Tag: Medical Imaging

A retrospective study of 428 hospitalized COVID-19 patients in southern Iran found that more than 40 percent of chest HRCT ...

A standardized benchmark of six convolutional neural networks shows that the most accurate pneumonia-detecting models also produce the most faithful ...

A deep learning model segments fetal lungs on MRI in about four seconds with expert-level accuracy across diverse pulmonary hypoplasia ...

Researchers in South Korea have developed a fully automated deep-learning system that uses supervised contrastive learning across multiphase CT scans ...

A new deep learning model that embeds Turing-inspired reaction-diffusion mathematics and attention mechanisms into a ResNet50 backbone classifies dermoscopic images ...

Researchers in Ethiopia have built an interpretable deep learning ensemble that identifies malaria parasite species from thin blood smears with ...

A comprehensive new review in Neural Computing and Applications charts how machine learning and deep learning are transforming lymphoma diagnosis ...

Researchers have built a two-stage deep learning workflow that converts routine brain MRI into CT-like images and attenuation-corrected PET scans, ...

Researchers have developed LMANet, a lightweight multiscale attention network that achieves high-accuracy skin-lesion segmentation with only 5.6 million parameters by ...

Researchers in India combined EfficientNet-B0 and a transformer encoder to classify Alzheimer's disease from multi-slice MRI scans, achieving 88 percent ...

Researchers have developed a Swin Transformer-based U-Net with a novel SECA cross-attention decoder that improves breast tumor segmentation accuracy across ...

A new study shows that combining spectral CT-derived extracellular volume and skeletal muscle index with CEA and tumor stage improves ...

A prospective study shows that a random forest model combining shear wave elastography, contrast-enhanced ultrasound and clinical factors can predict ...

Researchers in Vietnam have developed U-NetL2O, an explainable learning-to-optimize framework that embeds a U-Net into an unrolled ADMM scheme to ...

A new review of 61 studies reveals that the explainability and privacy protections required for trustworthy medical and biometric deep ...

A Memorial Sloan Kettering feasibility study found that ChatGPT-4 could plan CT-guided lung biopsy trajectories that were safe in 93 ...

A two-sequence abbreviated MRI protocol using hepatobiliary phase imaging detected recurrent hepatocellular carcinoma after microwave ablation with 87.5 percent sensitivity ...

In an era where innovative applications of medical imaging and 3D printing are gaining traction, researchers Dell, Wist, and Grasshoff ...

Professors Scott Acton and Mathews Jacob, esteemed faculty members from the University of Virginia’s Charles L. Brown Department of Electrical ...