Radiology

Diagnostic Performance of Artificial Intelligence in Detection of Hepatocellular Carcinoma: A Meta-analysis.

Due to the increasing interest in the use of artificial intelligence (AI) algorithms in hepatocellul...

Evaluation of the performance of both machine learning models using PET and CT radiomics for predicting recurrence following lung stereotactic body radiation therapy: A single-institutional study.

PURPOSE: Predicting recurrence following stereotactic body radiotherapy (SBRT) for non-small cell lu...

Multitask deep learning for prediction of microvascular invasion and recurrence-free survival in hepatocellular carcinoma based on MRI images.

BACKGROUND AND AIMS: Accurate preoperative prediction of microvascular invasion (MVI) and recurrence...

Classification of multi-feature fusion ultrasound images of breast tumor within category 4 using convolutional neural networks.

BACKGROUND: Breast tumor is a fatal threat to the health of women. Ultrasound (US) is a common and e...

Impact of artificial intelligence arrhythmia mapping on time to first ablation, procedure duration, and fluoroscopy use.

INTRODUCTION: Artificial intelligence (AI) ECG arrhythmia mapping provides arrhythmia source localiz...

Advanced hybrid attention-based deep learning network with heuristic algorithm for adaptive CT and PET image fusion in lung cancer detection.

Lung cancer is one of the most deadly diseases in the world. Lung cancer detection can save the pati...

Enhancing the fairness of AI prediction models by Quasi-Pareto improvement among heterogeneous thyroid nodule population.

Artificial Intelligence (AI) models for medical diagnosis often face challenges of generalizability ...

Coupling speckle noise suppression with image classification for deep-learning-aided ultrasound diagnosis.

. During deep-learning-aided (DL-aided) ultrasound (US) diagnosis, US image classification is a foun...

Towards precision medicine in breast imaging: A novel open mammography database with tailor-made 3D image retrieval for AI and teaching.

This project addresses the global challenge of breast cancer, particularly in low-resource settings,...

Predicting microvascular invasion in hepatocellular carcinoma with a CT- and MRI-based multimodal deep learning model.

PURPOSE: To investigate the value of a multimodal deep learning (MDL) model based on computed tomogr...

Deep Learning for Automatic Gross Tumor Volumes Contouring in Esophageal Cancer Based on Contrast-Enhanced Computed Tomography Images: A Multi-Institutional Study.

PURPOSE: To develop and externally validate an automatic artificial intelligence (AI) tool for delin...

Feasibility of the application of deep learning-reconstructed ultra-fast respiratory-triggered T2-weighted imaging at 3 T in liver imaging.

OBJECTIVE: The evaluate the feasibility of a novel deep learning-reconstructed ultra-fast respirator...

Magnetic resonance imaging-based deep learning imaging biomarker for predicting functional outcomes after acute ischemic stroke.

PURPOSE: Clinical risk scores are essential for predicting outcomes in stroke patients. The advancem...

Comment on "Predicting the risk stratification of gastrointestinal stromal tumors using machine learning-based ultrasound radiomics".

Machine learning-based medical imaging diagnosis in patients with temporomandibular disorders: a diagnostic test accuracy systematic review and meta-analysis.

OBJECTIVES: Temporomandibular disorders (TMDs) are the second most common musculoskeletal condition ...

Deep Learning Imaging Reconstruction Algorithm for Carotid Dual Energy CT Angiography: Opportunistic Evaluation of Cervical Intervertebral Discs-A Preliminary Study.

Thus, the aim of this study is to evaluate the performance of deep learning imaging reconstruction (...

Applications of artificial intelligence in biliary tract cancers.

Biliary tract cancers are malignant neoplasms arising from bile duct epithelial cells. They include ...

Deep learning-based metastasis detection in patients with lung cancer to enhance reproducibility and reduce workload in brain metastasis screening with MRI: a multi-center study.

OBJECTIVES: To assess whether a deep learning-based system (DLS) with black-blood imaging for brain ...

Design and testing of ultrasound probe adapters for a robotic imaging platform.

Medical imaging-based triage is a critical tool for emergency medicine in both civilian and military...

A narrative review on the application of artificial intelligence in renal ultrasound.

Kidney disease is a serious public health problem and various kidney diseases could progress to end-...

Synthesis of gadolinium-enhanced glioma images on multisequence magnetic resonance images using contrastive learning.

BACKGROUND: Gadolinium-based contrast agents are commonly used in brain magnetic resonance imaging (...