News | Artificial Intelligence | August 02, 2018

RSNA Launches Artificial Intelligence Initiatives for 2018 and Beyond

Research and education opportunities include the Pneumonia Detection Challenge, workshops and hands-on opportunities at RSNA 2018 annual meeting

RSNA Launches Artificial Intelligence Initiatives for 2018 and Beyond

August 2, 2018 — The Radiological Society of North America (RSNA) recently announced that it will offer its members expanded opportunities in machine learning (ML) and artificial intelligence (AI) research and education over the coming months and into the future.

“In the years to come, RSNA’s support for education, research and innovation in this field will grow as AI becomes an integral part of radiology practice,” said Curtis P. Langlotz, M.D., Ph.D., RSNA board liaison for information technology and annual meeting. “RSNA will continue to educate not only radiologists, but also researchers and industry scientists about AI and ML.”

In August 2018, RSNA will launch the first in a series of live, 60-minute webinars on AI and its applications for radiology, featuring internationally renowned experts. The first webinar, “Intro to AI and Machine Learning: Why All the Buzz?” will be held on Aug. 29. RSNA will offer additional AI webinars on Oct. 25, Dec. 11, and Feb.21, 2019.

Also in August, RSNA will co-sponsor the National Institutes of Health (NIH)/National Institute of Biomedical Imaging and Bioengineering workshop, “Artificial Intelligence in Medical Imaging,” to foster collaboration in applications for diagnostic medical imaging. RSNA’s co-sponsors for the workshop are the American College of Radiology (ACR) and the Academy for Radiology & Biomedical Imaging Research (ARBIR).

Following the successful debut of the ML Challenge in 2017, the RSNA Pneumonia Detection Challenge kicks off in August. The challenge invites teams to develop algorithms to identify and localize pneumonia on chest X-rays, using images from a publicly available National Institutes of Health (NIH) data set. The evaluation phase will be held in October, and the most accurate submissions will be recognized in the Machine Learning Showcase at the RSNA 2018 annual meeting, Nov. 25-30 in Chicago.

The 2018 challenge will be conducted using a software platform from data science competition firm Kaggle. Kaggle will donate $30,000 to be shared among the top entries.

“This year’s competition is a lot more image-heavy than in 2017,” said Safwan Halabi, M.D., clinical assistant professor of radiology and pediatric radiology at Stanford and chair of the ML Data and Standards Subcommittee of the RSNA Radiology Informatics Committee (RIC). “It represents one of the largest uses of patient imaging to date for this type of competition.”

The RSNA Spotlight Course, “Practical Applications in Artificial Intelligence,” being held Sept. 23-24 in Paris, France, will focus on integrating AI with current medical imaging and examine how AI will impact the future of radiology. Additional AI Spotlight courses will be held in 2019 in San Francisco and Paris, with more courses being developed in other regions of the world.

RSNA 2018 will offer a growing roster of programming focusing on the power and potential of AI in radiology and issues associated with implementation. Along with AI-focused refresher courses and scientific sessions, the meeting offers a variety of other educational experiences focusing on AI research.

Attendees can visit the National Cancer Institute’s Crowds Cure Cancer exhibit, returning for its second year. Presented in the Learning Center, the project invites radiologists to annotate clinical images for ML research.

Returning to the RSNA annual meeting in 2018 is the RSNA Deep Learning Classroom, presented by NVIDIA Deep Learning Institute (DLI). Certified instructors from NVIDIA’s DLI will be on hand to help attendees learn to write algorithms and improve their understanding of AI technology.

More than 1,000 people attended the 2017 classroom, which provided a general overview of ML. The 2018 classroom will increase the focus on radiology imaging with advanced topics like data augmentation, segmentation and multiparametric classification.

“The RSNA Deep Learning Classroom offers an opportunity for anyone with a laptop to construct and train an actual computer-vision system based on a neural network in just 90 minutes,” Langlotz said.

