Radiology

Development of an Integrated Deep Learning Approach for Detecting Fetal Brain Abnormalities in Routine Second Trimester Ultrasound Scan: A Multicenter Study.

Purpose To develop and validate an anatomy-aware, two-stage, end-to-end deep learning (DL) pipeline for fetal brain abnormality automated detection on standardized second-trimester brain US images. Materials and Methods This retrospective multicenter study included 319 fetal brain images (218 normal, 101 abnormal) between 19+0 and 23+6 weeks of gestation from nine international fetal medicine cent...

Uncertainty-Aware Multi-Class Brain Tumor Segmentation Using Bayesian U-Net Variants.

Accurate segmentation of brain tumors in magnetic resonance imaging (MRI) is essential for diagnosis, treatment planning, and surgical guidance. Although deep learning-based segmentation methods have achieved strong performance, their clinical adoption remains limited due to the lack of reliable uncertainty estimation. To address this challenge, we propose an uncertainty-aware framework for multi-...

Assessing predictive accuracy of 2D digital templating in fluoroscopy-guided direct anterior approach total hip arthroplasty.

INTRODUCTION: Preoperative 2D digital templating aids surgical planning in total hip arthroplasty (THA). We evaluated template accuracy by comparing p...

Segment anything small for ultrasound: Enhancing segmentation with non-generative augmentation.

Accurate segmentation of anatomical structures in ultrasound (US) images, particularly small ones, is challenging due to noise and variability in imag...

HACR-Net: An Efficient hybrid attention network for MRI image super-resolution.

High-resolution Magnetic Resonance Imaging (MRI) plays an important role in clinical diagnosis and pathological assessment, due to its non-invasive na...

Automatic detection of the fetal brain midsagittal plane on MRI using a deep learning pipeline.

BACKGROUND: Accurate localization of the midsagittal plane (MSP) is essential for evaluating midline brain structures such as the corpus callosum and ...

Multimodal multicentre investigation of diagnostic and prognostic markers in disorders of consciousness.

Severely brain-injured patients may enter a spectrum of conditions collectively known as disorders of consciousness. This spectrum includes clinical c...

On the Utility of Foundation Models for Fast MRI: Vision-Language-Guided Image Reconstruction.

PURPOSE: To investigate whether a vision-language foundation model can enhance undersampled MRI reconstruction by providing high-level contextual info...

Feasibility study of ultrasound-guided, power-assisted needle insertion for hemodialysis cannulation using an innovative, handheld device.

BACKGROUND: Vascular access (VA) for hemodialysis is achieved through arteriovenous fistulas (AVF), arteriovenous grafts (AVG), or central venous acce...

PET imaging of polymyalgia rheumatica: update and future trends.

Polymyalgia rheumatica (PMR) is a common immune-mediated inflammatory disease affecting older adults over 50 years of age and is characterized by cons...

EFSUMB Guidelines on Multiparametric Ultrasound Thyroid Nodule Evaluation: PART I.

Thyroid nodules are common incidental findings, but only a small proportion of cases are malignant (4-6.5%) or symptomatic. Numerous follow-up examina...

EFSUMB Guidelines on Multiparametric Ultrasound Thyroid Nodule Evaluation: PART II.

Thyroid nodules are common incidental findings but only a small proportion of cases are malignant (4-6.5%) or symptomatic. Numerous follow-up examinat...

Utilizing Deep Learning-based Computed Tomography Fractional Flow Reserve on Coronary Artery Disease Diagnosis and Treatment: 1-year Clinical Application From a Chinese Major Hospital.

PURPOSE: Machine learning-based coronary computed tomography fractional flow reserve (CT-FFR) holds great potential for assessing coronary ischemic st...

CT-Free Quantitative Thyroid SPECT Based on Artificial Intelligence: A Prospective Multicenter Noninferiority Clinical Trial.

BACKGROUND: Hybrid single-photon emission computed tomography (SPECT)/computed tomography (CT) is used for the differential diagnosis of thyrotoxicosi...

Magnetically controlled capsule endoscopy: Innovations, standardized practice, and emerging clinical roles.

Capsule endoscopy has transformed small bowel evaluation but remains limited for gastric examination because of passive, peristalsis dependent movemen...

Automated contrast-to-noise ratio analysis in chest CT: validation of an open-source segmentation approach.

OBJECTIVES: This study aimed to evaluate the feasibility and accuracy of automated contrast-to-noise ratio (CNR) analysis in chest CT using the open-s...

Artificial intelligence in the diagnostic imaging of developmental dysplasia of the hip: a systematic review.

PURPOSE: With the increased challenges in diagnosing DDH using traditional ultrasound imaging methods, accurate diagnosis is essential. This study ass...

Automatic Recognition and Prognostic Prediction of Colorectal Liver Metastases Using a Multi-Scale Deep Learning Framework: Model Development and Validation Study.

BACKGROUND: Colorectal cancer liver metastasis (CRLM) presents considerable challenges in both diagnosis and prognosis, as conventional approaches oft...

Carotid Imaging: Current Concepts and Advanced Imaging.

Carotid atherosclerosis is a major cause of ischemic stroke, historically managed according to luminal stenosis severity. However, stenosis alone fail...

Imaging-based stratification of Claudin 18.2-positive gastric adenocarcinoma using 18F-FDG PET/CT radiomics.

PURPOSE: This study aimed to develop and validate a non-invasive, multimodal radiomics model based on preoperative 1⁸F-FDG PET/CT to predict CLDN18.2 ...