PALO ALTO, Calif., April 19, 2023 /PRNewswire/ -- Segmed - in collaboration with NVIDIA and RadImageNet - today announced a joint effort to generate and commercialize synthetic medical imaging data for research and development.

As part of this initiative, Segmed will offer synthetic medical imaging data on their self-serve medical data curation platform, Segmed Insight. This is in addition to the 60M+ de-identified real-world imaging records that Segmed has access to in their data network.

State-of-the-art generative imaging models were trained to generate synthetic data for CT, MRIs, Ultrasound, and Endoscopic surgery. These models can generate over 160 pathologic classifications, as well as create synthetic segmentations on top of the synthetic image frames. This data can then be used to train or augment downstream AI model training. Segmed is making said data available for licensing to researchers and companies doing medical research.

In addition, Segmed is developing generative AI models to create high-quality synthetic images. These images will also be made available via their Insight platform in the coming months.

By generating large quantities of synthetic images that closely mimic real-world data, this partnership will help to expand the availability of training data, while also augmenting the scope and variability of patient datasets. Potential use cases of the generated data include classification of modality, body part, and reconstruction plane. Synthetic data has the added benefit of protecting patient privacy, as synthetic records cannot be linked back to real patients.

"We're thrilled to be working with NVIDIA and RadImageNet on this initiative, as this collaboration is a great step towards enhancing datasets used for research" said Adam Koszek, CTO & Co-founder of Segmed. "Supplementing the real-world data Segmed already provides with synthetic data can further increase the robustness and adaptability of our customers' AI algorithms and models."

"Generative AI for imaging is at an inflection point, and has the capability to truly democratize healthcare imaging data," said an NVIDIA representative. "We're excited to work with partners like Segmed and RadImageNet to make this a reality."

The goal of this partnership is to accelerate the refinement of medical AI algorithms to improve the accuracy and consistency of medical diagnoses, ultimately leading to better patient outcomes.

About Segmed:

Segmed's mission is to revolutionize healthcare research by unlocking the unique information found in medical imaging studies so they can be applied to innovation. Their software platform - Segmed Insight - enables the creation of study cohorts across a global imaging network, while also enabling safe extraction, de-identification, and transfer of the targeted studies. Images can be linked to other clinical data to provide a holistic longitudinal patient profile. These capabilities support research and AI-targeted imaging for specific patient populations and/or disease diagnosis and treatment. Learn more at .

About NVIDIA:

Since its founding in 1993, NVIDIA (NASDAQ: NVDA) has been a pioneer in accelerated computing. The company's invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined computer graphics, ignited the era of modern AI and is fueling the creation of the metaverse. NVIDIA is now a full- stack computing company with data-center-scale offerings that are reshaping the industry. More information at .

About RadImageNet:

RadImageNet, LLC was founded to provide a radiologic foundation for radiology artificial intelligence. In collaboration with Mount Sinai Medical Center's BioMedical Engineering and Imaging Institute, RadImageNet created an image database and model pre-training weights to supplant ImageNet in radiology AI. This work then led to the creation of a synthetic RadImageNet - RadImageGan.

SOURCE Segmed