Manoj K. Sarma1,
M. Albert Thomas1, Peng Hu2, Daniel B. Ennis2,
Ke K. Sheng3
1Radiological
Sciences, UCLA School of Medicine, Los Angeles, CA, United States; 2Radiological
Sciences, University of California Los Angeles, Los Angeles, CA, United
States; 3Radiation Oncology, UCLA School of Medicine, Los Angeles,
CA, United States
Radiotherapy guided by MRI has afforded the hardware potential to treat a moving tumor more accurately but existing imaging speed is inadequate for 3D real-time lung and lung tumor imaging. By exploiting the intrinsic coherence of the patient anatomy during time, we adapted a k-t SLR compressed sensing method to dramatically reduce the amount of data that is needed to update a new dynamic imaging without losing details. We were able to accurately track moving tumors of nine patients based on images reconstructed with very high data under-sampling ratio up to 5% of the original data.
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