KEY LEARNINGS FROM IMAGINE 2019
The two day symposium featured world leading experts from the UK, Germany, America, Italy and Australia. The event was an excellent opportunity for attendees to learn from world leading researchers, as well as network with a range of other like-minded imaging enthusiasts. The symposium showcased current innovations in imaging, radiology and MRI technology and software; highlighting challenges and opportunities to improving health outcomes and making innovations available worldwide from world renowned leaders in the imaging field.
The Hon. Kate Jones, Minister for Innovation and Tourism Industry Development officially opened the third IMAGINE symposium on 10th September. Emanating from the Advance Queensland-funded TRI Innovation and Translation Centre in collaboration with Siemens Healthineers, the symposium and workshops had over 250 registrations including national and international researchers, clinicians, radiographers, policy makers and company executives who attended presentations and workshops and engaged in lively discussions on emerging technologies and techniques, and their desired health outcomes.
Overall, it was a stimulating and collaborative two days that demonstrated the benefits of existing research partnerships and established the foundations for new collaborations.
If you missed out on any of the sessions or wish to re-watch them, the video series below allows you to recap on both the Tuesday and Wednesday sessions. Please note that some presentations featured confidential or unpublished research and can't be published here. Please contact us directly if you have questions about any presentations not covered here.
Session 1: Imaging for Complex Surgical Planning
Session 2: The Coming of Age for Functional Imaging
Session 3: Cardiac Imaging
Session 4: Pain - Acute to Chronic and Discussion Panel
Day 2: Workshops
Data Mining Medical Information
Prostate MRI 2019: Current Status and Developing Trends in Diagnosis, Staging, Surveillance and Monitoring Post Treatment
Engaging Multi-domain Data to drive Deep Learning in Understanding Cardiovascular Disease
