Abstract #3538

Empirically-Trained Image Contrast Synthesis for Intravascular MRI Endoscopy

Xiaoyang Liu^1,2 and Paul Bottomley^1,2

¹Department of Electrical and Computer Engineering, Johns Hopkins University, Baltimore, MD, United States, ²MR Research Division, Department of Radiology, Johns Hopkins University, Baltimore, MD, United States

Parameterized image synthesis is desirable for region-specific image contrast and protocol optimization. While this could arguably be performed with quantitative mapping and Bloch equation simulations, it is not well-suited for real-time cine MRI or MRI endoscopy in a real-time interventional application with views changing from frame-to-frame. Here we propose to use empirical data to calibrate signal behavior patterns from a specific MRI endoscopic device and pulse sequences to fit new acquisitions from which extra images and ultimately guide automated local contrast optimization.

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