IOMP Webinar on Machine Learning

Understanding the limitations of current CT dosimetry and the way forward

Monday, July 20
Time: 12 noon -1:00 GMT

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Register here: https://www.iomp.org/iomp-school-webinar-2

Organizer: Prof. Arun Chougule
IOMP School webinar Organiser
Senior Professor & Head
Department of radiological Physics
SMS Medical College & hospitals, JAIPUR, INDIA

Speaker: Prof. John Damilakis  
Chairman, Department of Medical Physics
School of Medicine
University of Crete, Iraklion, Crete, Greece

Moderator: Prof. Eva Bezak
Professor of Medical Radiation
University of South Australia
Adelaide, Australia

Prof. John Damilakis, PhD

John Damilakis is professor and chairman at the Department of Medical Physics, School of Medicine, University of Crete and director of the Department of Medical Physics of the University Hospital of Heraklion, Crete, Greece. He is Vice President and President-elect of the ‘International Organization for Medical Physics’ (IOMP), Immediate Past President of the ‘European Alliance for Medical Radiation Protection Research’ (EURAMED), Past President of the ‘European Federation of Organizations for Medical Physics’ (EFOMP) and Past President of the ‘Hellenic Association of Medical Physics’. Prof. Damilakis is a member of 2 ICRP Task Groups (TG 108 and TG 109) and member of the steering committee of the ‘EuroSafe Imaging’ of the ESR. He is coordinator or an active research member of several European and national projects. As a Visiting Professor he has given lectures on dosimetry and radiation protection in Boston University, USA. His publications have been focused on medical radiation protection and dosimetry. He is editor of 2 books published by the IOP Publishing and Springer-Verlag and co-author of 2 chapters in books published by Springer and Academic Press. Number of publications in PubMed: 213, h-index 45 (Google Scholar). Many of these publications are in leading journals such as Medical Physics, Physics in Medicine and Biology, Radiology, Investigative Radiology and European Radiology. John Damilakis has given more than 300 invited presentations in national and international conferences including ECR, RSNA, AAPM, IAEA, ICRP, IOMP and EFOMP meetings. He has received 10 awards for his work.



PAST WEBINARS


Webinar Topics:

  1. What is radiomics? What is its relationship to machine learning and deep learning? Arman Rahmin, UBC, Vancouver, Canada
  2. Potential value and pitfalls of machine learning for radiomics applications by Mathieu Hatt, INSERM, France

9 July 2020, 12 noon – 1:00 GMT

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Register here: https://www.iomp.org/iomp-school-webinar-4

Organizer: Prof. Madan Rehani, President, IOMP

Speakers:

Arman Rahmin is Associate Professor of Radiology and Physics at the University of British Columbia (UBC), as well as Senior Scientist and Provincial Medical Imaging Physicist at BC Cancer, Vancouver, Canada. He received his PhD in medical imaging physics at UBC. Following doctoral studies, he was recruited by Johns Hopkins University (JHU) to lead the high-resolution brain PET imaging physics program and to pursue research at the JHU Department of Radiology. In 2018, he was recruited back to Vancouver, where he leads the provincial molecular imaging and therapy physics program and his lab (rahmimlab.com) pursues research in tomographic image generation and analysis. He has published a book, over 130 journal articles and 280 conference proceeding papers/abstracts, and delivered more than 90 invited lectures worldwide. He was president (2018-2019) of the Physics, Instrumentation and Data Sciences (PIDS) Council of the Society of Nuclear Medicine & Molecular Imaging (SNMMI), and was awarded the John S. Laughlin Young Scientist Award by the American Association of Physicists in Medicine (AAPM) in 2016

Mathieu Hatt is a computer scientist. He received his PhD in 2008 and his habilitation to supervise research in 2012. His main skills and expertise lie in radiomics, from automated image segmentation to features extraction, as well as machine (deep) learning methods, for PET/CT, MRI and CT modalities. He is an elected member of the EANM physics committee, the SNMMI physics, data science and instrumentation council board of directors, and the IEEE nuclear medical and imaging sciences council.


Webinar Topic: Artificial Intelligence in Medical Physics and Medicine: Challenges and Opportunities

23 June 2020, 12 noon – 1:00 GMT

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Register here: https://www.iomp.org/iomp-school-webinar-3

Moderator: Prof. Madan Rehani, President, IOMP

Speaker:

Prof. Steve Jiang, Ph.D.
Vice Chair, Department of Radiation Oncology;
Director, Division of Medical Physics and Engineering
University of Texas Southwestern Medical Center
USA

Dr. Steve Jiang received his Ph.D. in Medical Physics from Medical College of Ohio in 1998. After completing his postdoctoral training at Stanford University, he joined Massachusetts General Hospital and Harvard Medical School in 2000 as an Assistant Professor of Radiation Oncology. In 2007, Dr. Jiang was recruited to University of California San Diego as a tenured Associate Professor to build Center for Advanced Radiotherapy Technologies, for which he was the founding and executive director. He was then promoted to Full Professor with tenure in 2011. In October 2013, Dr. Jiang joined University of Texas Southwestern Medical Center as a tenured Full Professor, Barbara Crittenden Professor in Cancer Research, Vice Chair of Radiation Oncology Department, and Director of Medical Physics and Engineering Division. Dr. Jiang is a Fellow of Institute of Physics and American Association of Physicists in Medicine. Dr. Jiang’s research in various areas of cancer radiotherapy has been funded by federal, state, charitable, and industrial grants for over 15 million dollars, resulting in over 200 peer-reviewed journal papers with an H-index of 75. His current research interest is on the development and deployment of artificial intelligence technologies to solve medical problems. He is the founding director for both Medical Artificial Intelligence and Automation Laboratory and Program of Excellence in Intelligent Medicine at UT Southwestern. He has supervised over 30 postdoctoral fellows and 10 Ph.D. students.