Life Science Meeting – Medical Imaging: latest developments and trends
What progress has been made in the field of medical imaging in the recent past?
In this webinar, LifeScienceNet Düsseldorf and BioRiver – Life Science im Rheinland e.V. will give a focused insight into the future of medical imaging at the upcoming Life Science Meeting “Medical Imaging: Latest developments and trends” on May 12, 2022 from 4:00 – 6:00 PM (CET).
Prof. Paul J.A. Borm from Nano4Imaging GmbH in Düsseldorf, Germany, and Prof. Dr. Bernhard Kainz from the Department of Artificial Intelligence in Biomedical Engineering at Friedrich Alexander University Erlangen-Nürnberg, Germany, share their knowledge and latest findings on developments in magnetic resonance imaging (MRI) in endovascular procedures and the use of artificial intelligence (AI) in medical imaging.
Participation in the webinar is open to all interested parties and is free of charge, registration in advance is requested. The meeting will be held in English.
Dr. Thomas Heck, Life Science Center Düsseldorf
Why are you not using MRI for your endovascular interventions?
Prof. Paul J.A. Borm, Co-Founder and CTO, Nano4Imaging GmbH, Düsseldorf, formerly HHU, Institute for Toxicology at the Medical Faculty
Successful applications of artifical intelligence in medical imaging
Prof. Dr. Bernhard Kainz, Institute for Image Data Exploration and Analysis in the Department Artificial Intelligence in Biomedical Engineering, Friedrich-Alexander-Universität Erlangen-Nürnberg
A home game this time. From our offices at the Dusseldorf Life Science Centres we are proud to co-organize a webinar on Advances on Medical Imaging using MRI and also include some time for the role of artificial intelligence in the proces of medical imaging. What progress has been made in the field of medical imaging in the recent past? LifeScienceNet Düsseldorf and BioRiver-Life Science im Rheinland e.V. will give an insight into the upcoming online life science meeting “Medical Imaging: Latest developments and trends” on 12 May 2022 from 16.00 – 18.00.
Participation in the webinar is open to all interested parties and is free of charge. The meeting will be held in English.
Optimised passive marker device visibility and automatic marker detection for 3-T MRI-guided endovascular interventions: a pulsatile flow phantom study
Passive paramagnetic markers on magnetic resonance imaging (MRI)-compatible endovascular devices induce susceptibility artifacts, enabling MRI-visibility and real-time MRI-guidance. Optimised visibility is crucial for automatic detection and device tracking but depends on MRI technical parameters and marker characteristics. We assessed marker visibility and automatic detection robustness for varying MRI parameters and marker characteristics in a pulsatile flow phantom. Marker visibility was sufficient and a large range of artifact sizes was generated by adjusting TE and IONP concentration. Deep learning-based marker detection was feasible but performance decreased for altered MR parameters. These factors should be considered to optimise device visibility and ensure reliable automatic marker detectability in MRI-guided endovascular interventions.
This video was used in our 2021 EU Accelerator application to share N4I vision on use of machine learning in MRI marker recognition and enabling new clinical procedures. Statements from members in our medical advisory board are included. Courtesy Sparkbox-Haarlem (NL)
It has always been assumed but never proven that iCMR gives an incremental value by providing more accurate flow quantification. In Dallas Childrens/UTSW interventional MRI is now standard procedure in young adults. Therefore they conducted a study in 30 patients with CHD and conducted both right and left heart cath at a success rate of multiple data points of 98 %. In doing the study the Dallas team validates hemodynamic measurements obtained via iCMR and showed that iCMR-derived flows have considerably higher test–retest reliability for Qs. iCMR evaluations allow for more reproducible hemodynamic assessments in the CHD population.