Abstract
Iterative cross-correlation (ICC) is the most popularly used schema for correcting eddy current (EC)-induced distortion in diffusion-weighted imaging data, however, it cannot process data acquired at high b-values. We analyzed the error sources and affecting factors in parameter estimation, and propose an efficient algorithm by expanding the ICC framework with a number of techniques: (1) pattern recognition for excluding brain ventricles; (2) ICC with the extracted ventricle for parameter initialization; (3) gradient-based entropy correlation coefficient (GECC) for optimal and finer registration. Experiments demonstrated that our method is robust with high accuracy and error tolerance, and outperforms other ICC-family algorithms and popular approaches currently in use.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 542-551 |
| Number of pages | 10 |
| Journal | Computerized Medical Imaging and Graphics |
| Volume | 36 |
| Issue number | 7 |
| DOIs | |
| State | Published - Oct 2012 |
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Keywords
- Diffusion tensor imaging
- Diffusion weighted imaging
- Distortion correction
- Eddy current
- Iterative cross-correlation
- Mutual information
ASJC Scopus subject areas
- Radiology Nuclear Medicine and imaging
- Health Informatics
- Radiological and Ultrasound Technology
- Computer Graphics and Computer-Aided Design
- Computer Vision and Pattern Recognition
Cite this
Improving the correction of eddy current-induced distortion in diffusion-weighted images by excluding signals from the cerebral spinal fluid. / Liu, Wei; Liu, Xiaozheng; Yang, Guang; Zhou, Zhenyu; Zhou, Yongdi; Li, Gengying; Dubin, Marc; Bansal, Ravi; Peterson, Bradley S.; Xu, Dongrong.
In: Computerized Medical Imaging and Graphics, Vol. 36, No. 7, 10.2012, p. 542-551.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - Improving the correction of eddy current-induced distortion in diffusion-weighted images by excluding signals from the cerebral spinal fluid
AU - Liu, Wei
AU - Liu, Xiaozheng
AU - Yang, Guang
AU - Zhou, Zhenyu
AU - Zhou, Yongdi
AU - Li, Gengying
AU - Dubin, Marc
AU - Bansal, Ravi
AU - Peterson, Bradley S.
AU - Xu, Dongrong
PY - 2012/10
Y1 - 2012/10
N2 - Iterative cross-correlation (ICC) is the most popularly used schema for correcting eddy current (EC)-induced distortion in diffusion-weighted imaging data, however, it cannot process data acquired at high b-values. We analyzed the error sources and affecting factors in parameter estimation, and propose an efficient algorithm by expanding the ICC framework with a number of techniques: (1) pattern recognition for excluding brain ventricles; (2) ICC with the extracted ventricle for parameter initialization; (3) gradient-based entropy correlation coefficient (GECC) for optimal and finer registration. Experiments demonstrated that our method is robust with high accuracy and error tolerance, and outperforms other ICC-family algorithms and popular approaches currently in use.
AB - Iterative cross-correlation (ICC) is the most popularly used schema for correcting eddy current (EC)-induced distortion in diffusion-weighted imaging data, however, it cannot process data acquired at high b-values. We analyzed the error sources and affecting factors in parameter estimation, and propose an efficient algorithm by expanding the ICC framework with a number of techniques: (1) pattern recognition for excluding brain ventricles; (2) ICC with the extracted ventricle for parameter initialization; (3) gradient-based entropy correlation coefficient (GECC) for optimal and finer registration. Experiments demonstrated that our method is robust with high accuracy and error tolerance, and outperforms other ICC-family algorithms and popular approaches currently in use.
KW - Diffusion tensor imaging
KW - Diffusion weighted imaging
KW - Distortion correction
KW - Eddy current
KW - Iterative cross-correlation
KW - Mutual information
UR - http://www.scopus.com/inward/record.url?scp=84865564707&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84865564707&partnerID=8YFLogxK
U2 - 10.1016/j.compmedimag.2012.06.004
DO - 10.1016/j.compmedimag.2012.06.004
M3 - Article
C2 - 22835646
AN - SCOPUS:84865564707
VL - 36
SP - 542
EP - 551
JO - Computerized Medical Imaging and Graphics
JF - Computerized Medical Imaging and Graphics
SN - 0895-6111
IS - 7
ER -