Radiology leaders have gathered for over 100 years running at RSNA, the annual meeting of the Radiological Society of North America, to discuss the industry’s latest challenges and opportunities. In recent years, AI in medical imaging has become a key focus — with startups at the center of the conversation.
Startups around the world are building AI solutions for a universal problem in medical imaging: limited time. Faced with rising numbers of patients being imaged, as well as the growing size of MRI and CT scans, radiologists must interpret one image every three or four seconds to keep up with the workload.
Agile startups are well-suited to tackle the demands of a rapidly evolving field like deep learning. In medical imaging, many are using AI to develop applications that target areas that slow radiologists down.
Healthcare startups raised more than $26 billion in venture capital funding last year and are partnering with major research institutions, hospitals and medical instrument manufacturers. They’re also receiving regulatory validation for clinical use: over three dozen healthcare AI startups have FDA clearance for algorithms that detect conditions including cancer, stroke and brain hemorrhages from medical scans.
At RSNA 2019, taking place in Chicago, Dec. 1-6, more than 50 attending startups are part of the NVIDIA Inception virtual accelerator program, which provides AI training and tools to fuel the growth of thousands of companies building GPU-powered applications, including over 700 healthcare startups.
Accelerated by NVIDIA GPUs, AI can speed up the acquisition, annotation and analysis of medical images to more quickly spot critical cases. It can also give experts quantitative insights that are too time-consuming to acquire using traditional methods.
Dozens of Inception companies will share their medical imaging applications for every phase of the radiology workflow at the RSNA AI Theater and the NVIDIA booth, including:
In NVIDIA booth 10939 and beyond, we’ll be exhibiting the latest AI tools for medical imaging, from training to deployment.
We’ll also showcase demos of the NVIDIA Clara medical imaging platform, which combines NVIDIA GPU hardware and the NVIDIA Clara software development kit to accelerate the training and inference of deep learning applications for healthcare. The platform includes APIs for AI-assisted annotation of medical images, a transfer learning toolkit, a medical model development environment and tools for AI deployment at scale.
A Clara developer meetup will be held on Tuesday, Dec. 3 at 11:30 a.m. CT.
The following RSNA panels feature NVIDIA speakers:
For more information, check out the full RSNA agenda.
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