1 code implementation • 3 Oct 2018 • Mohammad Golbabaee, Zhouye Chen, Yves Wiaux, Mike Davies
Current popular methods for Magnetic Resonance Fingerprint (MRF) recovery are bottlenecked by the heavy computations of a matched-filtering step due to the growing size and complexity of the fingerprint dictionaries in multi-parametric quantitative MRI applications.
no code implementations • 6 Sep 2018 • Mohammad Golbabaee, Zhouye Chen, Yves Wiaux, Mike E. Davies
Current proposed solutions for the high dimensionality of the MRF reconstruction problem rely on a linear compression step to reduce the matching computations and boost the efficiency of fast but non-scalable searching schemes such as the KD-trees.
no code implementations • 23 Jun 2017 • Mohammad Golbabaee, Zhouye Chen, Yves Wiaux, Mike E. Davies
We adopt data structure in the form of cover trees and iteratively apply approximate nearest neighbour (ANN) searches for fast compressed sensing reconstruction of signals living on discrete smooth manifolds.
no code implementations • 17 Dec 2015 • Zhouye Chen, Adrian Basarab, Denis Kouamé
Through this model, the resolution of reconstructed ultrasound images from compressed measurements mainly depends on three aspects: the acquisition setup, i. e. the incoherence of the sampling matrix, the image regularization, i. e. the sparsity prior, and the optimization technique.
no code implementations • 1 Jul 2015 • Zhouye Chen, Adrian Basarab, Denis Kouamé
The interest of compressive sampling in ultrasound imaging has been recently extensively evaluated by several research teams.