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Empowering Radiology with AI

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The promise of AI to provide better patient care through accelerated workflows and increased diagnostic capabilities was in full display at RSNA. Catch up with all the news and highlights from the event.

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Empowering Radiology with AI

  1. 1. Key Takeaways from RSNA 2018 Empowering Radiology with AI
  2. 2. RADIOLOGICAL SOCIETY OF NORTH AMERICA (RSNA) RSNA hosted their 104th Scientific Assembly and Annual Meeting, the largest radiological meeting in the world, bringing together a diverse community of key luminaries, industry thought leaders, leading researchers and premier medical imaging startups.
  3. 3. RSNA: BY THE NUMBERS 45,000+ Attendees 797 Exhibitors 80+ Startups, including 41 Inception members 431 Session talks 44 Theatre presentations 951 Scientific posters 22 Instructor-Led DLI classes 1,300+ DLI attendees
  4. 4. For over 100 years, RSNA has hosted the world’s brightest minds in radiology, bringing together key opinion leaders and industry experts from around the world to discuss the latest medical imaging research, new diagnostic tools and protocols, and breakthrough technologies. NVIDIA participated once again, announcing new technologies and partnerships, spotlighting innovative research, engaging in talks and panels, and offering 22 NVIDIA Deep Learning Institute (DLI) instructor-led training sessions. RSNA 2018 LEARN MORE Source: https://blogs.nvidia.com/blog/2018/11/06/rsna-radiology-transformation-ai/
  5. 5. NOW AVAILABLE: NVIDIA CLARA SDK NVIDIA Clara SDK bundles NVIDIA technology and expertise specifically for medical imaging application developers with GPU-accelerated libraries for computing, visualization, and AI. The stack can be used at any level to create world-class applications, from reconstruction, image processing and rendering, and computational workflows for CT, MRI and ultrasound. Source: https://developer.nvidia.com/clara APPLY FOR ACCESS
  6. 6. ACCELERATING INNOVATION IN MEDICAL IMAGING NVIDIA announced the Transfer Learning Toolkit and AI Assisted Annotation SDK for Medical Imaging. The NVIDIA Transfer Learning Toolkit enables developers to harness NVIDIA’s pre-trained models to fine tune and retrain models using their own data. NVIDIA’s AI Assisted Annotation SDK speeds up the 3D annotation process for CT and MRI volumes and assists in discovering abnormalities much faster. Available early 2019. Source: https://news.developer.nvidia.com/nvidia-announces-the-transfer-learning-toolkit-and-ai-assisted-annotation-sdk-for-medical-imaging/ DISCOVER MORE
  7. 7. RAPIDS FOR HEALTHCARE At RSNA, NVIDIA showcased RAPIDS, a new open source project that brings GPU acceleration to data science workflows. Applied specifically to healthcare, RAPIDS demonstrates its potential to improve clinical care, operational efficiency, speed up drug discovery, and advance precision medicine. Source: https://rapids.ai GET STARTED WITH RAPIDS
  8. 8. COLLABORATING TO BRING AI TO THE CLINIC NVIDIA also announced partnerships with OSU Wexner Medical Center and the National Institutes of Health. OSU Wexner Medical Center and NVIDIA aim to build the first in-house AI marketplace on the NVIDIA Clara platform. NVIDIA’s partnership with the National Institutes of Health will focus on bringing AI tools to clinical trials. Source: https://www.dotmed.com/news/story/45468?s=newsreg READ THE ARTICLE
  9. 9. HARNESSING THE NVIDIA CLARA AI INFERENCE ENGINE Watch OSU Wexner Medical Center demo the NVIDIA Clara AI Inference Engine on their Coronary Artery Disease and Femur Fracture Models. Source: http://aii.osu.edu/2018/11/25/our-coronary-artery-disease-and-femur-fracture-models-in-use-with-nvidias-clara-ai-inference-engine/ WATCH NOW
