Hatfield, Pennsylvania-based CurveBeam, LLC and Melbourne, Victoria, Australia-based StraxCorp Pty Ltd have entered into a definitive merger agreement to form CurveBeam AI Limited.
Introducing CurveBeam AI Limited
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The companies have been working together since 2018. CurveBeam specializes in weight bearing CT (WBCT) imaging for the orthopedics industry. StraxCorp provides artificial intelligence (AI) and deep learning AI (DLAI) solutions for bone separation, segmentation, and microstructure.
CurveBeam AI will apply the existing AI and DLAI solutions to “automated orthopedic analyses.” The solutions will be delivered via the cloud as “Software as a Medical Device.” The merger, per the press release, “expands CurveBeam’s financially viable point-of-care imaging solutions into the bone health space, as well as springboards artificial intelligence (AI) driven applications for weight bearing CT (WBCT) imaging.”
CurveBeam CEO Arun Singh explained, “CurveBeam AI will offer proprietary tools to improve patient outcomes at a speed and scope that CurveBeam could not alone.”
Singh continued, “Weight bearing CT imaging will remain a core focus, however this merger signifies our steadfast commitment to build the complementary AI software tools that will reduce the barriers to adoption.”
CurveBeam AI currently has 51 employees. It will be an unlisted public company and is aiming for an initial public offering in 2023. The company’s global operations headquarters will remain in the U.S. in Hatfield while its Melbourne office in Australia will handle AI research and development, corporate finance, and intellectual property tasks.
In the press release, StraxCorp CEO Greg Brown stated, “StraxCorp’s vision of delivering DLAI solutions at the point-of-care is best served by joining forces with a respected and trusted partner that ensures a new standard in high resolution CT imaging.”
Brown continued, “Often differences in scanner settings can be a major source of errors. Controlling image quality globally gives us an optimized platform to deliver a world class population health solution.”
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This is a fascinating development. In my practice we've seen similar outcomes with the revised protocol. The key differentiator seems to be patient selection criteria. Has anyone else noticed the correlation with BMI thresholds?
Great point. I'd push back slightly on the conclusion, the sample size in the cited study is too small to draw population-level inferences. That said, the directional signal is compelling and worth a larger RCT.
We implemented a similar approach last year. Early results are promising but we're still gathering 12-month follow-up data. Happy to share our protocol if anyone is interested.
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