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.
加利福尼亞州帕洛阿爾託， 2023年4月19日 /PRNewswire/ — Segmed與NVIDIA和RadimageNet合作，今天宣佈共同努力生成和商業化用於研發的合成醫學成像數據。
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.
作爲該計劃的一部分，Segmed將在其自助醫療數據管理平臺Segmed Insight上提供合成醫學成像數據。除此之外，Segmed還可以在其數據網絡中訪問超過6000萬條去識別化的現實世界成像記錄。
Segmed, NVIDIA and RadImageNet announce collaboration to generate and commercialize synthetic medical imaging data.
Segmed、NVIDIA和RadimageNet宣佈合作生成和商業化合成醫學成像數據。
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.
最先進的生成成像模型經過訓練，可以爲 CT、MRI、超聲波和內窺鏡手術生成合成數據。這些模型可以生成 160 多種病理分類，也可以在合成圖像幀之上創建合成分段。然後，這些數據可用於訓練或增強下游 AI 模型訓練。Segmed正在向從事醫學研究的研究人員和公司提供上述數據以獲得許可。
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正在開發生成式人工智能模型，以創建高質量的合成圖像。這些圖像也將在未來幾個月內通過其Insight平臺提供。
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.
通過生成大量緊密模仿現實世界數據的合成圖像，這種合作將有助於擴大訓練數據的可用性，同時擴大患者數據集的範圍和可變性。生成數據的潛在用例包括模態、身體部位和重建平面的分類。合成數據還有保護患者隱私的額外好處，因爲合成記錄無法與真實患者相關聯。
"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首席技術官兼聯合創始人亞當·科塞克說：“我們很高興能與NVIDIA和RadimageNet合作開展這項計劃，因爲這次合作是朝着增強用於研究的數據集邁出的重要一步。”“用合成數據補充Segmed已經提供的現實世界數據，可以進一步提高我們客戶的人工智能算法和模型的穩健性和適應性。”
"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的一位代表說：“用於成像的生成式人工智能正處於轉折點，有能力真正實現醫療保健成像數據的民主化。”“我們很高興能與Segmed和RadimageNet等合作伙伴合作，將其變爲現實。”
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.
這種合作的目標是加快醫療人工智能算法的完善，以提高醫學診斷的準確性和一致性，最終改善患者預後。
About Segmed:
關於 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的使命是通過解鎖醫學影像研究中發現的獨特信息來徹底改變醫療保健研究，以便將其應用於創新。他們的軟件平臺——Segmed Insight——可以在全球成像網絡上創建研究隊列，同時還可以安全提取、去識別和轉移靶向研究。圖像可以與其他臨牀數據相關聯，以提供全面的縱向患者概況。這些功能爲特定患者羣體和/或疾病診斷和治療的研究和人工智能靶向成像提供支持。要了解更多信息，請訪問 。
About NVIDIA:
關於 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年成立以來，NVIDIA（納斯達克股票代碼：NVDA）一直是加速計算領域的先驅。該公司在 1999 年發明 GPU 激發了 PC 遊戲市場的增長，重新定義了計算機圖形，點燃了現代 AI 時代，並推動了元宇宙的創建。NVIDIA 現在是一家全棧計算公司，其數據中心規模的產品正在重塑行業。更多信息，請訪問 。
About RadImageNet:
關於 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 的成立旨在爲放射學人工智能提供放射學基礎。RadimageNet 與西奈山醫學中心的生物醫學工程與成像研究所合作，創建了圖像數據庫並對預訓練權重進行建模，以取代放射學 AI 中的 ImageNet。然後，這項工作促成了合成的 RadimageNet ——RadimageGan 的創建。
SOURCE Segmed
來源 Segmed