A simple method to denoise ratio images in magnetic resonance imaging

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Neurodegenerative and neuroinflammatory disorders often involve complex pathophysiological mechanisms that are â to this date â only partially understood. A more comprehensive understanding of those microstructural processes and their characterization ...

Ultrafast ultrasound imaging, characterized by high frame rates, generates low-quality images. Convolutional neural networks (CNNs) have demonstrated great potential to enhance image quality without compromising the frame rate. However, CNNs have been most ...

Recent advances in image compression have made it both possible and desirable for image quality to approach the visually lossless range. However, the most commonly used subjective visual quality assessment protocols, e.g. those reported in ITU-T Rec. BT.50 ...

Rationale and objectives: To prospectively evaluate feasibility and robustness of an accelerated T2 mapping sequence (GRAPPATINI) in brain imaging and to assess its synthetic T2-weighted images (sT2w) in comparison with a standard T2-weighted sequence (T2 ...

Data for: "A Neural-Network-Based Convex Regularizer for Inverse Problems". The corresponding scripts can be accessed on GitHub (https://github.com/axgoujon/convex_ridge_regularizers). The data is organized as follows: - ct_data_sets.tar.gz: contains prepr ...

The nitrogen-vacancy (NV) center in diamond is a powerful and versatile quantum sensor for diverse quantities. In particular, relaxometry (or T1), can be used to detect magnetic noise at the nanoscale. For experiments with single NV centers the analysis of ...

To obtain a more complete understanding of material microstructure at the nanoscale and to gain profound insights into their properties, there is a growing need for more efficient and precise methods that can streamline the process of 3D imaging using a tr ...

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 ...

ObjectiveWall shear stress (WSS) and its derived spatiotemporal parameters have proven to play a major role on intracranial aneurysms (IAs) growth and rupture. This study aims to demonstrate how ultra-high field (UHF) 7 T phase contrast magnetic resonance ...

Magnetic resonance imaging (MRI) has been a valuable tool in investigating the pathological cascade of Alzheimer's disease (AD) and its progression, which are still open questions. Although some MRI-derived hallmarks in terms of functional connectivity and ...

Noise is an intrinsic part of any sensor and is present, in various degrees, in any content that has been captured in real life environments. In imaging applications, several pre- and post-processing solutions have been proposed to cope with noise in captu ...

Quantitative magnetic resonance imaging (qMRI) can increase the specificity and sensitivity of conventional weighted MRI to underlying pathology by comparing meaningful physical or chemical parameters, measured in physical units, with normative values acqu ...

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 ...

This paper describes the development of a novel medical x-ray imaging system adapted to the needs and constraints of low- and middle-income countries. The developed system is based on an indirect conversion chain: a scintillator plate produces visible ligh ...

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 ...

Attribute-based representations help machine learning models perform tasks based on human understandable concepts, allowing a closer human-machine collaboration. However, learning attributes that accurately reflect the content of an image is not always str ...

MRI is a non-invasive medical imaging modality that is sensitive to patient motion, which constitutes a major limitation in most clinical applications. Solutions may arise from the reduction of acquisition times or from motion-correction techniques, either ...

We study the dynamics of a cavitation bubble near beds of sand of different grain sizes. We use high-speed imaging to observe the motion of the bubble and the sand for different values of the stand-off parameter gamma (dimensionless bubble-boundary distanc ...

Data imputation of incomplete image sequences is an essential prerequisite for analyzing and monitoring all development stages of plants in precision agriculture. For this purpose, we propose a conditional Wasserstein generative adversarial network TransGr ...

Magnetic Resonance Spectroscopy (MRS) is the only technique capable of measuring a large number of metabolites simultaneously in vivo. Ultra-high magnetic fields (UHF) combined with ultra-short echo time (TE) sequences allow the detection of high-quality 1 ...

A simple method to denoise ratio images in magnetic resonance imaging

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Development and clinical validation of computational imaging biomarkers for neurodegenerative diseases

A KL Divergence-Based Loss for In Vivo Ultrafast Ultrasound Image Enhancement with Deep Learning

On the assessment of high-quality images: advances on the JPEG AIC-3 activity

Clinical feasibility and validation of the accelerated T2 mapping sequence GRAPPATINI in brain imaging

Data for: "A Neural-Network-Based Convex Regularizer for Inverse Problems"

Optimizing Data Processing for Nanodiamond Based Relaxometry

3D reconstruction of curvilinear one-dimensional objects viewed in transmission electron microscopy

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

Near-wall hemodynamic parameters quantification in in vitro intracranial aneurysms with 7 T PC-MRI

Brain microstructural and functional MRI: developments and application to a rat model of Alzheimer's disease

On combining denoising with learning-based image decoding

Variability and reproducibility of multi-echo T2 relaxometry: Insights from multi-site, multi-session and multi-subject MRI acquisitions

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

X-ray imaging detector for radiological applications adapted to the context and requirements of low- and middle-income countries

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

Attribute Prediction as Multiple Instance Learning

Choreography Controlled (ChoCo) brain MRI artifact generation for labeled motion-corrupted datasets

Dynamics of cavitation bubbles near granular boundaries

Time Dependent Image Generation of Plants from Incomplete Sequences with CNN-Transformer

Advanced metabolite mapping at ultra-high field using 1H-MRS, 1H-MRSI and macromolecules: applications in a rat model of type C hepatic encephalopathy