👉 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!
Smarter Integrations with TotalSegmentator
Integrating TotalSegmentator into Your Workflow
One question we hear often is how to integrate TotalSegmentator into medical imaging workflows. This powerful open-source tool breaks segmentation into “tasks,” with each task calling one or more nnUNet models. Running all models can be overkill if you only need a few specific structures segmented wasting both time and resources. That’s why it’s crucial to understand which tasks call which models and choose only what you need. In our projects, we don’t just install TotalSegmentator “as is.” We usually fork the repo, optimize inference speed, and deploy a custom version tailored to the client’s workflow. This approach saves computation time, reduces costs, and ensures smooth integration with existing systems. ​ Virtual Reality Is Transforming HealthcareVirtual reality (VR) is finding its place in clinics, classrooms, and even operating rooms. From streaming live surgeries for global training to helping patients relax during stressful procedures, VR is making care more engaging and less intimidating. Early studies show VR can reduce pain and anxiety, speed up recovery in physical therapy, and even improve empathy among medical students by simulating age-related conditions. As headsets become cheaper and more accessible, expect VR to become a standard part of medical education, patient care, and rehabilitation. ​ ​
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 ↓ 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...
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...