Radiology

Development and deployment of a histopathology-based deep learning algorithm for patient prescreening in a clinical trial.

Accurate identification of genetic alterations in tumors, such as Fibroblast Growth Factor Receptor, is crucial for treating with targeted therapies; however, molecular testing can delay patient care due to the time and tissue required. Successful development, validation, and deployment of an AI-based, biomarker-detection algorithm could reduce screening cost and accelerate patient recruitment. He...

Machine learning models based on ultrasound and physical examination for airway assessment.

PURPOSE: To demonstrate the utility of machine learning models for predicting difficult airways using clinical and ultrasound parameters.

Deep learning-based magnetic resonance imaging analysis for chronic cerebral hypoperfusion risk.

BACKGROUND: Chronic cerebral hypoperfusion (CCH) is a frequently encountered clinical condition that poses a diagnostic challenge due to its nonspecif...

Artificial intelligence in veterinary diagnostic imaging: Perspectives and limitations.

The field of veterinary diagnostic imaging is undergoing significant transformation with the integration of artificial intelligence (AI) tools. This m...

Investigation on ultrasound images for detection of fetal congenital heart defects.

Congenital heart defects (CHD) are one of the serious problems that arise during pregnancy. Early CHD detection reduces death rates and morbidity but ...

DAU-Net: Dual attention-aided U-Net for segmenting tumor in breast ultrasound images.

Breast cancer remains a critical global concern, underscoring the urgent need for early detection and accurate diagnosis to improve survival rates amo...

Robotic Guided Interventional Radiology Set to Break Boundaries.

Transformer-CNN hybrid network for improving PET time of flight prediction.

In positron emission tomography (PET) reconstruction, the integration of time-of-flight (TOF) information, known as TOF-PET, has been a major research...

Multimodal Brain Tumor Classification Using Convolutional Tumnet Architecture.

The most common and aggressive tumor is brain malignancy, which has a short life span in the fourth grade of the disease. As a result, the medical pla...

Machine Learning Model for Predicting Axillary Lymph Node Metastasis in Clinically Node Positive Breast Cancer Based on Peritumoral Ultrasound Radiomics and SHAP Feature Analysis.

OBJECTIVE: This study seeks to construct a machine learning model that merges clinical characteristics with ultrasound radiomic analysis-encompassing ...

Clinical evaluation of deep learning-enhanced lymphoma pet imaging with accelerated acquisition.

PURPOSE: This study aims to evaluate the clinical performance of a deep learning (DL)-enhanced two-fold accelerated PET imaging method in patients wit...

Thermally Drawn-Based Microtubule Soft Continuum Robot for Cardiovascular Intervention.

Cardiovascular disease is becoming the leading cause of human mortality. In order to address this, flexible continuum robots have emerged as a promisi...

A multimodal machine learning model for predicting dementia conversion in Alzheimer's disease.

Alzheimer's disease (AD) accounts for 60-70% of the population with dementia. Mild cognitive impairment (MCI) is a diagnostic entity defined as an int...

Artificial Intelligence Quantification of Enhanced Synovium Throughout the Entire Hand in Rheumatoid Arthritis on Dynamic Contrast-Enhanced MRI.

BACKGROUND: Challenges persist in achieving automatic and efficient inflammation quantification using dynamic contrast-enhanced (DCE) MRI in rheumatoi...

Patient-specific cerebral 3D vessel model reconstruction using deep learning.

Three-dimensional vessel model reconstruction from patient-specific magnetic resonance angiography (MRA) images often requires some manual maneuvers. ...

Deep Learning Based Cystoscopy Image Enhancement.

Endoscopy image enhancement technology provides doctors with clearer and more detailed images for observation and diagnosis, allowing doctors to asse...

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 Echinococcus granulosus parasitize the livers of humans and m...

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, scanners, and acquisition parameters accounts for the hi...

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 (FPGA)-based inference machine in an ultrasound sca...

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 programmes. Artificial intelligence (AI) products that can ...