University of Southern California


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MRI Technology

Real-time and interactive MRI requires an entirely new imaging infrastructure that supports real-time reconstruction and display, as well as real-time operator controls (such as scan plane and image contrast). Our acquisition pulse sequences are implemented using the RTHawk real-time imaging system developed at Stanford. We are developing accelerated 2D and 3D imaging techniques tailored to the upper airway and accurate depiction of air-tissue boundaries during vocal production. In addition, we are involved in the development and validation of new targeted phased array coils for imaging the upper airway.

Related references:

YC Kim, MI Proctor, SS Narayanan & KS Nayak, Improved Imaging of Lingual Articulation Using Real-Time Multislice MRI (2012), in Journal of Magnetic Resonance Imaging, 35:4(943-948). [pdf]

Y Zhu, YC Kim, MI Proctor, SS Narayanan & KS Nayak, Dynamic 3D Visualization of Vocal Tract Shaping during Speech (2012), in IEEE Transactions on Medical Imaging. [pdf]

YC Kim, S Narayanan & KS Nayak, Flexible retrospective selection of temporal resolution in real-time speech MRI using a golden-ratio spiral view order (2011), in Magnetic Resonance in Medicine, 65:5(1365-1371). [pdf]

YC Kim, C Hayes, S Narayanan & KS Nayak, A Novel 16-Channel Receive Coil Array for Accelerated Upper Airway MRI at 3 Tesla (2011), in Magnetic Resonance in Medicine, 65:6(1711-1717). [pdf]

YC Kim, S Narayanan & KS Nayak. (2009). Accelerated 3D upper airway MRI using compressed sensing. Magnetic Resonance in Medicine, vol. 61, pp. 1434-1440. [pdf]

E Bresch, YC Kim, K Nayak, D Byrd & S Narayanan. (2008). Seeing Speech: Capturing Vocal Tract Shaping using Real-time Magnetic Resonance Imaging. IEEE Signal Processing Magazine, 123, May 2008. [pdf]

JM Santos, GA Wright & JM Pauly, Flexible Real-Time Magnetic Resonance Imaging Framework Proc., IEEE EMBS, 26th Annual Meeting, San Francisco, 2004. [pdf]

S. Narayanan, K. Nayak, S. Lee, A. Sethy & D. Byrd (2004) An approach to real-time magnetic resonance imaging for speech production. Journal of the Acoustical Society of America, 115, 1771-1776. [pdf]

KS Nayak, CH Cunningham, JM Santos & JM Pauly. Real-Time Cardiac Imaging at 3 Tesla. Magnetic Resonance in Medicine. 2004:51(4):655-660. April 2004. [pdf]

Image Processing and Analysis

Vocal tract image sequences acquired using rtMRI are rich in information, which presents many challenges in the domain of image processing and analysis. Much of our work is focused on developing computational methods to extract low-dimensional representations of image sequences which faithfully capture the complex structures and actions of the vocal tract. Analysis techniques must take theoretical considerations into account regarding scientific/linguistic interpretability, in addition to practical concerns like precision, robustness and efficiency.

Related references:

MI Proctor, AC Lammert, A Katsamanis, L Goldstein, C Hagedorn & SS Narayanan, Direct Estimation of Articulatory Kinematics from Real-time Magnetic Resonance Image Sequences, in Proceedings of Interspeech, Florence, Italy, 2011. [pdf]

AC Lammert, MI Proctor & SS Narayanan, Data-Driven Analysis of Realtime Vocal Tract MRI using Correlated Image Regions, in Proceedings of InterSpeech, 2010. [pdf]

MI Proctor, D Bone, A Katsamanis & SS Narayanan, Rapid Semi-automatic Segmentation of Real-time Magnetic Resonance Images for Parametric Vocal Tract Analysis, in Proceedings of InterSpeech, 2010. [pdf]

E Bresch & SS Narayanan, Region segmentation in the frequency domain applied to upper airway real-time magnetic resonance images (2009), in IEEE Transactions on Medical Imaging, 28:3(323-338). [pdf]

Audio Technology

MRI is a noisy imaging modality, making it challenging to acquire high-quality speech audio to accompany rtMRI videos. Thus, we are actively engaged in researching ways to record and process running speech inside the MRI scanner. The main focus of this work is (a) to ensure synchronicity between image and audio acquisition, and (b) to obtain a good signal-to-noise ratio to facilitate further speech analysis and modeling. The audio setup itself features two fiber optical microphones. Synchronization is achieved with custom designed field-programmable gate array hardware. We use novel approaches for noise cancellation employing, for instance, a pulse-sequence-specific model of the gradient noise of the MRI scanner.

Related references:

Erik Bresch, Jon-Fredrik Nielsen, Krishna Nayak, Shri Narayanan. (2005). Synchronized audio recording and real-time MR imaging of fluent speech. Journal of the Acoustical Society of America, 120 (4), 1791-1794. [pdf]