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Learning Data Triage: Linear Decoding Works for Compressive MRI

Publications associées (27)

Graph Slepians To Strike A Balance Between Local And Global Network Interactions: Application To Functional Brain Imaging

Dimitri Nestor Alice Van De Ville, Thomas William Arthur Bolton, Younes Farouj, Silvia Obertino

Brain function exhibits coordinated activity patterns that are also reflected in anatomy, a finding that can be harnessed to constrain the dynamics of functional time series to the underlying structure while performing various signal processing operations. ...

IEEE2018

Sparse Recovery of Strong Reflectors With an Application to Non-Destructive Evaluation

Martin Vetterli, Jean-Philippe Thiran, Dimitris Perdios, Hanjie Pan, Adrien Georges Jean Besson, Eric Bezzam

In this paper we show that it is sufficient to recover the locations of K strong reflectors within an insonified medium from three receive elements and 2K+1 samples per element. The proposed approach leverages advances in sampling signals with a finite rat ...

IEEE2018

Super Resolution Phase Retrieval for Sparse Signals

Martin Vetterli, Amina Chebira, Gilles Baechler, Juri Ranieri, Miranda Krekovic

In a variety of fields, in particular those involving imaging and optics, we often measure signals whose phase is missing or has been irremediably distorted. Phase retrieval attempts to recover the phase information of a signal from the magnitude of its Fo ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2018

Unified Theory for Recovery of Sparse Signals in a General Transform Domain

Kyong Hwan Jin

Compressed sensing is provided a data-acquisition paradigm for sparse signals. Remarkably, it has been shown that the practical algorithms provide robust recovery from noisy linear measurements acquired at a near optimal sampling rate. In many real-world a ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2018

Learning of robust spectral graph dictionaries for distributed processing

Pascal Frossard, Ntorina Thanou

We consider the problem of distributed representation of signals in sensor networks, where sensors exchange quantized information with their neighbors. The signals of interest are assumed to have a sparse representation with spectral graph dictionaries. We ...

SPRINGEROPEN2018

Development and Optimization of Methods for Accelerated Magnetic Resonance Imaging

Tom Hilbert

Magnetic resonance imaging (MRI) has yielded great success as a medical imaging modality in the past decades, and its excellent soft tissue contrast is used in clinical routine to support diagnosis today. However, MRI is still facing challenges. For exampl ...

EPFL2018

MULAN: A Blind and Off-Grid Method for Multichannel Echo Retrieval

Rémi Gribonval, Helena Peic Tukuljac

This paper addresses the general problem of blind echo retrieval, i.e., given M sensors measuring in the discrete-time domain M mixtures of K delayed and attenuated copies of an unknown source signal, can the echo locations and weights be recovered? This p ...

2018