Affine Coregistration of Diffusion Tensor Magnetic Resonance Images Using Mutual Information

2005 ◽  
pp. 523-530 ◽  
Author(s):  
Alexander Leemans ◽  
Jan Sijbers ◽  
Steve De Backer ◽  
Everhard Vandervliet ◽  
Paul M. Parizel
Keyword(s):  
Magnetic Resonance ◽  
Mutual Information ◽  
Diffusion Tensor ◽  
Magnetic Resonance Images

Cluster Analysis of Diffusion Tensor Magnetic Resonance Images in Human Head Injury

Neurosurgery ◽  
2000 ◽  
Vol 47 (2) ◽  
pp. 306-314 ◽  
Author(s):  
Derek K. Jones ◽  
Ronan Dardis ◽  
Max Ervine ◽  
Mark A. Horsfield ◽  
Martin Jeffree ◽  
...  
Keyword(s):  
Cluster Analysis ◽  
Head Injury ◽  
Magnetic Resonance ◽  
Diffusion Tensor ◽  
Human Head ◽  
Magnetic Resonance Images

scholarly journals A geometric flow-based approach for diffusion tensor image segmentation

2008 ◽  
Vol 366 (1874) ◽  
pp. 2279-2292 ◽  
Author(s):  
Weihong Guo ◽  
Yunmei Chen ◽  
Qingguo Zeng
Keyword(s):  
Magnetic Resonance ◽  
Similarity Measure ◽  
Diffusion Tensor ◽  
Three Dimensional ◽  
Positive Definite Matrix ◽  
Magnetic Resonance Images ◽  
Cerebral White Matter ◽  
Geometric Flow ◽  
Proposed Model ◽  
Consistency Measure

Diffusion tensor magnetic resonance imaging (DT-MRI, shortened as DTI) produces, from a set of diffusion-weighted magnetic resonance images, tensor-valued images where each voxel is assigned a 3×3 symmetric, positive-definite matrix. This tensor is simply the covariance matrix of a local Gaussian process with zero mean, modelling the average motion of water molecules. We propose a three-dimensional geometric flow-based model to segment the main core of cerebral white matter fibre tracts from DTI. The segmentation is carried out with a front propagation algorithm. The front is a three-dimensional surface that evolves along its normal direction with speed that is proportional to a linear combination of two measures: a similarity measure and a consistency measure. The similarity measure computes the similarity of the diffusion tensors at a voxel and its neighbouring voxels along the normal to the front; the consistency measure is able to speed up the propagation at locations where the evolving front is more consistent with the diffusion tensor field, to remove noise effect to some extent, and thus to improve results. We validate the proposed model and compare it with some other methods using synthetic and human brain DTI data; experimental results indicate that the proposed model improves the accuracy and efficiency in segmentation.

A method for non-rigid registration of diffusion tensor magnetic resonance images

2003 ◽  
Author(s):  
Jeffrey T. Duda ◽  
Mariano Rivera ◽  
Daniel C. Alexander ◽  
James C. Gee
Keyword(s):  
Magnetic Resonance ◽  
Diffusion Tensor ◽  
Magnetic Resonance Images ◽  
Rigid Registration

Denoising human cardiac diffusion tensor magnetic resonance images using sparse representation combined with segmentation

2009 ◽  
Vol 54 (6) ◽  
pp. 1435-1456 ◽  
Author(s):  
L J Bao ◽  
Y M Zhu ◽  
W Y Liu ◽  
P Croisille ◽  
Z B Pu ◽  
...  
Keyword(s):  
Magnetic Resonance ◽  
Sparse Representation ◽  
Diffusion Tensor ◽  
Magnetic Resonance Images

Deformable Anatomic Templates Improve Analysis of Gliomas With Minimal Mass Effect in Eloquent Areas

Neurosurgery ◽  
2013 ◽  
Vol 73 (3) ◽  
pp. 534-542 ◽  
Author(s):  
Vinodh A. Kumar ◽  
Jackson Hamilton ◽  
L. Anne Hayman ◽  
Ashok J. Kumar ◽  
Ganesh Rao ◽  
...  
Keyword(s):  
Magnetic Resonance Imaging ◽  
Magnetic Resonance ◽  
Diffusion Tensor ◽  
Mass Effect ◽  
Magnetic Resonance Images ◽  
Diffuse Glioma ◽  
Resonance Imaging ◽  
Resection Cavity ◽  
Eloquent Area ◽  
Minimal Mass

Abstract BACKGROUND: Despite improvements in advanced magnetic resonance imaging and intraoperative mapping, cases remain in which it is difficult to determine whether viable eloquent structures are involved by a glioma. A novel software program, deformable anatomic templates (DAT), rapidly embeds the normal location of eloquent cortex and functional tracts in the magnetic resonance images of glioma-bearing brain. OBJECTIVE: To investigate the feasibility of the DAT technique in patients with gliomas related to eloquent brain. METHODS: Forty cases of gliomas (grade II-IV) with minimal mass effect were referred for a prospective preoperative and postoperative DAT analysis. The DAT results were compared with the patient's functional magnetic resonance imaging, diffusion tensor imaging, operative stimulation, and new postoperative clinical deficits. RESULTS: Fifteen of the 40 glioma patients had overlap between tumor and eloquent structures. Immediate postoperative neurological deficits were seen in 9 cases in which the DAT showed the eloquent area both within the tumor and within or at the edge of the resection cavity. In 6 cases with no deficits, DAT placed the eloquent area in the tumor but outside the resection cavity. CONCLUSION: This is proof of concept that DAT can improve the analysis of diffuse gliomas of any grade by efficiently alerting the surgeon to the possibility of eloquent area invasion. The technique is especially helpful in diffuse glioma because these tumors tend to infiltrate rather than displace eloquent structures. DAT is limited by tract displacement in gliomas that produces moderate to severe mass effect.

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