AI Medical Compendium Journal:
Journal of medical radiation sciences

Showing 1 to 10 of 17 articles

Enhancing medical imaging education: integrating computing technologies, digital image processing and artificial intelligence.

Journal of medical radiation sciences
The rapid advancement of technology has brought significant changes to various fields, including medical imaging (MI). This discussion paper explores the integration of computing technologies (e.g. Python and MATLAB), digital image processing (e.g. i...

Deep learning in image segmentation for cancer.

Journal of medical radiation sciences
This article discusses the role of deep learning (DL) in cancer imaging, focusing on its applications for automatic image segmentation. It highlights two studies that demonstrate how U-Net- and convolutional neural networks-based architectures have i...

Artificial intelligence and radiographer preliminary image evaluation: What might the future hold for radiographers providing x-ray interpretation in the acute setting?

Journal of medical radiation sciences
In a stretched healthcare system, radiographer preliminary image evaluation in the acute setting can be a means to optimise patient care by reducing error and increasing efficiencies in the patient journey. Radiographers have shown impressive accurac...

Using a new artificial intelligence-aided method to assess body composition CT segmentation in colorectal cancer patients.

Journal of medical radiation sciences
INTRODUCTION: This study aimed to evaluate the accuracy of our own artificial intelligence (AI)-generated model to assess automated segmentation and quantification of body composition-derived computed tomography (CT) slices from the lumber (L3) regio...

Improved deep learning for automatic localisation and segmentation of rectal cancer on T2-weighted MRI.

Journal of medical radiation sciences
INTRODUCTION: The automatic segmentation approaches of rectal cancer from magnetic resonance imaging (MRI) are very valuable to relieve physicians from heavy workloads and enhance working efficiency. This study aimed to compare the segmentation accur...

Artificial Intelligence and the future of radiotherapy planning: The Australian radiation therapists prepare to be ready.

Journal of medical radiation sciences
The use of artificial intelligence (AI) solutions is rapidly changing the way radiation therapy tasks, traditionally relying on human skills, are approached by enabling fast automation. This evolution represents a paradigm shift in all aspects of the...

Automation and artificial intelligence in radiation therapy treatment planning.

Journal of medical radiation sciences
Automation and artificial intelligence (AI) is already possible for many radiation therapy planning and treatment processes with the aim of improving workflows and increasing efficiency in radiation oncology departments. Currently, AI technology is a...

The use of weather nowcasting convolutional neural network extrapolators in cardiac PET imaging.

Journal of medical radiation sciences
INTRODUCTION: Algorithms to predict short-term changes in local weather modalities have been used in meteorology for many years. These algorithms predict the temporospatial change in the movement of weather patterns such as cloud cover or precipitati...

Radiation therapist perceptions on how artificial intelligence may affect their role and practice.

Journal of medical radiation sciences
INTRODUCTION: The use of artificial intelligence (AI) has increased in medical radiation science, with advanced computing and modelling. Considering radiation therapists (RTs) perceptions of how this may affect their role is imperative, as this will ...

The transformational potential of molecular radiomics.

Journal of medical radiation sciences
Conventional radiomics in nuclear medicine involve hand-crafted and computer-assisted regions of interest. Recent developments in artificial intelligence (AI) have seen the emergence of AI-augmented segmentation and extraction of lower order traditio...