title: Improving the correction of eddy current-induced distortion in diffusion-weighted images by excluding signals from the cerebral spinal fluid.
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.
authors: Key Laboratory of Brain Functional Genomics, Ministry of Education & Shanghai Key Laboratory of Brain Functional Genomics, Shanghai Key Laboratory of Magnetic Resonance, East China Normal University, Shanghai, China.
authors: Wei
authors: W
authors: Liu
authors: Xiaozheng
authors: X
authors: Liu
authors: Guang
authors: G
authors: Yang
authors: Zhenyu
authors: Z
authors: Zhou
authors: Yongdi
authors: Y
authors: Zhou
authors: Gengying
authors: G
authors: Li
authors: Marc
authors: M
authors: Dubin
authors: Ravi
authors: R
authors: Bansal
authors: Bradley S
authors: BS
authors: Peterson
authors: Dongrong
authors: D
authors: Xu
mesh_terms: D000465:Algorithms; D002555:Cerebrospinal Fluid; D038524:Diffusion Magnetic Resonance Imaging / Q000379:methods; D056324:Diffusion Tensor Imaging / Q000379:methods*; D017352:Echo-Planar Imaging / Q000379:methods*; D019277:Entropy; D006801:Humans; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D007091:Image Processing, Computer-Assisted; D019047:Phantoms, Imaging