Marriott Marquis Houston
Houston, Texas, United States
15 - 20 February 2020
Technical Events
Sunday/Monday Poster Viewing
Date: Sunday - Monday 16 - 17 February 2020
Time: 12:00 PM - 9:00 PM
Location: Salon D/E
Posters will be on display Sunday and Monday with extended viewing until 9:00pm on Sunday. The poster session with authors in attendance will be Monday evening from 5:30 to 7:00 pm. Award winners will be identified with ribbons during the reception. Award announcement times are listed in the conference schedule.

Poster presentations from the following conferences will be included: Physics of Medical Imaging; Computer-Aided Diagnosis; Image-Guided Procedures, Robotic Interventions, and Modeling; Imaging Informatics for Healthcare, Research, and Applications; and Ultrasonic Imaging and Tomography.
Workshop: Live Demonstrations
Date: Sunday 16 February 2020
Time: 5:45 PM - 7:45 PM
Location: Salon D/E
WK 4 Computer-Aided Diagnosis (Conference 11314)

Live Demonstrations


Workshop Chairs:
Dr. Lubomir Hadjiiski, Univ. of Michigan Health System (United States)
Dr. Karen Drukker, Univ. of Chicago (United States)

CALL FOR PARTICIPATION


The goal of this workshop is to provide a forum for systems and algorithms developers to show off their creations. The intent is for the audience to be inspired to conduct derivative research, for the demonstrators to receive feedback and find new collaborators, and for all to learn about the rapidly evolving field of medical imaging.

The Live Demonstration Workshop invites participation from all of the conferences that comprise the SPIE Medical Imaging symposium. We encourage the CAD, Digital Pathology, Image Processing, Imaging Informatics, Image Perception, Physics, and all other conferences to participate.

This workshop features interactive demonstrations that are complementary to the topics of SPIE Medical Imaging. Workshop demonstrations include samples, systems, and software demonstrations that depict the implementation, operation, and utility of cutting-edge as well as mature research. Having an accepted SPIE Medical Imaging paper is not required for giving a Live Demonstration; however, authors of SPIE Medical Imaging papers are encouraged to submit demonstrations that are complementary to their oral and poster presentations.

The session will include a Certificate of Merit Award presented to one demonstration considered to be of exceptional interest. We invite all workshop visitors to vote for three of their favorite demonstrations, with the final winner chosen from the top scorers by a group of appointed judges.

IMPORTANT DATES

  • January 17, 2020: Deadline for submission
  • January 24, 2020: Notification of acceptance
  • January 31, 2020: Deadline for two-slide summary


JOIN THE WORKSHOP


If you would like to demonstrate at the SPIE Medical Imaging Live Demonstrations Workshop, please send an e-mail with the subject "SPIE live demonstrations workshop" by the submission deadline to Lubomir Hadjiiski and Karen Drukker:
In the e-mail, supply the following information:
  • Title of the demo
  • Names and affiliations (name of institute, city, country) of the demonstrators
  • Short description of the demo, one paragraph minimum. Make sure it clearly describes the technology and application area of the demo. You may cite or include a paper describing the demo.
  • Optionally, describe the public data used in the development or evaluation of the system. Include a link to the data or to a page that describes how to access that data.
  • Optionally, include a link to a video showing the system in action.


NOTES

Please note the following rules and requirements:
  • The accepted demonstrations will be listed online in the workshop program.
  • If there are more proposals than presentation slots in the workshop, the organizers will accept teams for demonstrations based on the quality of the provided description, while also striving to select a representative mix of applications.
  • Each team is responsible for bringing their own equipment. The organization will provide a table and power supply for each demonstration. Demos should be done on a single laptop. If the demo requires an external monitor this is allowed, but there should be no more than one monitor of 25″ maximum size.
  • Participation in the workshop is free of charge, but all demonstrators (those present during the workshop) must be registered to attend the SPIE Medical Imaging Conference.
  • Teams from academia (universities, university medical centers, research organizations), and from industry are invited to participate in this year’s workshop. Demonstrations from industry should be scientific and not commercial in nature; demonstration of research prototypes is highly encouraged.
  • All participating teams will need to provide one or two slides describing their system shortly before the conference from which the opening presentation will be compiled (two-slide summary).
  • After you submit a description, you will receive a confirmation by e-mail. Notification of acceptance or rejection will follow on the date given above.
Workshop: X-ray Source Technologies: Fundamental Principles, Technological Advances, and Clinical Needs
Date: Sunday 16 February 2020
Time: 5:45 PM - 7:45 PM
Location: Salon A
WK 1 Technical Workshop: Physics of Medical Imaging (Conference 11312)

