AI Medical Compendium Journal:
Radiography (London, England : 1995)

Showing 21 to 30 of 53 articles

Impact of intelligent virtual and AI-based automated collimation functionalities on the efficiency of radiographic acquisitions.

Radiography (London, England : 1995)
INTRODUCTION: Intelligent virtual and AI-based collimation functionalities have the potential to enable an efficient workflow for radiographers, but the specific impact on clinical routines is still unknown. This study analyzes primarily the influenc...

Predictive value of magnetic resonance imaging diffusion parameters using artificial intelligence in low-and intermediate-risk prostate cancer patients treated with stereotactic ablative radiotherapy: A pilot study.

Radiography (London, England : 1995)
INTRODUCTION: To investigate the predictive value of the pre-treatment diffusion parameters of diffusion-weighted magnetic resonance imaging (DW-MRI) using artificial intelligence (AI) for prostate-specific antigen (PSA) response in patients with low...

Nordic radiographers' and students' perspectives on artificial intelligence - A cross-sectional online survey.

Radiography (London, England : 1995)
INTRODUCTION: The integration of artificial intelligence (AI) into the domain of radiography holds substantial potential in various aspects including workflow efficiency, image processing, patient positioning, and quality assurance. The successful im...

Improving the detection of hypo-vascular liver metastases in multiphase contrast-enhanced CT with slice thickness less than 5 mm using DenseNet.

Radiography (London, England : 1995)
INTRODUCTION: Thinner slices are more susceptible in detecting small lesions but suffer from higher statistical fluctuation. This work aimed to reduce image noise in multiphase contrast-enhanced CT reconstructed with slice thickness thinner than the ...

A scoping review of educational programmes on artificial intelligence (AI) available to medical imaging staff.

Radiography (London, England : 1995)
INTRODUCTION: Medical imaging is arguably the most technologically advanced field in healthcare, encompassing a range of technologies which continually evolve as computing power and human knowledge expand. Artificial Intelligence (AI) is the next fro...

Assessment of inspiration and technical quality in anteroposterior thoracic radiographs using machine learning.

Radiography (London, England : 1995)
INTRODUCTION: Chest radiographs are the most performed radiographic procedure, but suboptimal technical factors can impact clinical interpretation. A deep learning model was developed to assess technical and inspiratory adequacy of anteroposterior ch...

Considerations for environmental sustainability in clinical radiology and radiotherapy practice: A systematic literature review and recommendations for a greener practice.

Radiography (London, England : 1995)
INTRODUCTION: Environmental sustainability (ES) in healthcare is an important current challenge in the wider context of reducing the environmental impacts of human activity. Identifying key routes to making clinical radiology and radiotherapy (CRR) p...

ChatGPT in medical imaging higher education.

Radiography (London, England : 1995)
INTRODUCTION: Academic integrity among radiographers and nuclear medicine technologists/scientists in both higher education and scientific writing has been challenged by advances in artificial intelligence (AI). The recent release of ChatGPT, a chatb...

Collimation border with U-Net segmentation on chest radiographs compared to radiologists.

Radiography (London, England : 1995)
INTRODUCTION: Chest Radiography (CXR) is a common radiographic procedure. Radiation exposure to patients should be kept as low as reasonably achievable (ALARA), and monitored continuously as part of quality assurance (QA) programs. One of the most ef...