Shuo Li: Will MICCAI 2022 be virtual?
Prof. Shuo Li is the Founding Scientific Director of Digital Imaging Group at London, Canada. He is also the general chair of MICCAI 2022 that will happen in Singapore.
Mar 01, 2022•49 min•Season 4Ep. 1
AI-ready Healthcare
Deep meaningful discussions for Knowledge dissemination and constructive arguments, with a shared mission about making Healthcare AI-ready.
I invite stakeholders such as clinicians, AI experts, industry personnel and regulatory personnel to talk about the translational aspects of AI research into patient care. Often we converse with my co-host Henry Krumb.
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Episodes
Julia Schnabel: MICCAI goes to Africa
Julia Schnabel is the Professor for Computational Imaging and AI in Medicine at TUM (TUM Liesel Beckmann Distinguished Professorship), jointly with Helmholtz Center Munich (Helmholtz Distinguished Professorship). Her research focuses on intelligent imaging solutions and computer aided evaluation, including complex motion modelling, image reconstruction, image quality control, image segmentation and classification, applied to multi-modal, quantitative and dynamic imaging. She is the co-general ch...
Dec 07, 2021•49 min•Season 3Ep. 7
Anant Madabhushi: When MICCAI scientist meets Real Clinicians
Anant Madabhushi is the Donnell Institute Professor of Biomedical Engineering at Case Western Reserve University (CWRU) in Cleveland and director of the university's Center for Computational Imaging and Personalized Diagnostics (CCIPD). He is a Research Scientist at the Louis Stokes Cleveland Veterans Administration (VA) Medical Center and has affiliate appointments both at University Hospitals and Cleveland Clinic. He holds secondary appointments in the departments of Urology, Radiology, Pathol...
Nov 30, 2021•50 min•Season 3Ep. 6
Leo Joskowicz: Shaping up AI and MICCAI
Leo Joskowicz is a pioneer of Computer Assisted Intervention and the President of MICCAI society. He is a professor at the School of Engineering and Computer Science at the Hebrew University of Jerusalem. In this episode, we explore his interest in Geometry, Shape and making MICCAI society a home to all scientists working in medical imaging problems, no matter their geographical location....
Nov 23, 2021•43 min•Season 3Ep. 5
Dan Stoyanov: Surgical Data Science 101
Dan Stoyanov is a Professor of Robot Vision in the Department of Computer Science at University College London, Director of the Wellcome/EPSRC Centre for Interventional and Surgical Sciences (WEISS), Royal Academy of Engineering Chair in Emerging Technologies and a Fellow of the Institution of Engineering and Technology. Dan is also Chief Scientific Officer at Digital Surgery Ltd and Co-Founder of Odin Medical, both companies specializing in developing AI products for interventional healthcare. ...
Nov 16, 2021•48 min•Season 3Ep. 4
John Mongan: To buy or not to buy radiology AI
John Mongan is the Associate Chair for Translational Informatics, Director of the Center for Intelligent Imaging and an Associate Professor of Clinical Radiology (Abdominal Imaging and Ultrasound section) in the Department of Radiology and Biomedical Imaging at the University of California, San Francisco. His research focuses on AI in medical imaging. In this session, we discussed the business case of Radiology AI and his Checklist for Artificial Intelligence in Medical Imaging (CLAIM) . You can...
Nov 09, 2021•56 min•Season 3Ep. 3
Qi Dou: Federated Learning for radiology
Qi Dou is an Assistant Professor from The Chinese University of Hong Kong. Her research focus is on the interdisciplinary field of medical image analysis, artificial intelligence and robotics. In this episode, we talked about the importance of Federated Learning in medical imaging and in particular, her paper Federated deep learning for detecting COVID-19 lung abnormalities in CT: a privacy-preserving multinational validation study . You can find her in Twitter @QiDou_ ....
