Abstract #2644

A low rank k-space approach to channel-by-channel reduced FOV imaging

Fadil Ali^1,2, Mark Bydder³, Stefan Zbyn¹, Brendan Eck¹, Ben Garelick⁴, Andres Saucedo⁵, Vahid Ghodrati⁶, Ajin Joy⁶, J. Paul Finn⁶, and Xiaojuan Li¹

¹Imaging Institute, The Cleveland Clinic Foundation, Cleveland, OH, United States, ²Radiology, University of California, Los Angeles, Los Angeles, CA, United States, ³Medical Research, Matai Medical Research Institute, Gisborne, New Zealand, ⁴The Pennsylvania State University, University Park, PA, United States, ⁵The University of Southern California, Los Angeles, CA, United States, ⁶The University of California, Los Angeles, Los Angeles, CA, United States

Synopsis

Keywords: Artifacts, Image Reconstruction, beamforming, phased-array

Motivation: To introduce a channel-by-channel reduced field-of-view (FOV) method for an arbitrary region of interest (ROI).

Goal(s): With N_c channels as input, we output N_c channels, with the signal outside of the target ROI vectorially nulled while preserving the original channel sensitivity profiles and relative phases for each channel.

Approach: Using a full-FOV calibration set, we learned the linear operators needed to be applied on local k-space neighbors across all channels in order to vectorially cancel the signal outside of the target-ROI for any channel.

Results: We were able to generate reduced FOV images in phantom and in vivo settings.

Impact: A reduced FOV method is introduced that determines the linear operators needed to vectorially cancel the signal outside the target ROI. The output is the N_c channels with the region outside of the target ROI cancelled while preserving channel sensitivities.

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