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.