Publications related to Multi-modal Latent-Space Self-alignment for Super-Resolution Cardiac MR Segmentation

Axial and radial axonal diffusivities and radii from single encoding strongly diffusion-weighted MRI

Erick Jorge Canales Rodriguez, Marco Pizzolato, Tim Bjørn Dyrby

We enable the estimation of the per-axon axial diffusivity from single encoding, strongly diffusion-weighted, pulsed gradient spin echo data. Additionally, we improve the estimation of the per-axon radial diffusivity compared to estimates based on spherica ...

ELSEVIER2023

Learning to sample in Cartesian MRI

Thomas Sanchez

Magnetic Resonance Imaging (MRI) is a non-invasive, non-ionizing imaging modality with unmatched soft tissue contrast. However, compared to imaging methods like X-ray radiography, MRI suffers from long scanning times, due to its inherently sequential acqui ...

EPFL2022

Prospective motion correction in kidney MRI using FID navigators

Tobias Kober

Purpose Abdominal MRI scans may require breath-holding to prevent image quality degradation, which can be challenging for patients, especially children. In this study, we evaluate whether FID navigators can be used to measure and correct for motion prospec ...

WILEY2022

3-Dimensional Fluid and White Matter Suppression Magnetic Resonance Imaging Sequence Accelerated With Compressed Sensing Improves Multiple Sclerosis Cervical Spinal Cord Lesion Detection Compared With Standard 2-Dimensional Imaging

Tobias Kober

Objectives Fluid and white matter suppression (FLAWS) is a recently proposed magnetic resonance sequence derived from magnetization-prepared 2 rapid acquisition gradient-echo providing 2 coregistered datasets with white matter- and cerebrospinal fluid-supp ...

LIPPINCOTT WILLIAMS & WILKINS2022

Combining Model Driven and Data Driven Approaches for Inverse Problems in Parameter Estimation and Image Reconstruction: From Modelling to Validation

Thomas Yu

Machine learning has become the state of the art for the solution of the diverse inverse problems arising from computer vision and medical imaging, e.g. denoising, super-resolution, de-blurring, reconstruction from scanner data, quantitative magnetic reson ...

EPFL2022

Medipix4, a high granularity four sides buttable pixel readout chip for high resolution spectroscopic X-ray imaging at rates compatible with medical CT scans

Viros Sriskaran

Medipix4 is the latest member in the Medipix/Timepix family of pixel detector chips aimed at high rate spectroscopic X-ray imaging using high-Z materials. The chip address the limitations of conventional hybrid pixel detectors for X-ray imaging. Its predec ...

EPFL2022

Diamond-Based Nanoscale Quantum Relaxometry for Sensing Free Radical Production in Cells

Hoda Shirzad, Mayeul Sylvain Chipaux

Diamond magnetometry makes use of fluorescent defects in diamonds to convert magnetic resonance signals into fluorescence. Because optical photons can be detected much more sensitively, this technique currently holds several sensitivity world records for r ...

WILEY-V C H VERLAG GMBH2022

Simulated Half-Fourier Acquisitions Single-shot Turbo Spin Echo (HASTE) of the Fetal Brain: Application to Super-Resolution Reconstruction

Meritxell Bach Cuadra, Patric Hagmann, Reto Meuli, Sébastien Tourbier, Tobias Kober, Hamza Kebiri, Tom Hilbert, Thomas Yu

Accurate characterization of in utero human brain maturation is critical as it involves complex interconnected structural and functional processes that may influence health later in life. Magnetic resonance imaging is a powerful tool complementary to the u ...

SPRINGER INTERNATIONAL PUBLISHING AG2021

Open-access quantitative MRI data of the spinal cord and reproducibility across participants, sites and manufacturers

Dimitri Nestor Alice Van De Ville, Christian Büchel, Nawal Noëlle Kinany, Maryam Seif, Maxime Descoteaux

In a companion paper by Cohen-Adad et al. we introduce the spine generic quantitative MRI protocol that provides valuable metrics for assessing spinal cord macrostructural and microstructural integrity. This protocol was used to acquire a single subject da ...

NATURE PORTFOLIO2021

Self-Attentive Spatial Adaptive Normalization for Cross-Modality Domain Adaptation

Jean-Philippe Thiran, Manana Lortkipanidze, Guillaume Marc Georges Vray, Seyedbehzad Bozorgtabar, Devavrat Tomar

Despite the successes of deep neural networks on many challenging vision tasks, they often fail to generalize to new test domains that are not distributed identically to the training data. The domain adaptation becomes more challenging for cross-modality m ...

