Nick
Todd1, Jaya Prakash2, Henrik Odeen3, Josh de
Bever4, Allison Payne1, Phaneendra Yalavarthy2,
Dennis L. Parker1
1Radiology/UCAIR, University of Utah, Salt Lake CIty, UT, United States; 2Supercomputer Education and Research Centre, Indian Institute of Science, India; 3Physics, University of Utah, Salt Lake CIty, UT, United States; 4Computer Science, University of Utah, Salt Lake CIty, UT, United States
Large coverage 3-D temperature maps are desirable for many thermal therapy applications. Constrained reconstruction algorithms that create images from undersampled k-space data have been shown capable of providing such maps with the necessary spatial and temporal resolution. However, a large computation burden and batch reconstruction prevent the images from being available in real-time. This work attempts to overcome these challenges by developing a real-time temporally constrained reconstruction algorithm, with the goal of providing large volume 3-D temperature maps with less than 1 second latency.