NVIDIA’s AI-powered medical imaging platform to transform healthcare sector
New AI platform Clara can revolutionise the way medical imaging devices across the globe operate.
The pharmaceutical companies and the medical technology developers are trying their best to serve the healthcare requirements of the ever-growing population. They are using Deep Learning, quite a powerful version of Artificial Intelligence to simplify the medical processes and at the same time empower the consumers as well as care providers.
NVIDIA, the video game company, who recently ventured into the development of self-driving vehicles has recently disclosed its plans to develop Clara, an AI-powered medical imaging supercomputer, at the GPU Technology Conference held last month at Silicon Valley.
Towards the end of the last year, the company had earlier announced its partnership with GE Healthcare and Nuance to use NVIDIA’s AI platform for diagnostic imaging devices.
The company plans to exploit the advancements in the field of computation to create a virtual platform that aids in medical imaging requirements of the healthcare providers. Clara is still in the development phase and the company plans to chart out the detailed workflow by autumn this year, which is the time for Radiological Society of North America Summit to take place. NVIDIA says that it has been working in medical imaging field for over a decade.
Kimberly Powell, Healthcare VP at Nvidia said, “A decade ago, researchers realized NVIDIA GPUs provide the most efficient architecture for medical imaging applications and could help reduce radiation exposure, improve image quality and produce images in real time. More recently, deep learning is dominating, with more than half of new research in medical imaging applications involving AI.”
The imaging supercomputer Clara is believed to be virtual, remote, universal and scalable. It can simultaneously run innumerable computations; it can be accessed by multiple users at a time.
It can be used with data from any kind of imaging device such as CT, MR, ultrasound, or X-Ray etc.
Also, it can achieve even higher computational power as required. It simply takes bare data from medical imaging devices and uses it to do virtual imaging very quickly and efficiently.
At the AI World Medical Innovation Forum in Boston, company’s CEO Jenson Huang explained how the idea stemmed out. The current medical imaging devices, about 3 million in number across the world, are far less to serve the requirements of the medical industry. The company also hinted that it would like to expand its AI operations to other healthcare fields.
Image credit: www.nvidia.com