Co-registration and distortion correction of diffusion and anatomical images based on inverse contrast normalization

被引:82
作者
Bhushan, Chitresh [1 ]
Haldar, Justin P. [1 ]
Choi, Soyoung [2 ]
Joshi, Anand A. [1 ]
Shattuck, David W. [3 ]
Leahy, Richard M. [1 ]
机构
[1] Univ So Calif, Signal & Image Proc Inst, Los Angeles, CA 90089 USA
[2] Univ So Calif, Dana & David Dornsife Cognit Neurosci Imaging Ins, Los Angeles, CA USA
[3] Univ Calif Los Angeles, Dept Neurol, Los Angeles, CA 90024 USA
关键词
Diffusion MRI; Co-registration; Distortion correction; Echo-planar imaging; B-0-field inhomogeneity; ECHO-PLANAR IMAGES; GEOMETRIC DISTORTION; INTENSITY NONUNIFORMITY; NONRIGID REGISTRATION; MRI; EPI; ACCURATE; ROBUST; RECONSTRUCTION; OPTIMIZATION;
D O I
10.1016/j.neuroimage.2015.03.050
中图分类号
Q189 [神经科学];
学科分类号
071006 ;
摘要
Diffusion MRI provides quantitative information about microstructural properties which can be useful in neuroimaging studies of the human brain. Echo planar imaging (EPI) sequences, which are frequently used for acquisition of diffusion images, are sensitive to inhomogeneities in the primary magnetic (B-0) field that cause localized distortions in the reconstructed images. We describe and evaluate a new method for correction of susceptibility-induced distortion in diffusion images in the absence of an accurate B-0 fieldmap. In our method, the distortion field is estimated using a constrained non-rigid registration between an undistorted T1-weighted anatomical image and one of the distorted EPI images from diffusion acquisition. Our registration framework is based on a new approach, INVERSION (Inverse contrast Normalization for VERy Simple registratION), which exploits the inverted contrast relationship between T1- and T2-weighted brain images to define a simple and robust similarity measure. We also describe how INVERSION can be used for rigid alignment of diffusion images and T1-weighted anatomical images. Our approach is evaluated with multiple in vivo datasets acquired with different acquisition parameters. Compared to other methods, INVERSION shows robust and consistent performance in rigid registration and shows improved alignment of diffusion and anatomical images relative to normalized mutual information for non-rigid distortion correction. (C) 2015 Elsevier Inc. All rights reserved.
引用
收藏
页码:269 / 280
页数:12
相关论文
共 67 条
[1]  
Andersson J.L. R., 2011, Diffusion MRI: Theory, Methods, and Applications, P285, DOI [10.1093/med/9780195369779.003.0017., DOI 10.1093/MED/9780195369779.003.0017]
[2]   How to correct susceptibility distortions in spin-echo echo-planar images: application to diffusion tensor imaging [J].
Andersson, JLR ;
Skare, S ;
Ashburner, J .
NEUROIMAGE, 2003, 20 (02) :870-888
[3]  
[Anonymous], PATTERN CLASSIFICATI
[4]   Geometric distortion correction of high-resolution 3 T diffusion tensor brain images [J].
Ardekani, S ;
Sinha, U .
MAGNETIC RESONANCE IN MEDICINE, 2005, 54 (05) :1163-1171
[5]  
Bartels R. H., 1987, INTRO SPLINES USE CO
[6]  
Bhushan C., 2013, MAGN RESON MED
[7]  
Bhushan C., 2012, SIGN INF PROC ASS AN, P1, DOI DOI 10.1177/0963721412473755
[8]  
Bhushan C., 2013, 21st Scientific Meeting of International Society for Magnetic Resonance in Medicine (ISMRM), Salt Lake City, Utah, P55
[9]  
Bowtell R., 1994, SOC MAGN RES ABSTR, V2, P411
[10]   A TECHNIQUE FOR ACCURATE MAGNETIC-RESONANCE-IMAGING IN THE PRESENCE OF FIELD INHOMOGENEITIES [J].
CHANG, H ;
FITZPATRICK, JM .
IEEE TRANSACTIONS ON MEDICAL IMAGING, 1992, 11 (03) :319-329