Radiology

Deep Learning Based Cystoscopy Image Enhancement.

Endoscopy image enhancement technology provides doctors with clearer and more detailed images for o...

Clinical Application of Artificial Intelligence in the Ultrasound Classification of Hepatic Cystic Echinococcosis.

Hepatic cystic echinococcosis (HCE) is a zoonotic disease that occurs when the larvae of Echinococcu...

Probability maps for deep learning-based head and neck tumor segmentation: Graphical User Interface design and test.

BACKGROUND: The different tumor appearance of head and neck cancer across imaging modalities, scanne...

Arterial Distension Monitoring Scheme Using FPGA-Based Inference Machine in Ultrasound Scanner Circuit System.

This paper presents an arterial distension monitoring scheme using a field-programmable gate array (...

Liability of Health Professionals Using Sensors, Telemedicine and Artificial Intelligence for Remote Healthcare.

In the last few decades, there has been an ongoing transformation of our healthcare system with larg...

Protocol for evaluating the fitness for purpose of an artificial intelligence product for radiology reporting in the BreastScreen New South Wales breast cancer screening programme.

INTRODUCTION: Radiologist shortages threaten the sustainability of breast cancer screening programme...

Machine learning-based model for predicting tumor recurrence after interventional therapy in HBV-related hepatocellular carcinoma patients with low preoperative platelet-albumin-bilirubin score.

INTRODUCTION: This study aimed to develop a prognostic nomogram for predicting the recurrence-free s...

The potential and pitfalls of ChatGPT in radiology.

DTDO: Driving Training Development Optimization enabled deep learning approach for brain tumour classification using MRI.

A brain tumour is an abnormal mass of tissue. Brain tumours vary in size, from tiny to large. Moreov...

Deep-learning features based on F18 fluorodeoxyglucose positron emission tomography/computed tomography (F-FDG PET/CT) to predict preoperative colorectal cancer lymph node metastasis.

AIM: The objective of this study was to create and authenticate a prognostic model for lymph node me...

Enhanced reliability and time efficiency of deep learning-based posterior tibial slope measurement over manual techniques.

PURPOSE: Multifaceted factors contribute to inferior outcomes following anterior cruciate ligament (...

Deep learning nomogram for predicting neoadjuvant chemotherapy response in locally advanced gastric cancer patients.

PURPOSE: Developed and validated a deep learning radiomics nomogram using multi-phase contrast-enhan...

Systematic review and meta-analysis of deep learning applications in computed tomography lung cancer segmentation.

BACKGROUND: Accurate segmentation of lung tumors on chest computed tomography (CT) scans is crucial ...

Pituitary MRI Radiomics Improves Diagnostic Performance of Growth Hormone Deficiency in Children Short Stature: A Multicenter Radiomics Study.

RATIONALE AND OBJECTIVES: To develop an efficient machine-learning model using pituitary MRI radiomi...

Preliminary study on the ability of the machine learning models based on F-FDG PET/CT to differentiate between mass-forming pancreatic lymphoma and pancreatic carcinoma.

PURPOSE: The objective of this study was to preliminarily assess the ability of metabolic parameters...

An effective ensemble learning approach for classification of glioma grades based on novel MRI features.

The preoperative diagnosis of brain tumors is important for therapeutic planning as it contributes t...

Evaluating the Diversity and Representation of Artificial Intelligence-Generated Images of Radiologists: An Observational Study.

nBEST: Deep-learning-based non-human primates Brain Extraction and Segmentation Toolbox across ages, sites and species.

Accurate processing and analysis of non-human primate (NHP) brain magnetic resonance imaging (MRI) s...

Deep learning of mammogram images to reduce unnecessary breast biopsies: a preliminary study.

BACKGROUND: Patients with a Breast Imaging Reporting and Data System (BI-RADS) 4 mammogram are curre...

AI for interpreting screening mammograms: implications for missed cancer in double reading practices and challenging-to-locate lesions.

Although the value of adding AI as a surrogate second reader in various scenarios has been investiga...

Performance of an ultra-fast deep-learning accelerated MRI screening protocol for prostate cancer compared to a standard multiparametric protocol.

OBJECTIVES: To establish and evaluate an ultra-fast MRI screening protocol for prostate cancer (PCa)...