Image Registration for Distortion Correction in Diffusion Tensor Imaging

2003 ◽  
pp. 171-180 ◽  
Author(s):  
Thomas Netsch ◽  
Arianne van Muiswinkel
Keyword(s):  
Diffusion Tensor Imaging ◽  
Image Registration ◽  
Diffusion Tensor ◽  
Distortion Correction

scholarly journals Diffusion tensor imaging of the human kidney: Does image registration permit scanning without respiratory triggering?

2016 ◽  
Vol 44 (2) ◽  
pp. 327-334 ◽  
Author(s):  
Maryam Seif ◽  
Laila Yasmin Mani ◽  
Huanxiang Lu ◽  
Chris Boesch ◽  
Mauricio Reyes ◽  
...  
Keyword(s):  
Diffusion Tensor Imaging ◽  
Image Registration ◽  
Diffusion Tensor ◽  
Human Kidney ◽  
Respiratory Triggering

scholarly journals DTI Image Registration under Probabilistic Fiber Bundles Tractography Learning

2016 ◽  
Vol 2016 ◽  
pp. 1-12
Author(s):  
Zhe Guo ◽  
Yi Wang ◽  
Tao Lei ◽  
Yangyu Fan ◽  
Xiuwei Zhang
Keyword(s):  
Diffusion Tensor Imaging ◽  
Image Registration ◽  
Diffusion Tensor ◽  
Sample Selection ◽  
Nerve Fibers ◽  
Residual Error ◽  
Fiber Bundles ◽  
Finite Sample ◽  
Registration Method ◽  
Sample Set

Diffusion Tensor Imaging (DTI) image registration is an essential step for diffusion tensor image analysis. Most of the fiber bundle based registration algorithms use deterministic fiber tracking technique to get the white matter fiber bundles, which will be affected by the noise and volume. In order to overcome the above problem, we proposed a Diffusion Tensor Imaging image registration method under probabilistic fiber bundles tractography learning. Probabilistic tractography technique can more reasonably trace to the structure of the nerve fibers. The residual error estimation step in active sample selection learning is improved by modifying the residual error model using finite sample set. The calculated deformation field is then registered on the DTI images. The results of our proposed registration method are compared with 6 state-of-the-art DTI image registration methods under visualization and 3 quantitative evaluation standards. The experimental results show that our proposed method has a good comprehensive performance.

scholarly journals Geometric Distortion Correction of Renal Diffusion Tensor Imaging Using the Reversed Gradient Method

2021 ◽  
Vol Publish Ahead of Print ◽  
Author(s):  
Ruth P. Lim ◽  
Jeremy C. Lim ◽  
Jose R. Teruel ◽  
Elissa Botterill ◽  
Jas-mine Seah ◽  
...  
Keyword(s):  
Diffusion Tensor Imaging ◽  
Gradient Method ◽  
Diffusion Tensor ◽  
Distortion Correction ◽  
Geometric Distortion ◽  
Renal Diffusion

How does distortion correction correlate with anisotropic indices? A diffusion tensor imaging study

2006 ◽  
Vol 24 (10) ◽  
pp. 1369-1376 ◽  
Author(s):  
Dae-Jin Kim ◽  
Hae-Jeong Park ◽  
Kyung-Whun Kang ◽  
Yong-Wook Shin ◽  
Jae-Jin Kim ◽  
...  
Keyword(s):  
Diffusion Tensor Imaging ◽  
Diffusion Tensor ◽  
Imaging Study ◽  
Distortion Correction ◽  
Diffusion Tensor Imaging Study
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