Radiology

Advances in photoacoustic imaging reconstruction and quantitative analysis for biomedical applications.

Photoacoustic imaging (PAI), a modality that combines the high contrast of optical imaging with the ...

Automatic lymphedema segmentation in T2-STIR MRI using an unsupervised clustering method.

PURPOSE: To develop and evaluate an unsupervised artificial intelligence (AI)-based method for the a...

Deep learning for high-resolution magnetic resonance vessel wall imaging: image reconstruction, stenosis diagnosis and plaque calculation.

OBJECTIVES: This study developed an automated AI-based method for accurate image reconstruction, ste...

Performance of an adult-trained AI tool for intracranial hemorrhage detection on head CT in children aged 6-17 years.

BACKGROUND: Most commercially available artificial intelligence (AI) tools in radiology are trained ...

An Optimized Strategy for Brain Tumor Classification Using SO(3) Equivariant Graph Neural Networks with Snow Geese Algorithm in MRI Imaging.

Brain tumors (BT) are actually an uncontrolled growth of cancer cells inside the body that can be cl...

Scanner-integrated reconstruction versus post-processing deep learning for low-count 18F-FDG PET/CT: a comparative clinical evaluation.

OBJECTIVES: To compare two deep learning (DL) approaches for low-count PET/CT: deep progressive reco...

Interval cancer, sensitivity, and specificity comparing AI-supported mammography screening with standard double reading without AI in the MASAI study: a randomised, controlled, non-inferiority, single-blinded, population-based, screening-accuracy trial.

BACKGROUND: Evidence indicates that artificial intelligence (AI) can improve mammography screening b...

Machine learning prediction of live birth after IVF using the morphological uterus sonographic assessment group features of adenomyosis.

Diagnostic accuracy of artificial intelligence models for temporomandibular joint anomalies on MRI: a systematic review and meta-analysis.

BACKGROUND: Artificial intelligence (AI) techniques are increasingly applied to magnetic resonance i...

Functional and Structural Evidence of Neurofluid Circuit Aberrations in Huntington Disease.

OBJECTIVE: Disrupted neurofluid regulation may contribute to neurodegeneration in Huntington disease...

High Accuracy but Low Explainability: The Challenge of Explainable Artificial Intelligence in Multiple Sclerosis Assessment From Magnetic Resonance Imaging Radiology Reports.

Timely identification of disease progression and/or active lesions in multiple sclerosis (MS) is ess...

Diagnostic performance of AI-assisted intraoperative imaging for parathyroid identification: a systematic review.

BACKGROUND: Intra-operative identification of parathyroid glands might be technically challenging an...

Ultrasound-guided sound speed correction for photoacoustic computed tomography.

Photoacoustic computed tomography (PACT) reconstructs high-resolution images of various chromophores...

The Impact of a Neuroradiologist on the Report of a Real-World CT Perfusion Imaging Map Derived from Artificial Intelligence/Machine Learning-Driven Software.

BACKGROUND AND PURPOSE: According to the guideline, CT perfusion should be read and analyzed by usin...

Development of a quantitative multiparametric ultrasound and deep learning classifier for the detection of prostate cancer.

OBJECTIVES: Prostate cancer (PCa) diagnosis is increasingly guided by imaging, with ultrasound (US) ...

A New Insight into Imaging Diagnosis of Otosclerosis Enhanced by Machine Learning and Radiomics.

Otosclerosis is a disease affecting the middle and inner ear, characterized by abnormal bone remodel...

DOSTA-Net: Domain-Shuffle Temporal Attention Network for Vessel Extraction in X-Ray Coronary Angiography Using Synthetic Data.

Artery extraction from X-ray coronary angiography (XCA) images is essential for the accurate diagnos...

Incorporating artificial intelligence into imaging for surveillance and diagnosis of liver cancer: Innovations, challenges, and clinical translation.

Primary liver cancer, mainly hepatocellular carcinoma and intrahepatic cholangiocarcinoma, remains a...

Veterinary workers report low knowledge of artificial intelligence but positive attitudes toward its adoption in diagnostic imaging and the workplace as a whole.

OBJECTIVE: To describe veterinary workers' knowledge, attitudes, and practices regarding AI in veter...

Clinical Validation of Deep Learning-Accelerated versus Wave-CAIPI Postcontrast 3D T1-MPRAGE for Evaluation of Intracranial Enhancing Lesions.

BACKGROUND AND PURPOSE: Deep learning (DL) reconstruction methods have shown promise in accelerating...

Alzheimer's disease diagnosis support for brain perfusion SPECT scans in a real-world clinical cohort.

BackgroundDementia diagnosis is challenging and often delayed. Brain imaging techniques such as sing...