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High Resolution Time Resolved Contrast Enhanced MR Angiography Using k-t FOCUSS  

Jung, Hong (Bio-Imaging & Signal Processing Lab, Dept. Bio/Brain Engineering, Korea Advanced Institute of Science & Technology (KAIST))
Kim, Eung-Yeop (Department of Radiology and Research Institute of Radiological Science, Yonsei University College of Medicine)
Ye, Jong-Chul (Bio-Imaging & Signal Processing Lab, Dept. Bio/Brain Engineering, Korea Advanced Institute of Science & Technology (KAIST))
Publication Information
Investigative Magnetic Resonance Imaging / v.14, no.1, 2010 , pp. 10-20 More about this Journal
Abstract
Purpose : Recently, the Recon Challenge at the 2009 ISMRM workshop on Data Sampling and Image Reconstruction at Sedona, Arizona was held to evaluate feasibility of highly accelerated acquisition of time resolved contrast enhanced MR angiography. This paper provides the step-by-step description of the winning results of k-t FOCUSS in this competition. Materials and Methods : In previous works, we proved that k-t FOCUSS algorithm successfully solves the compressed sensing problem even for less sparse cardiac cine applications. Therefore, using k-t FOCUSS, very accurate time resolved contrast enhanced MR angiography can be reconstructed. Accelerated radial trajectory data were synthetized from X-ray cerebral angiography images and provided by the organizing committee, and radiologists double blindly evaluated each reconstruction result with respect to the ground-truth data. Results : The reconstructed results at various acceleration factors demonstrate that each components of compressed sensing, such as sparsifying transform and incoherent sampling patterns, etc can have profound effects on the final reconstruction results. Conclusion : From reconstructed results, we see that the compressed sensing dynamic MR imaging algorithm, k-t FOCUSS enables high resolution time resolved contrast enhanced MR angiography.
Keywords
Time resolved contrast enhanced MR angiography; Compressed sensing; k-t FOCUSS; Karhunen-Loeve Transform; Principal component analysis;
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