Institute of Electrical and Electronics Engineers2021

Towards quantum 3D imaging devices

Claudio Bruschini, Edoardo Charbon, Samuel Burri, Arin Can Ülkü, Paul Mos, Michael Alan Wayne

We introduce a new generation of 3D imaging devices based on quantum plenoptic imaging. Position-momentum entanglement and photon number correlations are exploited to provide a scan-free 3D image after post-processing of the collected light intensity signa ...

2021

Polarization-sensitive optics diffraction tomography

Demetri Psaltis, Ahmed Ayoub, Joowon Lim, Elizabeth Elena Antoine, Amirhossein Saba Shirvan

Polarization of light has been widely used as a contrast mechanism in two-dimensional (2D) microscopy and also in some three-dimensional (3D) imaging modalities. In this paper, we report the 3D tomographic reconstruction of the refractive index (RI) tensor ...

2021

Robust Phase Unwrapping via Deep Image Prior for Quantitative Phase Imaging

Matthias Lütolf, Michaël Unser, Nathalie Brandenberg, Thanh-An Michel Pham, Fangshu Yang

Quantitative phase imaging (QPI) is an emerging label-free technique that produces images containing morphological and dynamical information without contrast agents. Unfortunately, the phase is wrapped in most imaging system. Phase unwrapping is the comput ...

2021

Fat navigators based retrospective motion correction strategies for brain magnetic resonance imaging

Frédéric Gretsch

Magnetic resonance resonance (MRI) is a widely used modality to obtain in vivo tissue information. Clinical applications are near countless, and almost all body parts can be examined using an MR scanner. As the method is non invasive, does not use ionizing ...

EPFL2020

Tracing in 2D to reduce the annotation effort for 3D deep delineation of linear structures

Pascal Fua, Mathieu Salzmann, Agata Justyna Mosinska, Mateusz Kozinski

The difficulty of obtaining annotations to build training databases still slows down the adoption of recent deep learning approaches for biomedical image analysis. In this paper, we show that we can train a Deep Net to perform 3D volumetric delineation giv ...

2020

Roadmap toward the 10 ps time-of-flight PET challenge

Mathieu Benoit, Edoardo Charbon, Christian Morel, Joao Varela

Since the seventies, positron emission tomography (PET) has become an invaluable medical molecular imaging modality with an unprecedented sensitivity at the picomolar level, especially for cancer diagnosis and the monitoring of its response to therapy. Mor ...

IOP PUBLISHING LTD2020

Metabolic fingerprints discriminating severity of acute ischemia using in vivo high-field H-1 magnetic resonance spectroscopy

Hongxia Lei, Lara Buscemi Estefanell, Mario Gaetano Lepore

Despite the improving imaging techniques, it remains challenging to produce magnetic resonance (MR) imaging fingerprints depicting severity of acute ischemia. The aim of this study was to evaluate the potential of the overall high-field H-1 MR Spectroscopy ...

Wiley-Blackwell2020

Micrometer-resolution X-ray tomographic full-volume reconstruction of an intact post-mortem juvenile rat lung

Anders Larsson, Marco Stampanoni, Goran Lovric

In this article, we present an X-ray tomographic imaging method that is well suited for pulmonary disease studies in animal models to resolve the full pathway from gas intake to gas exchange. Current state-of-the-art synchrotron-based tomographic phase-con ...

SPRINGER2021

Homogeneous multifocal excitation for high-throughput super-resolution imaging

Pierre Gönczy, Virginie Hamel, Suliana Manley, Paul Guichard, Dora Mahecic, Kyle Michael Douglass, Denis Fortun, Niccolo Banterle, Khalid Ashraf Mohie Ibrahim, Davide Gambarotto

Super-resolution microscopies have become an established tool in biological research. However, imaging throughput remains a main bottleneck in acquiring large datasets required for quantitative biology. Here we describe multifocal flat illumination for fie ...

2020

Model-informed machine learning for multi-component T2 relaxometry

Jean-Philippe Thiran, Meritxell Bach Cuadra, Tobias Kober, Elda Fischi Gomez, Cristina Granziera, Tom Hilbert, Muhamed Barakovic, Gian Franco Piredda, Erick Jorge Canales Rodriguez, Marco Pizzolato, Thomas Yu

Recovering the distribution from multi-echo magnetic resonance (MR) signals is challenging but has high potential as it provides biomarkers characterizing the tissue micro-structure, such as the myelin water fraction (MWF). In this work, we propose to comb ...

2020