Paper Info
Title
Motion Aware MR Imaging via Spatial Core Correspondence.
Abstract
Motion awareness in MR imaging is essential when it comes to long acquisition times. For volumetric high-resolution or temporal resolved images, sporadic subject movements or respiration induced organ motion has to be considered in order to reduce motion artifacts. We present a novel MR imaging sequence and an associated retrospective reconstruction method incorporating motion via spatial correspondence of the k-space center. The sequence alternatingly samples k-space patches located in the center and in peripheral higher frequency regions. Each patch is transformed into the spatial domain in order to normalize for spatial transformations rigidly as well as non-rigidly. The k-space is reconstructed from the spatially aligned patches where the alignment is derived using image registration of the center patches. Our proposed method assumes neither periodic motion nor requires any binning of motion states to properly compensate for movements during acquisition. As we directly acquire volumes, 2D slice stacking is avoided. We tested our method for brain imaging with sporadic head motion and for chest imaging where a volunteer has been scanned under free breathing. In both cases, we demonstrate high-quality 3D reconstructions.
Year
DOI
Venue
2018
10.1007/978-3-030-00928-1_23
Lecture Notes in Computer Science
Keywords
Field
DocType
Magnetic Resonance Imaging,Motion correction,4DMRI
Mr imaging,Computer vision,Periodic function,Normalization (statistics),Pattern recognition,Organ Motion,Computer science,Chest imaging,Artificial intelligence,Neuroimaging,Image registration,Magnetic resonance imaging
Conference
Volume
ISSN
Citations 
11070
0302-9743
0
PageRank 
References 
Authors
0.34
2
6
Name
Order
Citations
PageRank
Christoph Jud1397.12
Damien Nguyen200.68
Robin Sandkühler332.97
Alina Giger411.09
Oliver Bieri592.34
Philippe C. Cattin636746.80