Radiology

Application Value of Deep Learning-Based AI Model in the Classification of Breast Nodules.

Breast nodules are highly prevalent among women, and ultrasound is a widely used screening tool. Ho...

Psychedelics, entactogens and psychoplastogens for depression and related disorders.

Currently, the most actively investigated rapidly acting antidepressants, anxiolytics and/or anti PT...

ThreeF-Net: Fine-grained feature fusion network for breast ultrasound image segmentation.

Convolutional Neural Networks (CNNs) have achieved remarkable success in breast ultrasound image seg...

A review: Lightweight architecture model in deep learning approach for lung disease identification.

As one of the leading causes of death worldwide, early detection of lung disease is a very important...

Predicting pulmonary hemodynamics in pediatric pulmonary arterial hypertension using cardiac magnetic resonance imaging and machine learning: an exploratory pilot study.

PURPOSE: Pulmonary arterial hypertension (PAH) significantly affects the pulmonary vasculature, requ...

Comparative analysis of pre-transcatheter aortic valve implantation CTA protocols: Optimizing radiation dose and contrast volume.

BACKGROUND: To establish the most effective and safe pre-transcatheter aortic valve implantation (TA...

Application of Machine Learning to Breast MR Imaging.

The demand for breast imaging services continues to grow, driven by expanding indications in breast ...

Does restrictive anorexia nervosa impact brain aging? A machine learning approach to estimate age based on brain structure.

Anorexia nervosa (AN), a severe eating disorder marked by extreme weight loss and malnutrition, lead...

Enhancing Free-hand 3D Photoacoustic and Ultrasound Reconstruction using Deep Learning.

This study introduces a motion-based learning network with a global-local self-attention module (MoG...

Uncovering ethical biases in publicly available fetal ultrasound datasets.

We explore biases present in publicly available fetal ultrasound (US) imaging datasets, currently at...

Long-term prognostic value of the CT-derived fractional flow reserve combined with atherosclerotic burden in patients with non-obstructive coronary artery disease.

OBJECTIVES: The long-term prognostic significance of the coronary computed tomography angiography (C...

Correction: Optimizing breast lesions diagnosis and decision-making with a deep learning fusion model integrating ultrasound and mammography: a dual-center retrospective study.

Same-model and cross-model variability in knee cartilage thickness measurements using 3D MRI systems.

PURPOSE: Magnetic Resonance Imaging (MRI) based three-dimensional analysis of knee cartilage has evo...

Multimodal deep learning for enhanced breast cancer diagnosis on sonography.

This study introduces a novel multimodal deep learning model tailored for the differentiation of ben...

Fusion of FDG and FMZ PET Reduces False-Positives in Predicting Epileptogenic Zone.

BACKGROUND AND PURPOSE: Epilepsy, a globally prevalent neurologic disorder, necessitates precise ide...

Application of Deep Learning Accelerated Image Reconstruction in T2-Weighted Turbo Spin-Echo Imaging of the Brain at 7T.

Prolonged imaging times and motion sensitivity at 7T necessitate advancements in image acceleration ...

Current status and challenges of minimally invasive ultrasound thermal ablation technology.

Image-guided minimally invasive ultrasound thermal ablation has been widely studied for disease trea...

OneTouch Automated Photoacoustic and Ultrasound Imaging of Breast in Standing Pose.

We developed an automated photoacoustic and ultrasound breast tomography system that images the pati...

Minimizing human-induced variability in quantitative angiography for a robust and explainable AI-based occlusion prediction in flow diverter-treated aneurysms.

BACKGROUND: Bias from contrast injection variability is a significant obstacle to accurate intracran...

Summary Report of the SNMMI AI Task Force Radiomics Challenge 2024.

In medical imaging, challenges are competitions that aim to provide a fair comparison of different m...

A strategy for the automatic diagnostic pipeline towards feature-based models: a primer with pleural invasion prediction from preoperative PET/CT images.

BACKGROUND: This study aims to explore the feasibility to automate the application process of nomogr...