Radiology

Study on microwave ablation temperature prediction model based on grayscale ultrasound texture and machine learning.

BACKGROUND: Temperature prediction is crucial in the clinical ablation treatment of liver cancer, as...

Enhanced plasmonic scattering imaging via deep learning-based super-resolution reconstruction for exosome imaging.

Exosome analysis plays pivotal roles in various physiological and pathological processes. Plasmonic ...

Magnetically Actuated Soft Microrobot with Environmental Adaptative Multimodal Locomotion Towards Targeted Delivery.

The development of environmentally adaptive solutions for magnetically actuated microrobots to enabl...

[Artificial intelligence in radiology : From the Gartner Hype Cycle to Amara's Law].

3-1-3 Weight averaging technique-based performance evaluation of deep neural networks for Alzheimer's disease detection using structural MRI.

Alzheimer's disease (AD) is a progressive neurological disorder. It is identified by the gradual shr...

The legal regulation of artificial intelligence in the European Union: A practical guide for radiologists.

The European Union is taking the lead globally on the regulation of Artificial Intelligence (AI) and...

A Robust Deep Learning Method with Uncertainty Estimation for the Pathological Classification of Renal Cell Carcinoma Based on CT Images.

This study developed and validated a deep learning-based diagnostic model with uncertainty estimatio...

Uncertainty Estimation for Dual View X-ray Mammographic Image Registration Using Deep Ensembles.

Techniques are developed for generating uncertainty estimates for convolutional neural network (CNN)...

Machine Learning-Enabled Fuhrman Grade in Clear-cell Renal Carcinoma Prediction Using Two-dimensional Ultrasound Images.

OBJECTIVE: Accurate assessment of Fuhrman grade is crucial for optimal clinical management and perso...

The knowledge and perception of patients in Malta towards artificial intelligence in medical imaging.

INTRODUCTION: Artificial intelligence (AI) is becoming increasingly implemented in radiology, especi...

Deep learning enables accurate brain tissue microstructure analysis based on clinically feasible diffusion magnetic resonance imaging.

Diffusion magnetic resonance imaging (dMRI) allows non-invasive assessment of brain tissue microstru...

Dynamic MRI interpolation in temporal direction using an unsupervised generative model.

PURPOSE: Cardiac cine magnetic resonance imaging (MRI) is an important tool in assessing dynamic hea...

Exploration of fractional flow reservation score based on artificial intelligence post-processing for coronary artery lesions in patients with diabetes and coronary heart disease.

In order to evaluate the relationship between coronary heart disease (CHD) and fractional flow reser...

Enhancing Multi-Object Detection in Ultrasound Images Through Semi-Supervised Learning, Focal Loss and Relation of Frame.

OBJECTIVE: To identify musculoskeletal anatomical structures in real time by using deep learning tec...

Comparative evaluation of machine learning models in predicting overall survival for nasopharyngeal carcinoma using F-FDG PET-CT parameters.

PURPOSE: The objective of this study is to assess the prognostic efficacy of F-fluorodeoxyglucose (F...

AI-based lumbar central canal stenosis classification on sagittal MR images is comparable to experienced radiologists using axial images.

OBJECTIVES: The assessment of lumbar central canal stenosis (LCCS) is crucial for diagnosing and pla...

Exploring Deep Learning Applications using Ultrasound Single View Cines in Acute Gallbladder Pathologies: Preliminary Results.

RATIONALE AND OBJECTIVES: In this preliminary study, we aimed to develop a deep learning model using...

Fourier Convolution Block with global receptive field for MRI reconstruction.

Reconstructing images from under-sampled Magnetic Resonance Imaging (MRI) signals significantly redu...

Development of machine learning models to predict papillary carcinoma in thyroid nodules: The role of immunological, radiologic, cytologic and radiomic features.

OBJECTIVE: Approximately 30 % of thyroid nodules yield an indeterminate diagnosis through convention...

A physics-informed deep learning framework for dynamic susceptibility contrast perfusion MRI.

BACKGROUND: Perfusion magnetic resonance imaging (MRI)s plays a central role in the diagnosis and mo...

A Machine Learning Approach for Predicting Biochemical Outcome After PSMA-PET-Guided Salvage Radiotherapy in Recurrent Prostate Cancer After Radical Prostatectomy: Retrospective Study.

BACKGROUND: Salvage radiation therapy (sRT) is often the sole curative option in patients with bioch...