Journal of medical radiation sciences
Sep 23, 2022
INTRODUCTION: Contouring organs at risk (OARs) is a time-intensive task that is a critical part of radiation therapy. Atlas-based automatic segmentation has shown some success at reducing this time burden on practitioners; however, this method often ...
Journal of medical radiation sciences
Apr 15, 2022
INTRODUCTION: While artificial intelligence (AI) and recent developments in deep learning (DL) have sparked interest in medical imaging, there has been little commentary on the impact of AI on imaging technologists. The aim of this survey was to unde...
Journal of medical radiation sciences
Feb 14, 2021
INTRODUCTION: The integration of artificial intelligence (AI) systems into medical imaging is advancing the practice and patient care. It is thought to further revolutionise the entire field in the near future. This study explored Ghanaian radiograph...
Journal of medical radiation sciences
May 25, 2020
INTRODUCTION: To create and clinically validate knowledge-based planning (KBP) models for gynaecologic (GYN) and rectal cancer patients. Assessment of ecologic generalisability and predictive validity of conventional planning versus single calculatio...
Studies have shown that the use of artificial intelligence can reduce errors in medical image assessment. The diagnosis of breast cancer is an essential task; however, diagnosis can include 'detection' and 'interpretation' errors. Studies to reduce t...
Journal of medical radiation sciences
Nov 10, 2019
Artificial intelligence (AI) is heralded as the most disruptive technology to health services in the 21 century. Many commentary articles published in the general public and health domains recognise that medical imaging is at the forefront of these c...
Automated image contouring is showing improvements in efficiency for a number of clinical tasks in radiotherapy. While atlas segmentation has proven moderately beneficial, the next generation of algorithms based on convolutional neural networks is al...