Radiology

Fine-grained and multi-pattern anti-nuclear antibody recognition: A new dataset and framework.

Indirect immunofluorescence (IIF) staining imaging on human epithelial cell (HEp-2) is a standard technique for anti-nuclear antibodies (ANA) screening. The application of deep neural networks for automated IIF image processing has led to remarkable progress in ANA pattern recognition. However, existing research has predominantly focused on coarse-grained and single-pattern recognition, despite th...

Artificial intelligence-enhanced three-dimensional radiological analysis for predicting spread through air spaces in early-stage lung adenocarcinoma.

OBJECTIVES: Spread through air space (STAS) is a pathological feature that correlates with poor prognosis, especially in patients with lung adenocarcinoma undergoing sublobar resection. The microscopic nature of STAS complicates direct detection using preoperative radiological imaging. We aimed to develop an artificial intelligence (AI)-assisted three-dimensional (3D) computed tomography (CT) imag...

Opportunistic Cardiovascular Risk Assessment Using Routine Head CT in the Emergency Department.

BACKGROUND: Routine noncardiac computed tomography (CT) imaging may contain information about cardiovascular risk. Head computed tomography (CTH) is a...

Digital Enabled Diagnosis System for Mammogram Images Classification Using Machine Learning.

Breast tumor is the most commonly detected tumors and remain one of the leading causes of cancer-related mortality among women worldwide. Although mam...

Computerized diagnosis of brain tumor using graph based CNN classification.

Magnetic resonance imaging (MRI) is essential in the accurate diagnosis of brain tumors so that sound treatment planning can be done, however, clinica...

Multiparametric MRI-Based Integrated Analysis of Clinical, Radiomics, Deep Learning, and Machine Learning for Predicting Tumor Proliferation and Prognosis in Locally Advanced Rectal Cancer.

RATIONALE AND OBJECTIVES: This study aimed to develop and validate a predictive model integrating clinical, radiomics, deep learning (DL), and machine...

Opportunistic Screening on Chest CT, From the AJR Special Series on Screening.

The increase in chest CT volumes affords radiologists the opportunity to systematically assess imaging biomarkers, including coronary and thoracic art...

Association Between Breast Arterial Calcifications and Increased Cardiovascular Risk: A Canadian Perspective on Clinical Implications and the Potential Role in Preventive Care.

Breast arterial calcifications (BAC) are associated with increased cardiovascular risk and have been correlated with other methods of cardiovascular r...

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...

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. Altho...

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...