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Novel brain imaging platform combines upright PET and AR eye tracking to advance cognitive disorder research
A cutting-edge brain imaging platform that integrates upright PET scanning, an augmented reality (AR) headset, and motion ...
Science Daily2d
Breakthrough magnet design could transform MRI and magnetic levitation
Two German physicists have reimagined how to create powerful and uniform magnetic fields using compact permanent magnets. By ...
pv magazine International14d
Denoising outdoor electroluminescence images of PV panels through deep learning
A group of scientists led by researchers from the University of New South Wales (UNSW) in Australia has developed a novel deep-learning method for denoising outdoor electroluminescence (EL) images ...
Frontiers21d
Deep plug-and-play denoising prior with total variation regularization for low-dose CT - Frontiers
This advancement in deep learning has also inspired researchers to apply these techniques for image denoising, including noise reduction and artifact suppression in LDCT. Convolutional neural networks ...
snmjournals.org24d
Impact of Deep Learning-Based PET Image Denoising at Reduced Scan Time on Estimated Lesion Detectability
251367 Introduction: Lesion detectability is a critical metric in PET imaging, particularly in oncology, impacting diagnostic accuracy and patient outcomes. This study evaluates how a deep ...
GitHub24d
denoising-images · GitHub Topics · GitHub
Exploring deep learning models for medical imaging. ... pipelines distortion-correction bids motion-correction diffusion-mri denoising-images. Updated Apr 28, 2025; Python; ... medicine graphics ...
The Lancet27d
Deep learning for predicting invasive recurrence of ductal carcinoma in situ : leveraging histopathology images and clinical features - The Lancet
Deep learning models using routinely processed WSIs hold promise for DCIS risk stratification, while the benefits of integrating clinical data merit further investigation. Obtaining a larger, ...
EurekAlert!27d
Deep learning-powered denoising technique for high-speed dynamic fluorescence imaging | EurekAlert!
A self-supervised deep learning model has been developed to improve the quality of dynamic fluorescence images by leveraging temporal gradients. The method enables accurate denoising without ...
IEEE27d
Deep learning enables fast and accurate quantification of MRI-guided near-infrared spectral tomography for breast cancer diagnosis - IEEE Xplore
The utilization of magnetic resonance (MR) im-aging to guide near-infrared spectral tomography (NIRST) shows significant potential for improving the specificity and sensitivity of breast cancer ...
ascopubs.org28d
A novel application of deep learning (DL)-based MRI with liquid biomarkers for immune effector cell-associated neurotoxicity syndrome (ICANS) after chimeric antigen receptor ...
Background: ICANS is a complication of CAR T-cell therapy, yet risk factors and quantitative diagnostic criteria, particularly neuroimaging criteria, remain incompletely characterized. We implemented ...
IEEE28d
Deep Separable Spatiotemporal Learning for Fast Dynamic Cardiac MRI
Objective: Dynamic magnetic resonance imaging (MRI) plays an indispensable role in cardiac diagnosis. To enable fast imaging, the k-space data can be undersampled but the image reconstruction poses a ...