normal distribution,water,magnetic resonance imaging,molecular dynamics simulation,brain mapping,anisotropy,diffusion,diffusion tensor imaging
Diffusion MRI,Diffusion Kurtosis Imaging,Tensor,Computer science,Artificial intelligence,Kurtosis,Statistical physics,Computer vision,Fractional anisotropy,Gaussian,Gaussian network model,Nuclear magnetic resonance,Tractography
Journal
Volume
Issue
ISSN
2012
null
1748-670X
Citations 
PageRank 
References 
1
0.37
7
Authors
8
Name
Order
Citations
PageRank
Yuanyuan Chen111.38
Xin Zhao213917.21
Hongyan Ni310.37
Jie Feng410.37
Hao Ding510.37
Hongzhi Qi64920.61
Baikun Wan710416.90
Dong Ming810551.47