Radiology

Construction of an artificially intelligent model for accurate detection of HCC by integrating clinical, radiological, and peripheral immunological features.

BACKGROUND: Integrating comprehensive information on hepatocellular carcinoma (HCC) is essential to ...

AI-ECG Supported Decision-Making for Coronary Angiography in Acute Chest Pain: The QCG-AID Study.

This pilot study evaluates an artificial intelligence (AI)-assisted electrocardiography (ECG) analys...

Deep learning-based breast MRI for predicting axillary lymph node metastasis: a systematic review and meta-analysis.

BACKGROUND: To perform a systematic review and meta-analysis that assesses the diagnostic performanc...

Effectiveness and clinical impact of using deep learning for first-trimester fetal ultrasound image quality auditing.

BACKGROUND: Regular auditing of ultrasound images is required to maintain quality; however, manual a...

Gd-EOB-DTPA-enhanced MRI radiomics and deep learning models to predict microvascular invasion in hepatocellular carcinoma: a multicenter study.

BACKGROUND: Microvascular invasion (MVI) is an important risk factor for early postoperative recurre...

Automatic Human Embryo Volume Measurement in First Trimester Ultrasound From the Rotterdam Periconception Cohort: Quantitative and Qualitative Evaluation of Artificial Intelligence.

BACKGROUND: Noninvasive volumetric measurements during the first trimester of pregnancy provide uniq...

Deep Learning and Radiomics Discrimination of Coronary Chronic Total Occlusion and Subtotal Occlusion using CTA.

RATIONALE AND OBJECTIVES: Coronary chronic total occlusion (CTO) and subtotal occlusion (STO) pose d...

Prediction of BRAF and TERT status in PTCs by machine learning-based ultrasound radiomics methods: A multicenter study.

BACKGROUND: Preoperative identification of genetic mutations is conducive to individualized treatmen...

Image normalization techniques and their effect on the robustness and predictive power of breast MRI radiomics.

BACKGROUND AND PURPOSE: Radiomics analysis has emerged as a promising approach to aid in cancer diag...

Improving realism in abdominal ultrasound simulation combining a segmentation-guided loss and polar coordinates training.

BACKGROUND: Ultrasound (US) simulation helps train physicians and medical students in image acquisit...

Multimodal contrastive learning for enhanced explainability in pediatric brain tumor molecular diagnosis.

Despite the promising performance of convolutional neural networks (CNNs) in brain tumor diagnosis f...

Ultrasound-based deep learning to differentiate salivary gland tumors.

OBJECTIVE: Accurate preoperative diagnosis is essential for selecting appropriate surgical intervent...

Development and validation of a nomogram for predicting bone marrow involvement in lymphoma patients based on F-FDG PET radiomics and clinical factors.

OBJECTIVE: This study aimed to develop and validate a nomogram combining F-FDG PET radiomics and cli...

Deep Learning Based on Ultrasound Images Differentiates Parotid Gland Pleomorphic Adenomas and Warthin Tumors.

Exploring the clinical significance of employing deep learning methodologies on ultrasound images fo...

Internal Target Volume Estimation for Liver Cancer Radiation Therapy Using an Ultra Quality 4-Dimensional Magnetic Resonance Imaging.

PURPOSE: Accurate internal target volume (ITV) estimation is essential for effective and safe radiat...

In reply to the Letter to Editor regarding Comment on: Role of artificial intelligence in magnetic resonance imaging-based detection of temporomandibular joint disorder: a systematic review.

Comment On: "Role of artificial intelligence in magnetic resonance imaging-based detection of temporomandibular joint disorder: a systematic review".

Guided ultrasound acquisition for nonrigid image registration using reinforcement learning.

We propose a guided registration method for spatially aligning a fixed preoperative image and untrac...

Artificial intelligence for tumor [F]FDG-PET imaging: Advancement and future trends-part I.

The advent of sophisticated image analysis techniques has facilitated the extraction of increasingly...

Advanced convolutional neural network with attention mechanism for Alzheimer's disease classification using MRI.

This paper introduces a novel convolutional neural network model with an attention mechanism to adva...

AI and Machine Learning for Precision Medicine in Acute Pancreatitis: A Narrative Review.

Acute pancreatitis (AP) presents a significant clinical challenge due to its wide range of severity,...