Reconstruction of fetal brain MRI with intensity matching and complete outlier removal

被引:305
作者
Kuklisova-Murgasova, Maria [1 ]
Quaghebeur, Gerardine [2 ]
Rutherford, Mary A. [3 ]
Hajnal, Joseph V. [3 ]
Schnabel, Julia A. [1 ]
机构
[1] Univ Oxford, Dept Engn Sci, Inst Biomed Engn, Oxford OX1 2JD, England
[2] John Radcliffe Hosp, Oxford OX3 9DU, England
[3] Univ London Imperial Coll Sci Technol & Med, Hammersmith Hosp, MRC, Imaging Sci Dept,Clin Sci Ctr, London W12 0NN, England
基金
英国工程与自然科学研究理事会;
关键词
Fetal MRI; 3D reconstruction; Super-resolution; Bias field; Intensity matching; IN-UTERO; VOLUME RECONSTRUCTION; SUPERRESOLUTION; SEGMENTATION; IMAGES; PATTERNS;
D O I
10.1016/j.media.2012.07.004
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
We propose a method for the reconstruction of volumetric fetal MRI from 2D slices, comprising super-resolution reconstruction of the volume interleaved with slice-to-volume registration to correct for the motion. The method incorporates novel intensity matching of acquired 20 slices and robust statistics which completely excludes identified misregistered or corrupted voxels and slices. The reconstruction method is applied to motion-corrupted data simulated from MRI of a preterm neonate, as well as 10 clinically acquired thick-slice fetal MRI scans and three scan-sequence optimized thin-slice fetal datasets. The proposed method produced high quality reconstruction results from all the datasets to which it was applied. Quantitative analysis performed on simulated and clinical data shows that both intensity matching and robust statistics result in statistically significant improvement of super-resolution reconstruction. The proposed novel EM-based robust statistics also improves the reconstruction when compared to previously proposed Huber robust statistics. The best results are obtained when thin-slice data and the correct approximation of the point spread function is used. This paper addresses the need for a comprehensive reconstruction algorithm of 3D fetal MRI, so far lacking in the scientific literature. (C) 2012 Elsevier B.V. All rights reserved.
引用
收藏
页码:1550 / 1564
页数:15
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