Publication

Overview of the Predictive Value of Quantitative 18 FDG PET in Head and Neck Cancer Treated with Chemoradiotherapy

Publications associées (28)

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

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

Combined deletion of Glut1 and Glut3 impairs lung adenocarcinoma growth

Bernard Lanz, Graham Knott, Rolf Gruetter, Nadine Fournier, Caroline Anne-Lyse Contat, Mario Gaetano Lepore, Etienne Meylan, Anders Meibom, Stéphane Laurent Escrig, Justine Pascual, Louise Helene Soegaard Jensen, Anouk Rossier, Pierre-Benoit Bernard Ancey, Silvia Sabatino, Inti Zlobec

Glucose utilization increases in tumors, a metabolic process that is observed clinically by F-18-fluorodeoxyglucose positron emission tomography (F-18-FDG-PET). However, is increased glucose uptake important for tumor cells, and which transporters are impl ...

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

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

Methods and apparatus for tomographic additive manufacturing with a spatially coherent light source

Christophe Moser, Damien Claude-Marie Loterie, Paul Delrot

A method of fabricating a three-dimensional article comprises providing a spatially coherent light source (101, 201), generating from said light source (101, 201), patterns of light based on computed tomographic projections of said three-dimensional articl ...

2020

Development of novel tools for imaging of metabolic fluxes in vivo

Tamara Maric

Bioluminescent imaging is a powerful technique that enables imaging in living organisms with high sensitivity, low background signal, low cost and without the need for radioactivity. The emitted photons are produced in the oxidation reaction of luciferin c ...

EPFL2020

Image Clustering Algorithms to Identify Complicated Cerebral Diseases. Description and Comparison

Maria-Alexandra Paun

This article presents two algorithms developed based on two different techniques, from clusterization theory, namely k-means clustering technique and Fuzzy C-means technique, respectively. In this context, the study offers a sustained comparison of the two ...

2020