Technical Workshop: X-ray Source Technologies: Fundamental Principles, Technological Advances, and Clinical Needs

The x-ray source is one of the key components in modern x-ray and Computed Tomography (CT) imaging. X-ray beam characteristics have a profound impact on conventional x-ray and CT image quality. For this workshop, expert speakers were invited to discuss the fundamentals of conventional x-ray tubes, the physical principles that drive source technological innovations, and finally the challenges and opportunities of new x-ray source technology in current and future x-ray based medical imaging. Several blue sky short talks will introduce potentially impactful source technologies.

Speakers:
Rolf Behling, Phillips Medizin Systeme GmbH (Germany) - "Fundamentals of Conventional X-ray Tube Technologies"
Paul Schwoebel, Univ. of New Mexico and SRI International (United States) - "Fundamental Physics Principles that Drive New X-ray Source Developments"
Norbert Pelc, Stanford Univ. (United States) - "Challenges and Opportunities of X-ray Source Technologies in Present and Future Applications"
Blue Sky Talks To Be Announced
Monday Poster Session
Date: Monday 17 February 2020
Time: 5:30 PM - 7:00 PM
Location: Salon D/E
Conference attendees are invited to attend the Monday Poster Session, where authors will be in attendance. Come view the posters, enjoy light refreshments, ask questions, and network with colleagues in your field. Award winners will be identified with ribbons during the reception.

Poster presentations from the following conferences will be included: Physics of Medical Imaging; Computer-Aided Diagnosis; Image-Guided Procedures, Robotic Interventions, and Modeling; Imaging Informatics for Healthcare, Research, and Applications; and Ultrasonic Imaging and Tomography.
Tuesday/Wednesday Poster Viewing
Date: Tuesday - Wednesday 18 - 19 February 2020
Time: 12:00 PM - 9:00 PM
Location: Salon D/E
Posters will be on display Tuesday and Wednesday with extended viewing until 9:00pm on Tuesday. The poster session with authors in attendance will be Wednesday evening from 5:30 to 7:00 pm. Poster award winners will be recognized and certificates distributed in the conference meeting rooms. Check conference schedules for times and locations. Ribbons will identify winning posters during the Poster Sessions.

Poster presentations from the following conferences will be included: Image Processing; Image Perception, Observer Performance, and Technology Assessment; Biomedical Applications in Molecular, Structural, and Functional Imaging; and Digital Pathology.
Workshop: Translation of Deep Learning Technology to the Clinic
Date: Tuesday 18 February 2020
Time: 5:00 PM - 7:00 PM
Location: Salon C
WK 2 Technical Workshop: Image Processing (Conference 11313)

Technical Workshop: Translation of Deep Learning Technology to the Clinic

Medical AI market is expected to break to 2 billion USD revenue within 5 years. Even though promising we still need to overcome several barriers including technological robustness, clinical validation, regulatory compliance, market acceptance and financial risks. In a number of presentations we focus on the barriers and how to overcome these seen from start-up, regulators, and commercial perspectives.

Program:

5:00 PM Introduction by Hayit Greenspan, Tel Aviv Univ. (Israel) and Mads Nielsen, Univ. of Copenhagen (Denmark)
5:10 PM Nico Karssemeijer - The start-up perspective
5:35 PM Stephen Aylward - The technology perspective
6:00 PM Weijie Chen - The regulatory perspective
6:25 PM Ole Graumann - The radiologist perspective
6:50 PM Discussion of learnings and Q & A

Nico Karssemeijer, Radboud University Medical Ctr. (Netherlands) and Screenpoint (United States)

