Segmed, NVIDIA, and RadImageNet Kickstart Generative AI Initiative for Synthetic Medical Imaging Data
Segmed, NVIDIA, and RadImageNet Kickstart Generative AI Initiative for Synthetic Medical Imaging Data
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.
加利福尼亚州帕洛阿尔托， 2023年4月19日 /PRNewswire/ — Segmed与NVIDIA和RadimageNet合作，今天宣布共同努力生成和商业化用于研发的合成医学成像数据。
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.
作为该计划的一部分，Segmed将在其自助医疗数据管理平台Segmed Insight上提供合成医学成像数据。除此之外，Segmed还可以在其数据网络中访问超过6000万条去识别化的现实世界成像记录。
Segmed, NVIDIA and RadImageNet announce collaboration to generate and commercialize synthetic medical imaging data.
Segmed、NVIDIA和RadimageNet宣布合作生成和商业化合成医学成像数据。
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.
最先进的生成成像模型经过训练，可以为 CT、MRI、超声波和内窥镜手术生成合成数据。这些模型可以生成 160 多种病理分类，也可以在合成图像帧之上创建合成分段。然后，这些数据可用于训练或增强下游 AI 模型训练。Segmed正在向从事医学研究的研究人员和公司提供上述数据以获得许可。
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.
此外，Segmed正在开发生成式人工智能模型，以创建高质量的合成图像。这些图像也将在未来几个月内通过其Insight平台提供。
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.
通过生成大量紧密模仿现实世界数据的合成图像，这种合作将有助于扩大训练数据的可用性，同时扩大患者数据集的范围和可变性。生成数据的潜在用例包括模态、身体部位和重建平面的分类。合成数据还有保护患者隐私的额外好处，因为合成记录无法与真实患者相关联。
"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."
Segmed首席技术官兼联合创始人亚当·科塞克说：“我们很高兴能与NVIDIA和RadimageNet合作开展这项计划，因为这次合作是朝着增强用于研究的数据集迈出的重要一步。”“用合成数据补充Segmed已经提供的现实世界数据，可以进一步提高我们客户的人工智能算法和模型的稳健性和适应性。”
"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."
NVIDIA的一位代表说：“用于成像的生成式人工智能正处于转折点，有能力真正实现医疗保健成像数据的民主化。”“我们很高兴能与Segmed和RadimageNet等合作伙伴合作，将其变为现实。”
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.
这种合作的目标是加快医疗人工智能算法的完善，以提高医学诊断的准确性和一致性，最终改善患者预后。
About Segmed:
关于 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 .
Segmed的使命是通过解锁医学影像研究中发现的独特信息来彻底改变医疗保健研究，以便将其应用于创新。他们的软件平台——Segmed Insight——可以在全球成像网络上创建研究队列，同时还可以安全提取、去识别和转移靶向研究。图像可以与其他临床数据相关联，以提供全面的纵向患者概况。这些功能为特定患者群体和/或疾病诊断和治疗的研究和人工智能靶向成像提供支持。要了解更多信息，请访问 。
About NVIDIA:
关于 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 .
自1993年成立以来，NVIDIA（纳斯达克股票代码：NVDA）一直是加速计算领域的先驱。该公司在 1999 年发明 GPU 激发了 PC 游戏市场的增长，重新定义了计算机图形，点燃了现代 AI 时代，并推动了元宇宙的创建。NVIDIA 现在是一家全栈计算公司，其数据中心规模的产品正在重塑行业。更多信息，请访问 。
About RadImageNet:
关于 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.
RadimageNet, LLC 的成立旨在为放射学人工智能提供放射学基础。RadimageNet 与西奈山医学中心的生物医学工程与成像研究所合作，创建了图像数据库并对预训练权重进行建模，以取代放射学 AI 中的 ImageNet。然后，这项工作促成了合成的 RadimageNet ——RadimageGan 的创建。
SOURCE Segmed
来源 Segmed