Tractography passes the test: Results from the diffusion-simulated connectivity (disco) challenge

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Two-Tier Mapper, an unbiased topology-based clustering method for enhanced global gene expression analysis

Kathryn Hess Bellwald, Cathrin Brisken, Jacques Rougemont, Rachel Marcone

Motivation: Unbiased clustering methods are needed to analyze growing numbers of complex data sets. Currently available clustering methods often depend on parameters that are set by the user, they lack stability, and are not applicable to small data sets. ...

2019

Learning new physics from a machine

Andrea Wulzer, Raffaele Tito D'Agnolo

We propose using neural networks to detect data departures from a given reference model, with no prior bias on the nature of the new physics responsible for the discrepancy. The virtues of neural networks as unbiased function approximants make them particu ...

American Physical Society2019

Gray-matter-specific MR imaging improves the detection of epileptogenic zones in focal cortical dysplasia: A new sequence called fluid and white matter suppression (FLAWS)

Tobias Kober, Thomas Yu, Nan Chen, Xin Chen

Objectives: To evaluate the diagnostic value and characteristic features of FCD epileptogenic zones using a novel sequence called fluid and white matter suppression (FLAWS). ...

ELSEVIER SCI LTD2018

Diffusion-weighted imaging evidence of altered white matter development from late childhood to early adulthood in Autism Spectrum Disorder

Djalel Eddine Meskaldji, Fikret Isik Karahanoglu

Autism Spectrum Disorder (ASD) is thought to reflect disrupted development of brain connectivity characterized by white matter abnormalities and dyscoordination of activity across brain regions that give rise to core features. But there is little consensus ...

2018

Reducing false positives in tractography with microstructural and anatomical priors

Jean-Philippe Thiran, Alessandro Daducci, Muhamed Barakovic, Gabriel Girard, Maxime Descoteaux

Tractography has proven particularly effective for studying noninvasively the neuronal architecture of the brain but recent studies have showed that the high incidence of false positives can significantly bias any connectivity analysis. We present a novel ...

2018

Towards microstructure fingerprinting: Estimation of tissue properties from a dictionary of Monte Carlo diffusion MRI simulations

Jean-Philippe Thiran, Benoît Macq, Gabriel Girard, Gaëtan Olivier D Rensonnet

Many closed-form analytical models have been proposed to relate the diffusion-weighted magnetic resonance imaging (DW-MRI) signal to microstructural features of white matter tissues. These models generally make assumptions about the tissue and the diffusio ...

2018

MATHICSE Technical Report : Analysis of stochastic gradient methods for PDE-constrained optimal control problems with uncertain parameters

Fabio Nobile, Matthieu Claude Martin, Sebastian Krumscheid

We consider the numerical approximation of a risk-averse optimal control problem for an elliptic partial differential equation (PDE) with random coefficients. Specifically, the control function is a deterministic, dis- tributed forcing term that minimizes ...

MATHICSE2018

Cortical Dysconnectivity Measured by Structural Covariance Is Associated With the Presence of Psychotic Symptoms in 22q11.2 Deletion Syndrome

Dimitri Nestor Alice Van De Ville, Marie Schaer, Maude Schneider, Maria Carmela Padula

BACKGROUND: 22q11.2 deletion syndrome (22q11DS) is the third-largest known genetic risk factor for the development of psychosis. Dysconnectivity has consistently been implicated in the physiopathology of psychosis. Structural covariance of cortical morphol ...

2018

Feature optimization for atomistic machine learning yields a data-driven construction of the periodic table of the elements

Félix Benedito Clément Musil, Michele Ceriotti, Michael John Willatt

Machine-learning of atomic-scale properties amounts to extracting correlations between structure, composition and the quantity that one wants to predict. Representing the input structure in a way that best reflects such correlations makes it possible to im ...

2018

In-vivo probabilistic atlas of human thalamic nuclei based on diffusion-weighted magnetic resonance imaging

Jean-Philippe Thiran, Meritxell Bach Cuadra, Patric Hagmann, Elena Najdenovska, Maxime Descoteaux

The thalamic nuclei are involved in many neurodegenerative diseases and therefore, their identification is of key importance in numerous clinical treatments. Automated segmentation of thalamic subparts is currently achieved by exploring diffusion-weighted ...

NATURE PUBLISHING GROUP2018

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