Highly accelerated imaging and image reconstruction using adaptive sparsifying transforms

Luke A Pfister (Inventor), Yoram Bresler (Inventor), Saiprasad Ravishankar (Inventor)

Research output: Patent

Abstract

A system executes efficient computational methods for high quality image reconstructions from a relatively small number of noisy (or degraded) sensor imaging measurements or scans. The system includes a processing device and instructions. The processing device executes the instructions to employ transform learning as a regularizer for solving inverse problems when reconstructing an image from the imaging measurements, the instructions executable to: adapt a transform model to a first set of image patches of a first set of images containing at least a first image, to model the first set of image patches as sparse in a transform domain while allowing deviation from perfect sparsity; reconstruct a second image by minimizing an optimization objective comprising a transform-based regularizer that employs the transform model, and a data fidelity term formed using the imaging measurements; and store the second image in the computer-readable medium, the second image displayable on a display device.
Original languageEnglish (US)
U.S. patent number9734601
StatePublished - Aug 15 2017

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