Transatlantic UCSF/CAU Webinar on Artificial Intelligence
Date
Join Dr. Valentina Pedoia and Dr. Claus-C. Glüer, as they host the Transatlantic UCSF/CAU Webinar on Artificial Intelligence in Biomedical Imaging: Fighting the Pandemic with Federated Learning
Thursday, 29 April 2021 at 08:30AM-10:30AM
Hosts:
Dr. Claus-C. Glüer, Section Biomedical Imaging,
Department of Radiology and Neuroradiology, University Medical Center Schleswig-Holstein and Christian-Albrechts-University, Kiel, Germany
Dr. Valentina Pedoia, Center for Intelligent Imaging
Department of Radiology & Biomedical Imaging, University of California, San Francisco, USA
Presentations:
Collaborative Learning in Medical Imaging: Opportunities and Challenges
Dr. Jayashree Kalpathy-Cramer, Associate Professor of Radiology at MGH/Harvard Medical School
(0830AM UCSF/17:30 Kiel)
Joint Imaging Platform for Federated Clinical Data Analytics
Dr. Marco Nolden, Senior scientist, Division of Medical Image Computing of the German Cancer Research Center in Heidelberg
(9:30AMUCSF/18:30 Kiel)
Lessons Learned from Real-World Federated Learning: Experience with COVID-19 Modeling at UCSF
Dr. Jason Crane, Director Computational Core and Dr. Pablo Damasceno, PhD, Machine Learning Specialist, UCSF
(10:00AM UCSF/1900 Kiel)
Event Registration: LINK
2921 America/Los_Angeles publicType
Join Dr. Valentina Pedoia and Dr. Claus-C. Glüer, as they host the Transatlantic UCSF/CAU Webinar on Artificial Intelligence in Biomedical Imaging: Fighting the Pandemic with Federated Learning
Thursday, 29 April 2021 at 08:30AM-10:30AM
Hosts:
Dr. Claus-C. Glüer, Section Biomedical Imaging,
Department of Radiology and Neuroradiology, University Medical Center Schleswig-Holstein and Christian-Albrechts-University, Kiel, Germany
Dr. Valentina Pedoia, Center for Intelligent Imaging
Department of Radiology & Biomedical Imaging, University of California, San Francisco, USA
Presentations:
Collaborative Learning in Medical Imaging: Opportunities and Challenges
Dr. Jayashree Kalpathy-Cramer, Associate Professor of Radiology at MGH/Harvard Medical School
(0830AM UCSF/17:30 Kiel)
Joint Imaging Platform for Federated Clinical Data Analytics
Dr. Marco Nolden, Senior scientist, Division of Medical Image Computing of the German Cancer Research Center in Heidelberg
(9:30AMUCSF/18:30 Kiel)
Lessons Learned from Real-World Federated Learning: Experience with COVID-19 Modeling at UCSF
Dr. Jason Crane, Director Computational Core and Dr. Pablo Damasceno, PhD, Machine Learning Specialist, UCSF
(10:00AM UCSF/1900 Kiel)
Event Registration: LINK
Speakers
Dr. Jayashree Kalpathy-Cramer is an Associate Professor of Radiology at MGH/Harvard Medical School. She co-directs the QTIM lab and the Center for Machine Learning at the Athinoula A. Martinos Center for Biomedical Imaging. Her lab works at the intersection of machine learning and healthcare with a focus on medical imaging. Please see https://qtim-lab.github.io/ for more details.
Dr. Marco Nolden is a computer scientist working on software and algorithms for medical imaging research, with a focus on translation and open-source technologies. He is a senior scientist at the Division of Medical Image Computing (Head: Klaus Maier-Hein) of the German Cancer Research Center in Heidelberg, the largest biomedical research center in Germany with more than 3000 employees.
Dr. Jason Crane is Director of Computational Core for the Center for Intelligent Imaging in the Department of Radiology and Biomedical Imaging responsible for developing and managing state-of-the-art computational hardware and software to enable cutting-edge biomedical imaging research and clinical translation, with the most advanced CPU and GPU computing architecture, large-scale data storage and interoperability tools, and software stack for both traditional image analysis and state-of-the-art machine learning techniques.
Dr. Pablo Damasceno has over 15 years of experience in high-performance computing and has worked on a diverse range of problems, from biochemical engineering to mathematics to neuroscience. As a staff scientist at the Center for Intelligent Imaging at the UC San Francisco, he helps train, evaluate, and deploy deep learning applications to improve clinical care.