Nico Karssemeijer is professor of Computer-Aided Diagnosis. He studied Physics at Delft University of Technology and graduated at the Radboud University Nijmegen, department of Medical Physics. In 1989 he joined the Department of Radiology of the Radboud University Nijmegen Medical Center, where he formed a research group in computer aided detection (CAD). His professorship is in the Faculty of Science of the Radboud University in the section Intelligent Systems of the Institute for Computing and Information Sciences iCIS. He is Associate Editor of IEEE Transactions on Medical Imaging, and member of the Editorial Boards of Physics in Medicine and Biology and Medical Image Analysis. In 2012 and 2013 he was symposium chair of SPIE Medical Imaging while previously he chaired IWDM98 and IPMI 2007. Nico Karssemeijer was closely involved in the development of the R2 ImageChecker, the most widely used CAD system to date, and is co-founder of Matakina, Ltd. (Wellington, New Zealand), a company that develops technology for quantitative mammography. In 2014, he founded ScreenPoint, a company developing image analysis technology for automated reading of mammograms and digital breast tomosynthesis.

Stephen Aylward, Kitware, Inc. (United States) - "Delivering Clinical Deep Learning Algorithms"

Dr. Watson paved the way for AI systems to broadly impact patient care because it by brought many important issues surrounding data transfer, data gathering, and AI algorithm limitations into the collective consciousness of clinicians, hospital administrators, patients, and product developers. These advances have significantly reduced the barriers for large and small businesses to deliver deep learning algorithms as clinical products. However, the technologies underlying these products are still rapidly evolving, e.g., involving cloud computing, edge computing, and mobile computing as well as AR and VR systems. In this talk we will discuss recent advances, existing practical solutions, and future opportunities for delivering technologically effective clinical deep learning solutions.

Stephen R. Aylward, Ph.D. is Senior Director of Strategic Initiatives at Kitware. Kitware provides consultation in medical imaging, computer vision, data analytics, and scientific computing. Kitware also produces several open-source platforms such as the Visualization Toolkit (VTK), the Insight Toolkit (ITK), ParaView, CMake, and 3D Slicer. Stephen's research currently involves point-of-care ultrasound applications, image registration in the presence of large pathologies, and vascular network characterization for disease assessment.

Weijie Chen, U.S. Food and Drug Administration (United States) - "Assessment of AI/ML based devices in medical imaging applications"

Artificial intelligence and machine learning algorithms, currently dominated by deep learning neural networks, are widely used in medical imaging applications from radiology to pathology and optical imaging, etc. Assessment methodologies play a critical role in translating such technologies to the clinic to benefit patients: to reasonably ensure safety and effectiveness on the one hand and to do so in an efficient manner on the other. In this talk, I will briefly overview assessment methods that are currently in use. We will then discuss a few topics that warrant further research including: reproducibility of highly complex algorithms, continuous-learning AI/ML, monitoring AI/ML performance with an imperfect reference standard, and assessment of AI/ML for ruling out images from the physician’s review. We conclude that this is an exciting time for AI/ML and we call for consensus-oriented collaborative efforts to move the field forward.

Weijie Chen received his PhD in medical physics from the University of Chicago, Chicago, Illinois, in 2007. Since then, he has been a research scientist at the Center for Devices and Radiological Health, U.S. Food and Drug Administration, Silver Spring, Maryland. His research interests include assessment methodologies for artificial intelligence and machine learning algorithms with applications in radiology, digital pathology and beyond, computer-aided diagnosis in medical imaging, and reader studies.

Ole Graumann, Odense Univ. Hospital (Denmark) - "What deep learning technology does the clinic need?"

The amount of diagnostic imaging is increasing worldwide. It is estimated that CT and MRI alone have an increase around 8-10% annually. At the same time the number of Radiologist is not rising at the same pace. This presentation will give an insight to the radiologist perspective on where deep learning technology can help us up front now and in the near future: Referral, visitation, booking, selection of image protocol, reduction of unnecessary images to reduce scan time, image interpretation and automatically reporting. The presentation will also touch the importance of the evidence based holistic approach when a new technology is implemented in the clinic.

