For more than a decade, GE has partnered with Nvidia in Healthcare to power our most advanced modality equipment, from CT to Ultrasound. Part 1 of this session will offer an introduction to the deep learning efforts at GEHC, the platform we're building on top of NGC to accelerate new algorithm development, and then a deep dive into a case study of the evolution of our cardiovascular ultrasound scanner and the underlying extensible software stack. It will contain 3 main parts as follows: (a) Cardiovascular ultrasound imaging from a user perspective. Which problems we need to solve for our customers. Impact of Cardiovascular disease in a global perspective (b) An introduction to the Vivid E95 and the cSound platform , GPU based real time image reconstruction & visualization. How GPU performance can be translated to customer value and outcomes and how this has evolved the platform during the last 2 ½ years. (c) Role of deep learning in cardiovascular ultrasound imaging, how we are integrating deep learning inference into our imaging system and preliminary results from automatic cardiac view detection.
GEHC introduced the Vivid E95 premium cardiovascular ultrasound scanner in June 2015 based on the ground breaking cSound system architecture. The Vivid E95 uses two Quadro GPUs for real time image reconstruction, image processing and visualization. The session will first give a quick introduction to the architecture and the clinical benefits. It will then cover new GPU based features that were recently introduced to further improve the performance and usability of the Vivid E95. Finally the session will cover future plans for making the scanner more intelligent with use of deep learning algorithms and initial results of using TensorRT for real time cardiac view detection will be shared