Radiology

Methinks AI software for identifying large vessel occlusion in non-contrast head CT: A pilot retrospective study in American population.

BackgroundNon-contrast computed tomography (NCCT) is the first image for stroke assessment, but its ...

Carotid and femoral bifurcation plaques detected by ultrasound as predictors of cardiovascular events.

Risk factor-based algorithms give a good estimate of cardiovascular (CV) risk at the population leve...

Advances and challenges in AI-assisted MRI for lumbar disc degeneration detection and classification.

PURPOSE: Intervertebral disc degeneration (IDD) is a major contributor to chronic low back pain. Mag...

Letter to the Editor: "Development and Validation of a Deep Learning Ultrasound Radiomics Model for Predicting Drug Resistance in Lymph Node Tuberculosis a Multicenter Study".

Artificial intelligence for multi-time-point arterial phase contrast-enhanced MRI profiling to predict prognosis after transarterial chemoembolization in hepatocellular carcinoma.

PURPOSE: Contrast-enhanced magnetic resonance imaging (CE-MRI) monitoring across multiple time point...

Artificial intelligence in radiology: 173 commercially available products and their scientific evidence.

OBJECTIVES: To assess changes in peer-reviewed evidence on commercially available radiological artif...

Deep learning reconstruction of zero echo time magnetic resonance imaging: diagnostic performance in axial spondyloarthritis.

OBJECTIVES: To compare the diagnostic performance of deep learning reconstruction (DLR) of zero echo...

Enhanced HER-2 prediction in breast cancer through synergistic integration of deep learning, ultrasound radiomics, and clinical data.

This study integrates ultrasound Radiomics with clinical data to enhance the diagnostic accuracy of ...

A Multi-Modal Pelvic MRI Dataset for Deep Learning-Based Pelvic Organ Segmentation in Endometriosis.

Endometriosis affects approximately 190 million females of reproductive age worldwide. Magnetic Reso...

Association of initial core volume on non-contrast CT using a deep learning algorithm with clinical outcomes in acute ischemic stroke: a potential tool for selection and prognosis?

BACKGROUND: In an extended time window, contrast-based neuroimaging is valuable for treatment select...

Agentic AI in radiology: Emerging Potential and Unresolved Challenges.

This commentary introduces agentic artificial intelligence (AI) as an emerging paradigm in radiology...

SUP-Net: Slow-time Upsampling Network for Aliasing Removal in Doppler Ultrasound.

Doppler ultrasound modalities, which include spectral Doppler and color flow imaging, are frequently...

Vox-MMSD: Voxel-wise Multi-scale and Multi-modal Self-Distillation for Self-supervised Brain Tumor Segmentation.

Many deep learning methods have been proposed for brain tumor segmentation from multi-modal Magnetic...

Deep Learning-Driven High Spatial Resolution Attenuation Imaging for Ultrasound Tomography (AI-UT).

Ultrasonic attenuation can be used to characterize tissue properties of the human breast. Both quant...

MSA-Net: a multi-scale and adversarial learning network for segmenting bone metastases in low-resolution SPECT imaging.

BACKGROUND: Single-photon emission computed tomography (SPECT) plays a crucial role in detecting bon...

Pre-interventional transesophageal echocardiography as a reliable predictor of residual shunt following patent foramen ovale closure.

BACKGROUND: Closure of a patent foramen ovale (PFO) is an effective strategy in the prevention of re...

A Dynamic Machine Learning Model to Predict Angiographic Vasospasm After Aneurysmal Subarachnoid Hemorrhage.

BACKGROUND AND OBJECTIVES: The goal of this study was to develop a highly precise, dynamic machine l...

Deep Learning to Differentiate Parkinsonian Syndromes Using Multimodal Magnetic Resonance Imaging: A Proof-of-Concept Study.

BACKGROUND: The differentiation between multiple system atrophy (MSA) and Parkinson's disease (PD) b...

Malignancy classification of thyroid incidentalomas using 18F-fluorodeoxy-d-glucose PET/computed tomography-derived radiomics.

BACKGROUND: Thyroid incidentalomas (TIs) are incidental thyroid lesions detected on fluorodeoxy-d-gl...

Biological tumor volume predicts survival in recurrent High-Grade glioma: A multiparametric [F]FET PET/MRI study.

BACKGROUND AND PURPOSE: Single-session, multiparametric [¹⁸F]FET PET/MRI is used to detect tumor rec...

Preoperative MRI-based radiomics analysis of intra- and peritumoral regions for predicting CD3 expression in early cervical cancer.

The study investigates the correlation between CD3 T-cell expression levels and cervical cancer (CC)...