Dr. Graumann is board certified in Radiology. He has special interests in Oncology Intervention and is one of the leading experts in Europe within Cryo ablation of Renal Cancer. Dr. Graumann has, in an impressive innovative way, built an extremely effective teamwork-based CT intervention team. People from around the world are visiting the CT intervention team at OUH to see and get inspiration from the workflow. Dr. Graumann is a proctor and has trained many colleagues in Northern Europe. Dr. Graumann currently serves as the Head of Research and Innovation Unit of Radiology at University of Southern Denmark. Dr. Graumann has led and participated in a multitude of clinical trials and research. He is currently main- and co-supervisor for many PhD and post-doctoral students. His largest research area presently is Cryo ablation, Artificial Intelligence, clinical skill training and education. Dr. Graumann has written and contributed to a number of scientific books and published works within the subject of radiology. Dr. Graumann is becoming Professor of Radiology within the near future.
Workshop: Simulated Tumor Board: Brain and Breast
Date: Tuesday 18 February 2020
Time: 5:00 PM - 7:00 PM
Location: Salon B
WK 3 Technical Workshop: Computer-Aided Diagnosis (Conference 11314) and Digital Pathology (Conference 11320)

Simulated Tumor Board: Brain and Breast

This workshop will present two example clinical cases, one breast cancer case and one brain cancer case. A multi-disciplinary team will discuss the case, the imaging information, pathology, and treatment options. The workshop will mimic the format of a standard clinical tumor board process with time for Q&A at the end.

Moderator:
Kristy Brock, PhD, DABR, FAAPM
Professor, Department of Imaging Physics and Department of Radiation Physics, Univ. of Texas MD Anderson Cancer Center (United States)

Breast Panel Speakers:
Simona Shaitelman, Univ. of Texas MD Anderson Cancer Ctr., Radiation Oncology (United States)
Isabelle Bedrosian, Univ. of Texas MD Anderson Cancer Ctr., Surgery (United States)
Jennifer Litton, Univ. of Texas MD Anderson Cancer Ctr., Medical Oncology (United States)
Wei Yang, Univ. of Texas MD Anderson Cancer Ctr., Diagnostic Radiology (United States)
Alejandro Contreras, Univ. of Texas MD Anderson Cancer Ctr., Pathology (United States)

Brain Panel Speakers:
Caroline Chung, Univ. of Texas MD Anderson Cancer Ctr., Radiation Oncology (United States)
Jeff Weinberg, Univ. of Texas MD Anderson Cancer Ctr., Surgery (United States)
Melissa Chen, Univ. of Texas MD Anderson Cancer Ctr., Diagnostic Radiology (United States)
Jason Huse, Univ. of Texas MD Anderson Cancer Ctr., Pathology (United States)
Workshop: Task-driven AI: Taking into Account the User's Perspective
Date: Tuesday 18 February 2020
Time: 5:00 PM - 7:00 PM
Location: Salon A
WK 5: Technical Workshop: Image Perception, Observer Performance, and Technology Assessment (Conference 11316)

Task-driven AI: Taking into Account the User's Perspective

Machine learning and artificial intelligence techniques are exponentially being developed and applied to a wide variety of scenarios in medical imaging ranging from image segmentation and analysis to analyzing radiologists’ reports to managing clinical workflow. Although we are slowing seeing these applications integrated into clinical workflow, much of the development work is still in the research stages. In order to bridge the gap between research and clinical integration and implementation, a greater emphasis needs to be placed on understanding the impact of the output of these machine learning and AI schemes on the human decision-maker. This workshop will present a variety of perspectives on the role of AI and machine learning in medical imaging from the perspective of the users.

Moderators:
Yan Chen, Univ. of Nottingham (United Kingdom)
Elizabeth A. Krupinski, Emory Univ. (United States)

Panelists:
Sian Taylor-Phillips, Univ. of Warwick (United Kingdom)
Francine Jacobson, Brigham and Women's Hospital (United States)
Elizabeth A. Krupinski, Emory Univ. (United States)
Wednesday Poster Session
Date: Wednesday 19 February 2020
Time: 5:30 PM - 7:00 PM
Location: Salon D/E
Conference attendees are invited to attend the Wednesday Poster Session, where authors will be in attendance. Come view the posters, enjoy light refreshments, ask questions, and network with colleagues in your field. Award winners will be identified with ribbons during the reception.

Poster presentations from the following conferences will be included: Image Processing; Image Perception, Observer Performance, and Technology Assessment; Biomedical Applications in Molecular, Structural, and Functional Imaging; and Digital Pathology.
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