Radiology

Latest AI and machine learning research in radiology for healthcare professionals.

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DGEDDGAN: A dual-domain generator and edge-enhanced dual discriminator generative adversarial network for MRI reconstruction.

Magnetic resonance imaging (MRI) as a critical clinical tool in medical imaging, requires a long sca...

Diagnostic value of deep learning of multimodal imaging of thyroid for TI-RADS category 3-5 classification.

BACKGROUND: Thyroid nodules classified within the Thyroid Imaging Reporting and Data Systems (TI-RAD...

The Road Map for ACR Practice Accreditation for Radiology Artificial Intelligence.

As the use of artificial intelligence (AI) continues to grow in radiology, it has become clear that ...

Power-free knee rehabilitation robot for home-based isokinetic training.

Robot-assisted isokinetic training has been widely adopted for knee rehabilitation. However, existin...

MCNEL: A multi-scale convolutional network and ensemble learning for Alzheimer's disease diagnosis.

BACKGROUND AND OBJECTIVE: Alzheimer's disease (AD) significantly threatens community well-being and ...

Quantitative analysis of ureteral jets with dynamic magnetic resonance imaging and a deep-learning approach.

OBJECTIVE: To develop dynamic MRU protocol that focuses on the bladder to capture ureteral jets and ...

Towards automatic US-MR fetal brain image registration with learning-based methods.

Fetal brain imaging is essential for prenatal care, with ultrasound (US) and magnetic resonance imag...

Economics of AI and human task sharing for decision making in screening mammography.

The rising global incidence of breast cancer and the persistent shortage of specialized radiologists...

Hallmarks of artificial intelligence contributions to precision oncology.

The integration of artificial intelligence (AI) into oncology promises to revolutionize cancer care....

Alzheimer's disease prediction using 3D-CNNs: Intelligent processing of neuroimaging data.

Alzheimer's disease (AD) is a severe neurological illness that demolishes memory and brain functioni...

Accurate phenotyping of luminal A breast cancer in magnetic resonance imaging: A new 3D CNN approach.

Breast cancer (BC) remains a predominant and deadly cancer in women worldwide. By 2040, projections ...

Artificial intelligence for breast cancer screening in mammography (AI-STREAM): preliminary analysis of a prospective multicenter cohort study.

Artificial intelligence (AI) improves the accuracy of mammography screening, but prospective evidenc...

Deep learning-driven pulmonary artery and vein segmentation reveals demography-associated vasculature anatomical differences.

Pulmonary artery-vein segmentation is critical for disease diagnosis and surgical planning. Traditio...

D-GET: Group-Enhanced Transformer for Diabetic Retinopathy Severity Classification in Fundus Fluorescein Angiography.

Early detection of Diabetic Retinopathy (DR) is vital for preserving vision and preventing deteriora...

Syn-Net: A Synchronous Frequency-Perception Fusion Network for Breast Tumor Segmentation in Ultrasound Images.

Accurate breast tumor segmentation in ultrasound images is a crucial step in medical diagnosis and l...

CDAF-Net: A Contextual Contrast Detail Attention Feature Fusion Network for Low-Dose CT Denoising.

Low-dose computed tomography (LDCT) is a specialized CT scan with a lower radiation dose than normal...

Deep Augmented Metric Learning Network for Prostate Cancer Classification in Ultrasound Images.

Prostate cancer screening often relies on cost-intensive MRIs and invasive needle biopsies. Transrec...

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