Publication

Wavelet-Regularized Reconstruction For Rapid MRI

Michaël Unser, Dimitri Nestor Alice Van De Ville, Cédric René Jean Vonesch, Jean-Charles Baritaux
2009
Conference Papers

Abstract

We propose a reconstruction scheme adapted to MRI that takes advantage of a sparsity constraint in the wavelet domain. We show that, artifacts are significantly reduced compared to conventional reconstruction methods. Our approach is also competitive with Total Variation regularization both in terms of MSE and computation time. We show that l(1) regularization allows partial recovery of the missing k-space regions. We also present a multi-level version that significantly reduces the computational cost.

Official source

https://infoscience.epfl.ch/entities/publication/269643d1-2292-4683-bff1-34b79dc82660

About this result

This page is automatically generated and may contain information that is not correct, complete, up-to-date, or relevant to your search query. The same applies to every other page on this website. Please make sure to verify the information with EPFL's official sources.

Graph Chat

Chat with Graph Search

Ask any question about EPFL courses, lectures, exercises, research, news, etc. or try the example questions below.

DISCLAIMER: The Graph Chatbot is not programmed to provide explicit or categorical answers to your questions. Rather, it transforms your questions into API requests that are distributed across the various IT services officially administered by EPFL. Its purpose is solely to collect and recommend relevant references to content that you can explore to help you answer your questions.

Wavelet-Regularized Reconstruction For Rapid MRI

Chat with Graph Search

Accelerating Spectral Clustering under Fairness Constraints

Eflop: a Sparsity-aware Metric for Evaluating Computational Cost in Spiking and Non-spiking Neural Networks

Shuffled multi-channel sparse signal recovery