Radiology

Diagnostic Accuracy of Artificial Intelligence-based Automated Detection of Diabetic Retinopathy in Routine Care Using Nonmydriatic Fundus Images: The Silesia Diabetes-Heart Project.

PURPOSE: To evaluate the diagnostic performance of a regulatory-approved (CE-marked) artificial intelligence system (RetCAD) applied to nonmydriatic color fundus photographs for diabetic retinopathy (DR) screening in routine clinical care. METHODS: This was a prospective single-center observational diagnostic accuracy study including adults with diabetes who underwent nonmydriatic fundus imaging b...

Paddy leaf disease detection and classification using improved Gorilla Troops optimized YOLO-V8 network.

Paddy leaf disease (PLD) detection has grown more difficult, yet early detection might prevent significant losses due to decreased crop yield. However, existing models struggle to accurately classify diseases under difficult circumstances like intricate backgrounds, fluctuating lighting, and overlapping leaves. Additionally, existing models do not incorporate efficient optimization strategies, lea...

A cloud-edge adaptive lightweight network with dynamic inference enables real-time ultrasound image segmentation.

Ultrasound image segmentation plays an important role in clinical diagnosis, but existing deep learning methods struggle to balance accuracy and effic...

An attention-guided multimodal deep learning framework by integrating CT-PET imaging and clinical data for lung cancer detection.

The proposed multi-modal deep learning system for lung cancer diagnosis and characterisation uses structural (CT), functional (PET), and clinical (EHR...

Blurred and occluded target recognition in terahertz images based on improved YOLOv5.

Terahertz (THz) imaging technology is widely used in applications such as security screening, radar detection, and biomedical applications. Neverthele...

Scalable Left Ventricular ROI Annotation for Stress Perfusion Cardiac MRI using Deep Learning with Visual Refinement.

Accurate extraction of the left ventricular (LV)-centred region of interest (ROI) in stress perfusion cardiovascular magnetic resonance (CMR) remains ...

Nonlinear hydrothermal associations between coupled landscape ecological risk and resilience in a major grain-producing region of China.

In major grain-producing regions, hydrothermal processes are critical for regulating ecosystem stability. However, the long-term coupled dynamics betw...

Artificial Intelligence in Veterinary Diagnostic Imaging: A Narrative Review of the State of the Art and its Applications.

Artificial intelligence (AI) is transforming veterinary diagnostic imaging, improving the accuracy, speed, and efficiency of complex data analysis. Th...

Altered thalamic subregional connectivity with default mode and frontoparietal networks in adolescents with depression.

BACKGROUND: The thalamus plays a pivotal role in the pathophysiology of adolescent depression, with its subregions showing functional heterogeneity. A...

Comparative diagnostic accuracy of image-enhanced endoscopy modalities and artificial intelligence-assisted endoscopy for gastric intestinal metaplasia and gastric dysplasia: protocol for a systematic review and diagnostic test network meta-analysis.

INTRODUCTION: Gastric intestinal metaplasia (GIM) and gastric dysplasia are critical precursors in the Correa cascade of gastric carcinogenesis. Altho...

Simulating the Dedifferentiation Process of Thyroid Cancer: Insights from Mouse Models and Ultrasound Imaging.

RATIONALE AND OBJECTIVE: Anaplastic thyroid carcinoma (ATC) may arise from the progression of differentiated thyroid cancers, but the mechanisms are n...

High angular resolution diffusion imaging of neurodevelopment in children through data creation with deep learning.

High-angular resolution diffusion imaging (HARDI) is an advanced method for characterizing brain microstructure and function. However, HARDI is time-c...

Shifting from black box decisions to informed decision-making in using artificial intelligence to analyze prostate MRI.

Prostate magnetic resonance imaging (MRI) is central to the detection and localization of clinically significant prostate cancers. However, its interp...

Deep learning classification of significant prostate cancer on MRI: a systematic review and meta-analysis.

Deep learning (DL) image analysis of prostate MRI can be integrated into the prostate cancer diagnostic pathway to improve biopsy decision making, red...

Associations between body composition and radiotherapy-related side-effects and health-related quality of life in patients with prostate or lung cancer: sub-analysis of the REQUITE trial.

BACKGROUND: Body composition is emerging as a prognostic biomarker in cancer and may be associated with treatment tolerance, side-effects, and health-...

Interstitial lung disease pattern recognition on full high resolution computed tomography volume: Development and evaluation of a decision-support tool for less-experimented radiologists.

PURPOSE: The purpose of this study was to develop an artificial intelligence (AI) tool to assist recognition of three major interstitial lung disease ...

Deep learning and red deer optimiser for automatic cardiovascular disease identification on magnetic resonance images.

Magnetic Resonance Imaging (MRI) is a non-invasive imaging method that can give detailed visualization of the cardiac structures and blood flow, which...

Topology-decoupled end-to-end framework for brain tumor MRI detection: boundary-preserving feature flow and inter-channel correlation distillation.

Early and accurate detection of brain tumors is clinically valuable for improving prognosis and guiding treatment. Existing deep-learning methods for ...

MRI-based quantification of intratumoral heterogeneity for predicting recurrence risk in ER+/HER2- breast cancer.

OBJECTIVES: The need for a cost-effective, rapid, and increasingly accessible alternative to the 21-gene assay prompted this study, which developed a ...

Ultrasound-based assessment of peri-implant mucosal thickness: an ex vivo comparative study with artificial intelligence-assisted image analysis.

BACKGROUND: Mucosal thickness (MT) is a key factor influencing peri-implant soft-tissue response and outcomes in dental implantology. This ex vivo stu...