title: Hybrid Utrasound and MRI Acquisitions for High-Speed Imaging of Respiratory Organ Motion.
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 offine 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.
authors.affiliation: Brigham and Women's Hospital, Harvard Medical School.
authors.forename: Frank
authors.initials: F
authors.lastname: Preiswerk
authors.affiliation: Brigham and Women's Hospital, Harvard Medical School.
authors.forename: Matthew
authors.initials: M
authors.lastname: Toews
authors.affiliation: Brigham and Women's Hospital, Harvard Medical School.
authors.forename: W Scott
authors.initials: WS
authors.lastname: Hoge
authors.affiliation: Brigham and Women's Hospital, Harvard Medical School.
authors.forename: Jr-Yuan George
authors.initials: JG
authors.lastname: Chiou
authors.affiliation: Brigham and Women's Hospital, Harvard Medical School.
authors.forename: Lawrence P
authors.initials: LP
authors.lastname: Panych
authors.affiliation: Brigham and Women's Hospital, Harvard Medical School.
authors.forename: William M
authors.initials: WM
authors.lastname: Wells
authors.affiliation: Brigham and Women's Hospital, Harvard Medical School.
authors.forename: Bruno
authors.initials: B
authors.lastname: Madore