Bayesian Skip Net: Building on Prior Information for the Prediction and Segmentation of Stroke Lesions

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One aspect of the present invention proposes a method of predicting meteorological information by using an artificial deep neural network. The present invention according to one example focuses on image processing, specifically on fusing a plurality of ima ...

Measuring perceptual similarity is a key tool in computer vision. In recent years perceptual metrics based on features extracted from neural networks with large and diverse training sets, e.g. CLIP, have become popular. At the same time, the metrics extrac ...

Metabolic magnetic resonance spectroscopic imaging using hyperpolarized contrast agents offers a non-invasive approach to monitoring real-time in vivo energy metabolism. The technique involves hyperpolarizing a contrast agent in a polarizer, administering ...

Deep Learning (DL) models processing images to recognize the health state of large infrastructure components can exhibit biases and rely on non-causal shortcuts. eXplainable Artificial Intelligence (XAI) can address these issues but manually analyzing expl ...

The thalamus is a collection of gray matter nuclei that play a crucial role in sensorimotor processing and modulation of cortical activity. Characterizing thalamic nuclei non-invasively with structural MRI is particularly relevant for patient populations w ...

Deep learning models have shown great promise in estimating tissue microstructure from limited diffusion magnetic resonance imaging data. However, these models face domain shift challenges when test and train data are from different scanners and protocols, ...

Background After 18 months of responding to the COVID-19 pandemic, there is still no agreement on the optimal combination of mitigation strategies. The efficacy and collateral damage of pandemic policies are dependent on constantly evolving viral epidemiol ...

Deep learning (DL) has shown remarkable results in solving inverse problems in various domains. In particular, the Tikhonet approach is very powerful in deconvolving optical astronomical images. However, this approach only uses the l(2) loss, which does no ...

We propose an end-to-end Multitask Learning Transformer framework, named MulT, to simultaneously learn multiple high-level vision tasks, including depth estimation, semantic segmentation, reshading, surface normal estimation, 2D keypoint detection, and edg ...

We conducted a cross-sectional pilot study to explore the biological substrate of the Motoric Cognitive Risk (MCR) syndrome in a Memory Clinic cohort, using a multimodal imaging approach. Twenty participants were recruited and classified as MCR+/-. Amyloid ...

Purpose: Delineation of subtle lesions in magnetic resonance imaging (MRI)-negative patients is of great importance in preoperative epilepsy evaluation. The aim of our study was to explore the diagnostic value of the novel fluid and white matter suppressio ...

Brain stroke is an age-related illness which has become a major issue in our ageing societies. Early diagnosis and treatment are of high importance for the full recovery of the patient, as reminded in Anglo-Saxon countries by the abbreviation FAST (Face, A ...

Among the symptoms of schizophrenia, deficits in the recognition of intention is one of the most studied. However, there is no cognitive model of intention recognition that takes into account both innate and environmental/developmental factors. This work p ...

Bayesian Skip Net: Building on Prior Information for the Prediction and Segmentation of Stroke Lesions

Chattez avec Graph Search

Meteorological information prediction using images from webcams

Adversarially Robust CLIP Models Can Induce Better (Robust) Perceptual Metrics

A hybrid setup for rodent hyperpolarized metabolic imaging using a clinical magnetic resonance scanner

Automated processing of eXplainable Artificial Intelligence outputs in deep learning models for fault diagnostics of large infrastructures

Advancing Thalamic Nuclei Segmentation: The Impact of Compressed Sensing on MRI Processing

Cross-Age and Cross-Site Domain Shift Impacts on Deep Learning-Based White Matter Fiber Estimation in Newborn and Baby Brains

what If...? Pandemic Policy-decision-support to Guide a Cost-benefit-optimised, Country- Specific Response

ShapeNet: Shape constraint for galaxy image deconvolution

MulT: An End-to-End Multitask Learning Transformer

The Biological Substrate of the Motoric Cognitive Risk Syndrome: A Pilot Study Using Amyloid-/Tau-PET and MR Imaging

Fluid and White Matter Suppression Imaging and Voxel-Based Morphometric Analysis in Conventional Magnetic Resonance Imaging-Negative Epilepsy

Data driven approximation of parametrized PDEs by reduced basis and neural networks

Microwave Imaging of Brain Stroke : Contributions to Modeling and Inverse Problem Resolution

Crowding asymmetries in a neural model of image segmentation

Influence of Saliency and Social Impairments on the Development of Intention Recognition