AIMC Topic: Diagnostic Imaging

Clear Filters Showing 451 to 460 of 978 articles

Electromechanical Wave Imaging With Machine Learning for Automated Isochrone Generation.

IEEE transactions on medical imaging
Standard Electromechanical Wave Imaging isochrone generation relies on manual selection of zero-crossing (ZC) locations on incremental strain curves for a number of pixels in the segmented myocardium for each echocardiographic view and patient. When ...

Deep Learning-Based High-Frequency Ultrasound Skin Image Classification with Multicriteria Model Evaluation.

Sensors (Basel, Switzerland)
This study presents the first application of convolutional neural networks to high-frequency ultrasound skin image classification. This type of imaging opens up new opportunities in dermatology, showing inflammatory diseases such as atopic dermatitis...

A proof of concept study for machine learning application to stenosis detection.

Medical & biological engineering & computing
This proof of concept (PoC) assesses the ability of machine learning (ML) classifiers to predict the presence of a stenosis in a three vessel arterial system consisting of the abdominal aorta bifurcating into the two common iliacs. A virtual patient ...

Artificial intelligence-based hybrid deep learning models for image classification: The first narrative review.

Computers in biology and medicine
BACKGROUND: Artificial intelligence (AI) has served humanity in many applications since its inception. Currently, it dominates the imaging field-in particular, image classification. The task of image classification became much easier with machine lea...

Artificial intelligence: The opinions of radiographers and radiation therapists in Ireland.

Radiography (London, England : 1995)
INTRODUCTION: Implementation of Artificial Intelligence (AI) into medical imaging is much debated. Diagnostic Radiographers (DRs) and Radiation Therapists (RTTs) are at the forefront of this technological leap, thus an understanding of their views, i...

Application of Radiomics and Artificial Intelligence for Lung Cancer Precision Medicine.

Cold Spring Harbor perspectives in medicine
Medical imaging is the standard-of-care for early detection, diagnosis, treatment planning, monitoring, and image-guided interventions of lung cancer patients. Most medical images are stored digitally in a standardized Digital Imaging and Communicati...

Ensuring Adequate Development and Appropriate Use of Artificial Intelligence in Pediatric Medical Imaging.

AJR. American journal of roentgenology
Of over 100 FDA-cleared artificial intelligence (AI) tools for triage, detection, or diagnosis in medical imaging, only one is cleared for use in children. Thus, children may be unable to benefit from the advances that AI provides to adults. Furtherm...

Deep reinforcement learning in medical imaging: A literature review.

Medical image analysis
Deep reinforcement learning (DRL) augments the reinforcement learning framework, which learns a sequence of actions that maximizes the expected reward, with the representative power of deep neural networks. Recent works have demonstrated the great po...

Adoption of New Technologies: Artificial Intelligence.

Gastrointestinal endoscopy clinics of North America
Over the past decade, artificial intelligence (AI) has been broadly applied to many aspects of human life, with recent groundbreaking successes in facial recognition, natural language processing, autonomous driving, and medical imaging. Gastroenterol...

Development of a smartphone-based lateral-flow imaging system using machine-learning classifiers for detection of Salmonella spp.

Journal of microbiological methods
Salmonella spp. are a foodborne pathogen frequently found in raw meat, egg products, and milk. Salmonella is responsible for numerous outbreaks, becoming a frequent major public-health concern. Many studies have recently reported handheld and rapid d...