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Abstract #5076

Nonrigid Registration Based Segmentation for the Analysis of Real-Time Cardiac Flow Images.

Freddy Odille1, Jennifer Steeden1, Vivek Muthurangu2, David Atkinson1

1Centre for Medical Image Computing, University College London, London, United Kingdom; 2Centre for Cardiovascular MR, UCL Institute of Child Health, London, United Kingdom

Cardiac flow measurements can be obtained from real-time phase contrast MRI. Due to the compromised spatial resolution and signal-to-noise ratio, automatic segmentation of great vessels is challenging. Here, we propose to use nonrigid registration of the time series of magnitude images (148 frames) to propagate the segmentation performed manually in a reference frame. The registration, based on optical flow, includes smoothness constraints in both space and time, and is computationally very efficient. Flow measurements generated by manual and registration-based segmentations, as well as stroke volumes, were compared in data from 10 volunteers (rest and physical exercise), and showed good agreement.