Radiology

Robot-Assisted Laparoscopic Hysterectomy with Artificial Intelligence-Analyzed Imaging: Robot-Assisted Laparoscopic Hysterectomy with AI Imaging.

Exploring the limit of image resolution for human expert classification of vascular ultrasound images in giant cell arteritis and healthy subjects: the GCA-US-AI project.

OBJECTIVES: Prompt diagnosis of giant cell arteritis (GCA) with ultrasound is crucial for preventing...

CT derived fractional flow reserve: Part 2 - Critical appraisal of the literature.

The integration of computed tomography-derived fractional flow reserve (CT-FFR), utilizing computati...

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...

Accelerated MRI in temporomandibular joints using AI-assisted compressed sensing technique: a feasibility study.

OBJECTIVE: To investigate the feasibility of accelerated MRI with artificial intelligence-assisted c...

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...

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...

Enhancing the Accuracy of Skin Lesion Diagnosis Using Hyperspectral Imaging and Deep Learning.

This study presents a novel diagnostic approach that integrates hyperspectral imaging (HSI) with dee...

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...

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...

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 ...

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...

Pretreatment Multi-sequence Contrast-Enhanced MRI to Predict Response to Immunotherapy in Unresectable Hepatocellular Carcinoma Using Transformer: A Multicenter Study.

Targeted combined immunotherapy (TCI) has shown certain antitumor effects in patients with unresect...

Implementation of biomedical segmentation for brain tumor utilizing an adapted U-net model.

Using radio signals from a magnetic field, magnetic resonance imaging (MRI) represents a medical pro...

Towards more reliable prostate cancer detection: Incorporating clinical data and uncertainty in MRI deep learning.

Prostate cancer (PCa) is one of the most common cancers among men, and artificial intelligence (AI) ...

Diagnostic accuracy of machine learning-based magnetic resonance imaging models in breast cancer classification: a systematic review and meta-analysis.

OBJECTIVE: This meta-analysis evaluates the diagnostic accuracy of machine learning (ML)-based magne...

Enhancing Pulmonary Disease Prediction Using Large Language Models With Feature Summarization and Hybrid Retrieval-Augmented Generation: Multicenter Methodological Study Based on Radiology Report.

BACKGROUND: The rapid advancements in natural language processing, particularly the development of l...

Artery fragment guided approach for enhancing cerebral aneurysm detection in TOF-MRA imaging.

BACKGROUND: Cerebral aneurysms are a type of cerebrovascular disease that poses a severe threat to l...

ACOUSLIC-AI challenge report: Fetal abdominal circumference measurement on blind-sweep ultrasound data from low-income countries.

Fetal growth restriction, affecting up to 10% of pregnancies, is a critical factor contributing to p...

Challenges and Advances in Classifying Brain Tumors: An Overview of Machine, Deep Learning, and Hybrid Approaches with Future Perspectives in Medical Imaging.

Accurate brain tumor classification is essential in neuro-oncology, as it directly informs treatment...

Uncertainty estimation for trust attribution to speed-of-sound reconstruction with variational networks.

PURPOSE: Speed-of-sound (SoS) is a biomechanical characteristic of tissue, and its imaging can provi...