Nov 02, 2021•50 min•Season 3Ep. 2
Andreas Maier: Known operator learning for medical imaging
Professor Andreas Maier leads the Pattern Recognition Lab of Friedrich-Alexander-Universität of Erlangen-Nürnberg. In this episode, we discussed his research on Known Operator Learning and in particular his paper Learning with known operators reduces maximum error bounds . You can find him in Twitter @maier_ak ....
Oct 26, 2021•46 min•Season 3Ep. 1
Alex Frangi: Unlocking In-silico clinical trials
Professor Alex Frangi is Diamond Jubilee Chair in Computational Medicine and Royal Academy of Engineering Chair in Emerging Technologies at the University of Leeds, Leeds, UK, with joint appointments at the School of Computing and the School of Medicine. He directs the CISTIB Center for Computational Imaging and Simulation Technologies in Biomedicine . In this episode, we discuss computational medicine, the promises of in-silico trials and his new paper In-silico trial of intracranial flow diver...
Sep 14, 2021•1 hr 3 min•Season 2Ep. 7
Yuri Tolkach: Silent Failures of Deep Digital Pathology
Dr. Yuri Tolkach , a pathologist and researcher from Uniklinik Köln, is breaking new grounds in digital pathology with probing questions about the usability of deep learning. In this episode, we discussed in great details his recent article on Quality control stress test for deep learning-based diagnostic model in digital pathology ....
Sep 07, 2021•48 min•Season 2Ep. 6
Marius Linguraru: Making babies fitter - within MICCAI and beyond
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...
Aug 31, 2021•46 min•Season 2Ep. 5
Arijit Patra: Big-Pharmas need imaging AI, and they don't know it yet!
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.
Aug 24, 2021•1 hr 2 min•Season 2Ep. 4
Indranil Mallick: Why Indian healthcare needs AI post COVID? Reflections of a Radiation Oncologist
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.
Aug 17, 2021•43 min•Season 2Ep. 3
Michal Rosen-Zvi: Underwhelming maturity of Radiology AI in COVID-19 imaging
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 pitfal...
Aug 10, 2021•47 min•Season 2Ep. 2
Daniel Pinto dos Santos: Get your radiology report structured, have some ECLAIRS!
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 )...
Aug 03, 2021•51 min•Season 2Ep. 1
Terry Peters: Beware of the nasty surprises from healthcare AI
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....
Jun 15, 2021•42 min•Season 1Ep. 7
Ilkay Oksuz: AI gives a thumbs-up to Cardiac MRI
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.
Jun 08, 2021•50 min•Season 1Ep. 6
Saif Afat: Does global radiology need AI?
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.
Jun 01, 2021•44 min•Season 1Ep. 5
Andreas Bucher: Why a German Radiologist should care about AI?
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.
May 25, 2021•42 min•Season 1Ep. 4
Bernhard Dorweiler: Intelligent training of Vascular Surgeons
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.
May 18, 2021•47 min•Season 1Ep. 3
Sandy Engelhardt: Heart bits
Sandy Engelhardt is an assistant professor in the University hospital of Heidelberg , Germany. She leads the research group of AI in Cardiovascular Medicine. In this podcast, she talks about her research of using AI for complex Cardiac Surgery as well as the AdaptOR challenge (in association with the DGM4MICCAI workshop) we are co-organizing for MICCAI 2021....
May 11, 2021•50 min•Season 1Ep. 2
Tianming Liu: Cross-talk between Neuroimaging and Neural Networks
Tianming Liu is a Distinguished Research Professor and a Full Professor of Computer Science at University of Georgia, USA. He has also been the member of MICCAI board and co-general chair of MICCAI 2019. He talks about how the cross pollination of ideas between separate sub-fields of neuroimaging and neural nets (AI) can make both fields better.
May 05, 2021•56 min•Season 1Ep. 1
Intro AI-ready Healthcare
This short recording is to introduce the purpose of AI-ready Healthcare as well as the host.
Mar 31, 2021•1 min•Ep. 1
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