Marius Linguraru is a principal investigator in the Sheikh Zayed Institute for Pediatric Surgical Innovation at Children's National Hospital in Washington, D.C. Dr. Linguraru is also professor of Radiology and Pediatrics and secondary professor of Biomedical Engineering at George Washington University. He co-founded PediaMetrix Inc., a company focused on infant well-being by creating solutions to improve the management of conditions of early childhood. Finally Dr. Linguraru is a board member of MICCAI society with a focus on early career development of young researchers. In this episode we discussed in depth about his research on pediatric health and his activities for the MICCAI society.  

Arijit Patra, a senior machine learning scientist from AstraZeneca, discusses how AI can significantly speed-up pre-clinical imaging. He also discussed his PhD thesis on continual learning for fetal ultrasound imaging.

Indranil Mallick, a practicing oncologist from India, asserts the necessity of AI in Radiation Oncology. His reflections of practicing Oncology through the two waves of the pandemic in India is a reminder, how varied the demands are of the AI-readiness of healthcare across the globe.  

Michal Rosen-Zvi, director of IBM Research's healthcare informatics, talks about her perspective on the usefulness of radiology AI during the pandemic. In particular, we discussed her recently published article On the role of artificial intelligence in medical imaging of COVID-19.

With multiple articles describing similar concerns, this is a timely episode about a very relevant topic. Further reading:

1. Hundreds of AI tools have been built to catch covid. None of them helped.

2. Common pitfalls and recommendations for using machine learning to detect and prognosticate for COVID-19 using chest radiographs and CT scans

We chatted with the radiologist Dr. Daniel Pinto dos Santos about his research in deep learning for radiology. We focused on two of his recent articles. You can read both open-access article right here:

1.  Structured report data can be used to develop deep learning algorithms: a proof of concept in ankle radiographs

2. To buy or not to buy—evaluating commercial AI solutions in radiology (the ECLAIR guidelines)  

Prof. Terry Peters tackles problems related to Image-guided interventions with a special focus on intra-operative navigation. While majority of MICCAI society is whole-heartedly embracing AI, Prof. Peters, a MICCAI fellow, voices his skepticism in some of the research directions. He cautions about proper standardization and interpretability of healthcare AI. Very important lessons for the majority of young members within MICCAI society.  

Ilkay Oksuz is an Assistant Professor in Computer Engineering Department of Istanbul Technical University. He leads the Predictive Intelligence and Medical Imaging (PIMI) Lab. He talks about his research on machine learning for medical image quality assessment with a particular focus towards Cardiac Magnetic Resonance Imaging.

Dr. Saif Afat is a radiologist, originally from Iraq, trained and actively practicing in the University Hospital Tuebingen, Germany. He will introduce the radiology at the global context beyond developed world and the role that AI can play in global Radiology.  

Dr. Andreas Bucher is a radiologist practicing at the University Hospital Frankfurt. He is also one of the spokesperson of the project RACOON and the secretary of 102nd German Radiology Congress. In this episode Dr. Bucher shares his view about AI from a radiologist's perspective who is practicing in Germany. 

Professor Dorweiler is the director of the Clinic for Vascular Surgery in the Heart Center of the Cologne University Hospital. He is interested in the digital advancement of surgeries with a special focus on 3D printing patient specific anatomies for surgical planning and teaching. In this episode, he talks about his vision of how AI can help in this endeavor.