Reconstruction of fetal brain MRI with intensity matching and complete outlier removal.
Bottom Line: The method incorporates novel intensity matching of acquired 2D slices and robust statistics which completely excludes identified misregistered or corrupted voxels and slices.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.
Affiliation: Institute of Biomedical Engineering, Department of Engineering Science, University of Oxford, UK. firstname.lastname@example.orgShow MeSH
Mentions: Fig. 5 compares slice weights assigned by EM and Huber robust statistics for reconstruction from six simulated stacks. It can be seen that EM robust statistics assign zero weights to all corrupted and obviously misregistered slices, while Huber statistics only reduce their weights. Several slices have rather small TRE, but were assigned relatively small weights (below 0.5) by EM robust statistics. Visual inspection revealed that these are slices with high information content, where a small displacement can result in a relatively large intensity error. Conversely, some slices with small regions of interest and low information content, which are especially prone to misregistrations, can exhibit rather small intensity errors despite larger TRE and are thus not excluded.
Affiliation: Institute of Biomedical Engineering, Department of Engineering Science, University of Oxford, UK. email@example.com