Jin Jin
University of Queensland
46 Papers
221 Citations
Jin Jin is an academic researcher from University of Queensland. The author has contributed to research in topics: Iterative reconstruction & Radiofrequency coil. The author has an hindex of 10, co-authored 45 publications. Previous affiliations of Jin Jin include University of Southern California & Siemens.
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Papers
Improving SAR estimations in MRI using subject-specific models.
TL;DR: Results suggest that the developed patient model can predict regions of elevated SAR within the patient with remarkable accuracy, and a voxel analytical metric that can assist in the construction of a patient library and the selection of the matching model from the library for a patient is proposed.
36
An electromagnetic reverse method of coil sensitivity mapping for parallel MRI - theoretical framework.
TL;DR: Using the sensitivity profiles generated by the novel sensitivity mapping method proposed, SENSE (sensitivity encoding) reconstructions produce significantly less image artefacts than conventional methods.
35
An open 8‐channel parallel transmission coil for static and dynamic 7T MRI of the knee and ankle joints at multiple postures
Jin Jin,Ewald Weber,Aurelien Destruel,Kieran O'Brien,Bassem Henin,Craig Engstrom,Stuart Crozier +6 more
TL;DR: The initial in vivo imaging results of an open architecture eight‐channel parallel transmission (pTx) transceive radiofrequency (RF) coil array that was designed and constructed for static and dynamic 7T MRI of the knee and ankle joints are presented.
29
Sparsity-constrained SENSE reconstruction: an efficient implementation using a fast composite splitting algorithm
TL;DR: The results indicate that, for sparsity-regularized SENSE reconstruction, the FCSA-based method is capable of achieving significant improvements in reconstruction accuracy when compared with the state-of-the-art reconstruction method.
24
QSMxT: Robust masking and artifact reduction for quantitative susceptibility mapping.
Ashley Wilton Stewart,Simon Robinson,Kieran O'Brien,Kieran O'Brien,Jin Jin,Jin Jin,Georg Widhalm,Gilbert Hangel,Gilbert Hangel,Angela Walls,Jonathan Goodwin,Jonathan Goodwin,Korbinian Eckstein,Monique C. Tourell,Catherine Morgan,Aswin Narayanan,Markus Barth,Steffen Bollmann +17 more
TL;DR: In this paper, a robust masking and reconstruction procedure is presented to overcome these limitations and enable automated quantitative susceptibility mapping (QSM), which is integrated within an open-source software framework: QSMxT.