We built DICOM Viewer + Volume Rendering


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Hello Reader,

Welcome to another edition of PYCAD newsletter where we cover interesting topics in Machine Learning and Computer Vision applied to Medical Imaging. The goal of this newsletter is to help you stay up-to-date and learn important concepts in this amazing field! I've got some cool insights for you below ↓

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DICOM Viewer with Volume Rendering

What you're seeing below is a DICOM viewer with 4 views: axial, coronal, sagittal and volume rendering. All integrated into one web app!
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We've built this using Trame and VTK.
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There are a ton of DICOM viewers available online but what I really love about the viewers that we built is the amount of fine grained control that you can have.
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VTK is already known in the medical imaging community as a great tool for building different visualization software.
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And by having the ability to integrate VTK pipelines directly into a Trame app makes a big difference.
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Because you can spend time perfecting your visualization by using all the tools that VTK gives you.
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And once you're happy with the visualization, then just integrate it into Trame and you got yourself a powerful medical visualization web app!
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Would you like us to build such a tool for you with more features? Respond to this email!

AI in Medical Imaging: A Market on the Rise

The global AI medical imaging market is booming, with a projected growth from $1.29 billion in 2023 to $4.54 billion by 2029 at a CAGR of 22.4%. This explosive growth is fueled by increased government support, rising investments in AI startups, and expanding adoption in regions like Asia Pacific and Latin America.

Why It Matters

AI is transforming medical imaging by enhancing early detection, automating workflows, and improving diagnostic precision. Innovations in radiology, oncology, and cardiology are paving the way for more accurate, patient-centered care.

What’s Driving the Market

  • Software Leads the Way: Scalable AI software solutions dominate the market, offering seamless integration with clinical workflows and cloud-based updates.
  • Regional Growth: Asia Pacific is set to see the highest growth, driven by advancements in healthcare infrastructure and government AI initiatives.
  • Oncology on the Rise: AI tools for early cancer detection and personalized treatment are rapidly expanding this segment.

With major players like NVIDIA, Google, and Siemens Healthineers driving innovation, the future of AI in medical imaging is brighter than ever.

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AI Revolutionizing Retinal Screening with AEYE-DS

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AEYE Health, co-founded by Zack Dvey-Aharon, has developed AEYE-DS, an FDA-approved AI-powered system that diagnoses diabetic retinopathy in under a minute using a handheld camera. This low-cost, portable tool, already used in hundreds of U.S. locations, aims to make advanced screening accessible to millions globally while expanding to detect other conditions like cardiovascular disease and glaucoma.


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We Can Help You with Your Next Medical Imaging Project

If your company or organization is looking to build a machine learning solution for a medical imaging problem, then feel free to reach out to us at:

​contact@pycad.co​

We can help you build a full ML solution from training to deployment with affordable rates!

You can check out some of the projects that we worked on here:

​https://pycad.co/portfolio and some of our clients case studies here.

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That's it for this week's edition, I hope you enjoyed it!

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Machine Learning for Medical Imaging

πŸ‘‰ Learn how to build AI systems for medical imaging domain by leveraging tools and techniques that I share with you! | πŸ’‘ The newsletter is read by people from: Nvidia, Baker Hughes, Harvard, NYU, Columbia University, University of Toronto and more!

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