News | Artificial Intelligence | March 25, 2019

System helps radiologists deliver AI-assisted annotation, adapt AI for their patients and deploy it in the hospital

NVIDIA Launches Clara AI Toolkit for Algorithm Development

March 25, 2019 — NVIDIA introduced Clara AI, a toolkit that includes 13 classification and segmentation artificial intelligence (AI) segmentation algorithms, and software tools built for radiologists.

Labeled data is critical to build safe and robust AI, but radiologists’ time is too precious to spend hours labeling datasets. The Clara AI assisted annotation capability speeds up the creation of structured datasets, enabling annotations in minutes instead of hours. The toolkit facilitates the integration of AI models into existing radiology workflows using industry standards like DICOM.

Transfer learning, another capability in the Clara AI toolkit, adapts existing models to fit local variables. It customizes deep learning algorithms to data that includes local demographics and imaging devices, without having to move or share patient data. As a result, doctors can create models for their own patients with 10 times less data than starting from scratch.

NVIDIA noted that several institutions are already using Clara AI, including:

  • The Ohio State University radiologists quickly incorporated a model developed at another institution, validated it and annotated a local dataset to adapt the model to OSU patients. This enables faster AI development of effective algorithms which support clinical care.

  • The National Institutes of Health Clinical Center and NVIDIA scientists used Clara AI to develop a domain generalization method for the segmentation of the prostate from surrounding tissue on magnetic resonance imaging (MRI). The localized model achieved performance similar to that of a radiologist and outperformed other state-of-the-art algorithms that were trained and evaluated on data from the same domain.

  • The University of California San Francisco (UCSF) is using a Clara AI-powered scalable infrastructure that will enable the seamless creation, testing and deployment of multiple AI algorithms across radiology, serving as a pathway for future doctors to adopt the system.

“We have an incredibly innovative group of researchers who are building clinically valuable AI tools, and need a consistent way to validate and deploy these tools into clinical workflows,” said Christopher Hess, chair of radiology, UCSF. “NVIDIA Clara will be an essential component of the medical imaging AI ecosystem that enables us to develop and deploy our own and external AI models.”

For more information: www.nvidia.com

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