The Radiological Society of North America (RSNA) recently held an event on applied artificial intelligence (AI). NVIDIA, a leader in core AI technology, appeared at the event with partners to showcase how AI is advancing in medicine to significantly speed up diagnosis through images.
Where AI is having the greatest success at the moment is with unstructured image-based data where, whether we are talking facial recognition or medical imaging, it significantly speeds up accurate identification of the image.
But AI can and does go farther with medicine in that it’s also used to identify the cause of a related illness and recommend the most efficient way to cure or mitigate that illness. If you’ve watched science fiction TV shows and movies, you’ve seen medical scanners that can better identify illnesses and injuries automatically. NVIDIA’s AI technology is on that critical path. This makes the related process more efficient and accurate and moves the timeline for creating these more advanced systems ahead significantly.
The Importance of Medical Imaging
Medical imaging is one of the most important tools in modern medicine today.
There is two-dimensional imaging for screening and early detection. Three-dimensional imaging layers on special understanding and quantitative measurement and segmentation. The fourth dimension adds temporal information, such as illness progression, that is essential for diagnosing and planning treatments. If an illness is progressing quickly, the responses need to be more invasive and higher risk, while a slowly moving or static progression may result in no medical response other than regular future observation to assure it doesn’t start spreading faster.
According to NVIDIA, using medical images with real-time, deep learning AIs and computer vision brings the industry into a fifth dimension where practitioners can get a holistic view of the patient, navigate within the human body to look for causes, and get a far stronger sense of the damage being done by the disease.
They can then use this information to plan actions while tracking progress and changes to the disease during the process. This, in turn, can help surgeons plan related procedures and surgical tasks.
NVIDIA’s Impact on Imaging
NVIDIA is aggressively operating in the medical segment and partnering with companies — like United Imaging, Fujifilm, Philips, Canon, Accuracy, and others — to provide the computational infrastructure needed to implement a comprehensive solution designed to improve image quality, lower radiation dose for X-Ray implementations, and run the related AI application to assist with the resulting diagnosis.
Much of the innovation of late has come from advanced sensors at the device level, increasing doctors’ ability to identify common and not-so-common problems and illnesses. But as sensors advance, they capture more data, and the related AI back end has to evolve to both absorb that data and provide the deeper insights that this additional data enables.
An example of this is Siemens’ Naeotom Alpha, a photon-counting CT scan, that improves image acquisition and reconstruction by reducing electronic noise while lowering radiation doses. This last is important, because CT scanners can significantly increase cancer risk due to the amount of radiation they use. Another example is Advanced Breast-CT’s nu:view product that uses spiral CT combined with photon-counting technology to deliver a compression-less breast exam that is more accurate.
NVIDIA provides innovators with the computational foundation to create the next generation of AI-backed, enterprise-class imaging platforms.
Medical events are often misdiagnosed or remain undiagnosed because of the quality of the imaging and the knowledge of the doctors, putting life and continued health at increased risk as people age.
These AI-based imaging advancements are helping assure that this imaging and diagnosis problem will improve sharply over the rest of the decade and hopefully increase our chances of as long and healthy a life as possible.
As a result, this NVIDIA AI effort is already changing care in an increasing number of health care institutions.