Automatic quality assessment in structural brain magnetic resonance imaging

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2D profiles of electron density and neutral temperature are inferred from multi-delay coherence imaging spectroscopy data of divertor plasmas using a non-linear inversion technique. The inference is based on imaging the spectral line-broadening of Balmer l ...

Background: Fetal brain MRI is increasingly used to complement ultrasound imaging. Images are processed using complex super-resolution reconstruction pipelines, which may bias biometric and volumetric measurements. Objective: To assess the consistency of 2 ...

Magnetic resonance spectroscopic imaging (MRSI) enables the simultaneous noninvasive acquisition of MR spectra from multiple spatial locations inside the brain. Although 1H-MRSI is increasingly used in the human brain, it is not yet widely applied in the p ...

Noninvasive tracking of biochemical processes in the body is paramount in diagnostic medicine. Among the leading techniques is spectroscopic magnetic resonance imaging (MRI), which tracks metabolites with an amplified (hyperpolarized) magnetization signal ...

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 ...

Ultrasound imaging is one of the most widely used medical imaging modalities, with numerous applications in various fields of medicine. Today, its democratization is in full swing, with the increasing availability of quantitative parameters that simplify i ...

Whereas pulse-echo ultrasound imaging relied on focused acoustic waves since its inception, the last two decades have seen the development of techniques based on unfocused waves, including ultrafast ultrasound imaging. In large part due to the emergence of ...

BACKGROUND AND PURPOSE: MS lesions exhibit varying degrees of axonal and myelin damage. A comprehensive description of lesion phenotypes could contribute to an improved radiologic evaluation of smoldering inflammation and remyelination processes. This stud ...

The space industry has experienced substantial growth in recent years, leading to rapid advancements in space exploration and space-based technologies. Consequently, the study of electronics and sensor performance in extreme environments has become crucial ...

Background and Objective: Computational models of the cardiovascular system allow for a detailed and quantitative investigation of both physiological and pathological conditions, thanks to their ability to combine clinical-possibly patient-specific-data wi ...

With the emergence of ultra-portable ultrasound systems, the need to reduce cost and complexity of ultrasound systems has intensified. Sparse arrays, employing fewer transducer elements to acquire images, offer a viable solution by effectively minimizing d ...

Statistical (machine-learning, ML) models are more and more often used in computational chemistry as a substitute to more expensive ab initio and parametrizable methods. While the ML algorithms are capable of learning physical laws implicitly from data, ad ...

As large, data-driven artificial intelligence models become ubiquitous, guaranteeing high data quality is imperative for constructing models. Crowdsourcing, community sensing, and data filtering have long been the standard approaches to guaranteeing or imp ...

AIM: To characterise the corticoreticular pathway (CRP) in a case -control cohort of adolescent idiopathic scoliosis (AIS) patients using high -resolution slice -accelerated readoutsegmented echo -planar diffusion tensor imaging (DTI) to enhance the discri ...

Small-angle X-ray tensor tomography and the related wide-angle X-ray tensor tomography are X-ray imaging techniques that tomographically reconstruct the anisotropic scattering density of extended samples. In previous studies, these methods have been used t ...

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 ...

The performance of machine learning algorithms is conditioned by the availability of training datasets, which is especially true for the field of nondestructive evaluation. Here we propose one reconfigurable specimen instead of numerous reference specimens ...

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 ...

Context. Gaia DR3 has offered the scientific community a remarkable dataset of approximately one million spectra acquired with the radial velocity spectrometer (RVS) in the calcium II triplet region, which is well suited to identify very metal-poor (VMP) s ...

Purpose: This study aims to evaluate two distinct approaches for fiber radius estimation using diffusion-relaxation MRI data acquired in biomimetic microfiber phantoms that mimic hollow axons. The methods considered are the spherical mean power-law approac ...

Automatic quality assessment in structural brain magnetic resonance imaging

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First 2D electron density measurements using multi-delay coherence imaging spectroscopy in the MAST-U Super-X divertor

Biometry and volumetry in multi-centric fetal brain magnetic resonance imaging: assessing the bias of super-resolution reconstruction

Fast High-Resolution Metabolite Mapping in the rat Brain Using 1H-FID-MRSI at 14.1 T

Long-lived enhanced magnetization-A practical metabolic MRI contrast material

Development and clinical validation of computational imaging biomarkers for neurodegenerative diseases

An Angular Framework for Ultrasound Imaging

Inverse Problems in Pulse-Echo Ultrasound: Exploiting Coherence for Image Enhancement and Quantitative Imaging

Multiparametric Characterization and Spatial Distribution of Different MS Lesion Phenotypes

Single-Photon Avalanche Diode Image Sensors for Harsh Radiation Environments

The role of computational methods in cardiovascular medicine: a narrative review

Sequential CNN-based Enhancement of Ultrafast Ultrasound Imaging for Sparse Arrays

Encoding quantum-chemical knowledge into machine-learning models of complex molecular properties

Extensions of Peer Prediction Incentive Mechanisms

The hindbrain and cortico-reticular pathway in adolescent idiopathic scoliosis

X-ray tensor tomography for small-grained polycrystals with strong texture

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

Reduced Training Data for Laser Ultrasound Signal Interpretation by Neural Networks

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

Gaia's brightest very metal-poor (VMP) stars Metallicity catalogue of a thousand VMP stars from Gaia's radial velocity spectrometer spectra

Pore size estimation in axon-mimicking microfibers with diffusion-relaxation MRI