Hybrid utrasound and MRI acquisitions for high-speed imaging of respiratory organ motion

Hybrid utrasound and MRI acquisitions for high-speed imaging of respiratory organ motion

Preiswerk, Frank and Toews, Matthew and Hoge, W. Scott and Chiou, Jr Yuan George and Panych, Lawrence P. and Wells, William M. and Madore, Bruno

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 2015

Abstract : Magnetic Resonance (MR) imaging provides excellent image quality at a high cost and low frame rate. Ultrasound (US) provides poor image quality at a low cost and high frame rate. We propose an instance-based learning system to obtain the best of both worlds: high quality MR images at high frame rates from a low cost single-element US sensor. Concurrent US and MRI pairs are acquired during a relatively brief offline learning phase involving the US transducer and MR scanner. High frame rate, high quality MR imaging of respiratory organ motion is then predicted from US measurements, even after stopping MRI acquisition, using a probabilistic kernel regression framework. Experimental results show predicted MR images to be highly representative of actual MR images.