👉 Learn how to build AI systems for medical imaging domain by leveraging tools and techniques that I share with you! | 💡 The newsletter is read by people from: Nvidia, Baker Hughes, Harvard, NYU, Columbia University, University of Toronto and more!
How We Build Our DICOM Viewers Using Plugins
How We Build Our DICOM Viewers Using Plugins
One thing we focus on when building DICOM viewers is keeping every feature as a separate plugin. This gives the app a clean structure and makes it easy to add, remove, or customize modules based on client needs. Layout types (MPR, MPR + VR, MPR + 3D Mesh) are plugins. Measurement tools (distance, angle, etc.) are plugins. Everything stays modular. We usually work with VTK + Trame, then integrate the viewer into a full-stack app. The idea is simple: define how each plugin receives inputs and sends outputs, and it will fit into the viewer without interfering with others, just like extensions in 3D Slicer. This approach keeps the core app stable while giving us the flexibility to build custom features quickly. A Quick Look at 3D Printing in Medicine3D printing is becoming a major player in healthcare. It’s no longer just a futuristic idea, many practical applications already exist. According to the article, 3D printing is now used to create personalized medical equipment, including splints that cost only cents to produce, surgical planning models, and even life-saving bioresorbable devices for airway support in infants. The technology is also advancing in prosthetics and implants, making customization faster and more affordable, especially for patients in low-resource settings. Research teams are exploring 3D-printed bone scaffolds, heart valves, and synthetic skin. Some groups have even printed early versions of blood vessels and small organ structures. In pharmaceuticals, the FDA has already approved 3D-printed drugs, and clinical trials are underway for personalized pediatric medications produced directly on demand. We’re still far from printing fully functional organs, but the progress across equipment, implants, tissues, and drug manufacturing shows how quickly the field is moving.
That's it for this week's edition, I hope you enjoyed it! |
Machine Learning for Medical Imaging
👉 Learn how to build AI systems for medical imaging domain by leveraging tools and techniques that I share with you! | 💡 The newsletter is read by people from: Nvidia, Baker Hughes, Harvard, NYU, Columbia University, University of Toronto and more!
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 ↓ AI & Health Insurance Claims: Helpful Future or Hidden Risk? AI is becoming a key part of how insurance companies handle medical claims, and a recent article offered a clear...
Hi Reader, Welcome to the PYCAD newsletter, where every week you receive doses of machine learning and computer vision techniques and tools to help you learn how to build AI solutions to empower the most vulnerable members of our society, patients. Why Medical Imaging Is Moving to the Browser There’s a clear shift happening in medical imaging: more and more platforms are going web-first. And it’s not just for design reasons. When imaging tools run in the browser, doctors don’t have to install...
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 ↓ Making MPR Simple in the Browser One question we often get is how to make multiplanar reconstruction (MPR) feel effortless on the web. Our goal is to make it as intuitive as...