Also at RSNA 2018, the Machine Learning Showcase gives attendees an opportunity to learn about the latest ML technology and network with companies on the forefront of ML advances. The showcase will feature a Machine Learning Theater, offering presentations daily between 11 a.m. and 2 p.m.

In early 2019, RSNA will debut its new online journal, Radiology: Artificial Intelligence, highlighting the emerging applications of AI and ML in the field of imaging across multiple disciplines. The journal’s editor, Charles E. Kahn, Jr., M.D., M.S., invites submissions to the bi-monthly online journal.

For more information: www.rsna.org

Related AI Content

Technology Report: Artificial Intelligence 2017

Charles E. Kahn Jr. Named Editor of Radiology: Artificial Intelligence

SPECIAL SUPPLEMENT: How Artificial Intelligence Will Change Radiology

VIDEO: How AI Will Benefit Change Healthcare Customers and Enterprise Imaging

VIDEO: Examples of Artificial Intelligence in Medical Imaging Diagnostics

VIDEO: Development of Artificial Intelligence to Aid Radiology

Related Content

NVIDIA Launches Clara AI Toolkit for Algorithm Development
News | Artificial Intelligence | March 25, 2019
NVIDIA introduced Clara AI, a toolkit that includes 13 classification and segmentation artificial intelligence (AI)...
Improving Molecular Imaging Using a Deep Learning Approach
News | Nuclear Imaging | March 21, 2019
Generating comprehensive molecular images of organs and tumors in living organisms can be performed at ultra-fast speed...
DrChrono and 3D4Medical Partner to Bring 3-D Interactive Modeling to Physician Practices
News | Advanced Visualization | March 18, 2019
DrChrono Inc. and 3D4Medical have teamed up so practices across the United States can access 3-D interactive modeling...
Jennifer N. A. Silva, M.D., a pediatric cardiologist at Washington University School of Medicine in Saint Louis, Mo., describes “mixed reality” at ACC19 Future Hub.

Jennifer N. A. Silva, M.D., a pediatric cardiologist at Washington University School of Medicine in Saint Louis, Mo., describes “mixed reality” at ACC19 Future Hub.

Feature | Cardiac Imaging | March 17, 2019 | By Greg Freiherr
Virtual reality (VR) and its less immersive kin, augmented reality (AR), are gaining traction in some medical applica
WVU cardiology chief Partho Sengupta, M.D., describes at ACC 2019 how artificial intelligence already helps cardiologists in echocardiography.

WVU cardiology chief Partho Sengupta, M.D., describes at ACC 2019 how artificial intelligence already helps cardiologists in echocardiography. Photo by Greg Freiherr

Feature | Cardiac Imaging | March 16, 2019 | By Greg Freiherr
Machine learning is already having an enormous impact on cardiology, automatically calculating measurements in echoca
Sponsored Content | Videos | Enterprise Imaging | March 15, 2019
As a VNA, GE Healthcare Ce
Bay Labs Announces New Data on EchoGPS, AutoEF AI Software at ACC.19
News | Cardiovascular Ultrasound | March 15, 2019
Artificial intelligence (AI) company Bay Labs announced the presentation of two studies assessing performance of the...
Sponsored Content | Videos | Artificial Intelligence | March 13, 2019
At RSNA 2018, iCad showed how its...
Lucence Diagnostics to Develop AI Tools for Liver Cancer Treatment

Pseudocolor accentuated CT scan image of a liver tumor. Image courtesy of Lucence Diagnostics.

News | Oncology Diagnostics | March 12, 2019
Genomic medicine company Lucence Diagnostics announced a new project to develop artificial intelligence (AI) algorithms...
FDA Grants Breakthrough Designation to Paige.AI
News | Digital Pathology | March 08, 2019
Artificial intelligence (AI) startup company Paige.AI has been granted Breakthrough Device designation by the U.S. Food...