  10. 10. SPOTLIGHT ON NVIDIA RESEARCH 3D Brain MRI Brain Tumor Segmentation Using Autoencoder Regularization Automated segmentation of brain tumors provides faster, accurate diagnosis to enable better treatment plans. Medical Image Synthesis for Data Augmentation and Anonymization Using Generative Adversarial Networks For the first time, researchers are using GANs to generate abnormal brain MRI images. Learning Image Restoration without Clean Data, Enhance Grainy Photos with AI A deep learning based method that can fix images by simply looking at examples of corrupted images only. Source: https://www.youtube.com/watch?v=gg0F5JjKmhA&list=PLZHnYvH1qtOaI5QZVi5OwPAqq15AMEoMl WATCH THE VIDEOS
  11. 11. AI’S PATH TO THE CLINIC Kimberly Powell delivered a talk on the technology breakthroughs that have allowed for the development of AI tools for radiologists and have created a path to bring AI to the clinic. “Through listening to radiologists and our clinical partners we have learned and created a domain specific solution for healthcare to accelerate the path of AI to the clinic.” -Kimberly Powell, VP of Healthcare, NVIDIA Source: https://www.nvidia.com/en-us/healthcare LEARN MORE
  12. 12. BUILDING AN AI FUTURE NVIDIA’s own Abdul Hamid Halabi, Global Business Development Lead for Healthcare and Life Sciences, participated in two panels and outlined the three key pieces needed to make AI a reality in the clinic: Gather data sets, develop AI infrastructure, and create algorithms to support and capture the vast amount of health sensor data. Source: http://education.rsna.org/diweb/catalog/item/eid/1030717579 LEARN MORE
  13. 13. NVIDIA DEEP LEARNING INSTITUTE (DLI) AT RSNA RSNA Deep Learning Classroom hosted 1,300+ attendees for 22 hands-on training sessions throughout the week. Led by NVIDIA DLI instructors, these sessions focused on how to apply AI to solve challenging problems in medical imaging, including 3D Segmentation of Brain MR and Advanced Data Augmentation Using GANs. Source: https://www.nvidia.com/en-us/deep-learning-ai/education/ LEARN MORE ABOUT DLI
  14. 14. A GROWING STARTUP ECOSYSTEM In just one year, startup participation at RSNA doubled--bringing in over 80 startups, including 41 NVIDIA Inception program partners. 13 Inception partners showcased their cutting- edge technology in medical imaging in the NVIDIA booth, including: Zebra Medical Vision, Imagia, 12 Sigma Technologies, IMFusion, Cephasonics Ultrasound Solutions, EMTensor, Quibim, Image Biopsy Lab, CureMetrix, Balzano, Subtle Medical, HeartVista, and NE Scientific. Source: https://www.nvidia.com/en-us/deep-learning-ai/startups/ LEARN MORE ABOUT INCEPTION
  15. 15. NUANCE HOSTS NVIDIA CLARA PLATFORM Nuance hosted NVIDIA in their booth to show how the NVIDIA deep learning platform, combined with Nuance’s PowerScribe radiology reporting and PowerShare image exchange network, enables development and deployment of imaging AI models into the AI Marketplace. “The NVIDIA Clara computing platform powers scalable inferencing of applications to the Nuance AI Marketplace. NVIDIA’s AI computing platform is available everywhere, which gives the AI Marketplace maximum flexibility, allowing health systems to keep their data securely on premise, or to take advantage of AI computing in the cloud.” -Karen Holtzberger, Vice President and General Manager of Healthcare Diagnostics, Nuance Source: https://globenewswire.com/news-release/2018/11/26/1656562/0/en/Nuance-s-AI-Marketplace-Delivers-AI-at-Scale-with-Industry-s-First-Workflow-Integrated-Market-for-Diagnostic-Imaging-Algorithms.html LEARN MORE
  16. 16. To learn more about NVIDIA in healthcare, visit: http://www.nvidia.com/healthcare

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