Radiology

Cybersecurity for Interventional Radiologists: A Clinical Imperative for Protecting Patient Data and Imaging Systems.

Cybersecurity threats to medical imaging systems and workflows are no longer confined to information technology departments; they directly affect interventional radiology (IR) practice, patient safety, and procedural continuity. Two thirds of healthcare organizations experienced ransomware in 2024, with median and mean ransom payments of 1.5 million and 4.4 million dollars, respectively, and 725 l...

Clinical Application of an AI-Driven Framework for Accurate Endometrial Thickness Measurement in Transvaginal Ultrasound.

OBJECTIVE: This study aims to develop an AI-based framework for automatic endometrial thickness (ET) measurement in transvaginal ultrasound (TVUS) based on a large dataset and evaluate its performance from various clinical perspectives. METHODS: A dataset of 9850 ultrasound images from 5110 cases at Shenzhen Guangming District People's Hospital (2019-2023) was retrospectively included for training...

GL-mamba-net: A magnetic resonance imaging restoration network with global-local mamba.

In clinical practice, magnetic resonance imaging is essential for disease diagnosis and evaluation, although it generally requires a prolonged scannin...

Optimizing knee MRI: 3D proton density turbo spin echo nDixon sequence vs. 2D high-resolution turbo spin echo in half the acquisition time.

OBJECTIVES: The objective of this study was to evaluate the use of a single proton density (PD) new Dixon (nDixon) three-dimensional turbo spin echo (...

Rapid MR examination with deep learning reconstruction improves diagnosis of complicated acute appendicitis.

OBJECTIVE: To evaluate the performance of a non-contrast rapid magnetic resonance imaging (MRI) protocol with deep learning reconstruction (DLR) for i...

Potential for AI as first reader in lung cancer screening.

PURPOSE: To retrospectively assess the agreement between human and automated AI-based readings for low-dose computed tomography (LDCT) outcomes accord...

Accuracy of Photon Dose Calculation on Photon-Counting Computed Tomography-A Comparison Study Based on Virtual Monoenergetic and Electron Density (Rho) Images for Pancreatic Cases.

PURPOSE: Photon-counting computed tomography (PCCT) offers versatile anatomic information because of better energy discrimination and higher spatial r...

Feasibility of deep learning-accelerated HASTE-FS for pancreatic cystic lesion surveillance: comparison with conventional HASTE and MRCP.

PURPOSE: Pancreatic cystic lesions (PCL) commonly undergo surveillance using MRI with MR cholangiopancreatography (MRCP). Our objective is to compare ...

Abdominal multi-organ segmentation on 3D negative-contrast CT cholangiopancreatography: a comparative study of deep learning methods.

OBJECTIVES: This study aims to automate segmentation of the biliary and pancreatic systems on 3D negative-contrast CT cholangiopancreatography (3D-nCT...

Transformer-based ultrasound radiomics for novel multi-task automated segmentation and classification of ovarian tumors.

OBJECTIVE: To develop and evaluate a comprehensive AI-driven pipeline for automated segmentation and multi-class classification of ovarian tumors in u...

An Interpretable Machine Learning Model Based on MRI Features for Predicting Pain Severity in Temporomandibular Disorders.

BACKGROUND: Chronic pain around the temporomandibular joint (TMJ) and masticatory muscles is a primary symptom of temporomandibular disorders (TMD). H...

Total-body [18F]FDG-PET/CT imaging of healthy volunteers with minimal effective dose.

PURPOSE: High-sensitivity, total-body (TB) positron emission tomography (PET) and computed tomography (CT) imaging systems enable substantial reductio...

Efficacy of MRI-based deep learning algorithm for detecting acute ischemic stroke: evaluation among diverse readers.

OBJECTIVES: The efficacy of an MRI-based deep learning algorithm (DLA) for detecting acute ischemic stroke (AIS) was evaluated across readers with div...

Advancing deep learning based knee cartilage segmentation in MRI: Innovations, challenges and applications.

OBJECTIVE: Recent advancements in deep learning (DL) have advanced knee cartilage segmentation in Magnetic Resonance Imaging (MRI), offering scalable,...

MiniGPT-Pancreas: Multimodal Large Language Model for Pancreas Cancer Observation and Localization in CT Images.

Pancreatic cancer remains one of the deadliest malignancies, primarily because of its subtle CT appearance and frequent late-stage diagnosis. We intro...

Decoding depression with computer vision-assisted analysis of synchronized facial expressions.

BACKGROUND: Facial expressions convey nonverbal signals of internal emotional states and hold potential as important markers for affective disorders s...

Automated Segmentation of Bilateral Vestibular Schwannoma in Neurofibromatosis 2 (NF2).

OBJECTIVE: Automated segmentation models for volumetric measurement of vestibular schwannoma (VS) have been developed for sporadic VS but not for bila...

A Novel Instance Segmentation Method for Real-Time Detection of Thyroid Nodules in Ultrasound Videos: A Multi-Center Study.

OBJECTIVES: Thyroid nodules are one of the most common thyroid disorders and can be categorized into benign and malignant thyroid nodules. Currently, ...

Review of Techniques and Technologies for Mosaicking Ultrasound Volumes.

Ultrasound imaging, known for its affordability, portability and real-time capabilities, has become a crucial diagnostic tool worldwide. However, the ...

DoubleBlock-ViT: A MaxViT-based enhancement and dual-path skip connections for brain tumor segmentation in MRI scans.

BACKGROUND: Manual interpretation of brain tumor regions in MRI scans demands substantial medical expertise, is time-consuming, and is prone to human ...