The objective of this symposium is to present the latest advancements in computed tomography (CT), including the use of Artificial Intelligence (AI) and of photon counting CT. AI plays a pivotal role for an improved image acquisition and reconstruction process, aiding in correct patient positioning and achieving higher spatial resolution, lower dose and noise, and improved overall image quality. Photon counting pushed the boundaries of CT imaging, yielding ultra-high-resolution images with no electronic noise and inherent spectral capabilities. In this symposium, expert speakers will present these technologies, and will discuss how they can improve the outcome of CT imaging through the presentation of clinical cases acquired with state-of-the-art Canon CT technologies.
Introduction
Mathias Prokop, Nijmegen / Netherlands
Deep learning with the Aquilion ONE Insight: from acquisition to reconstruction
Russell Bull, Bournemouth / United Kingdom
To appreciate the ‘real world’ impact of deep learning CT technology in a high throughput general hospital environment
Current Clinical Experiences and Prospectives with CZT-based Photon Counting Detector CT
Martine Rémy-Jardin, Nijmegen / Netherlands
This session will summarize current results in image quality and radiation dose reduction.
The perspectives in terms of impact of this technology in clinical management will be covered.