👉 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!
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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 ↓ 3 Resources we released in the past 2 weeks for nnUNetIn the past 2 weeks we released a ton of information about how to nnUNet to build powerful medical imaging segmentation models. Here's a summary of them. X Post of the DayGoogle introduces Explainable AI in Medical Imaging!
TotalSegmentator Has a New Feature!If you've been a subscriber for a long time then you've probably seen me cover TotalSegmentator multiple times! This is because, the folks behind it keep updating it with new awesome features every few weeks or months. The latest feature? TotalSegmentator now supports MR images! It can segment 59 anatomical structures in MR images, regardless of sequence or contrast! You can find out more about it in the official github repo and also in the original paper. Btw, TotalSegmentator is based on nnUNet models! So if you plan to build AI models similar to what TotalSegmentator is doing, then the guides we shared above would be a great starting point for you!
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!
Hi Reader! I hope you're doing well in this fine weekend! In the past weeks I've been working on implementing basic image segmentation models for 2D and 3D from scratch. While doing so, I found a few things that were delightfully surprising while other things were painfully irritating. I tell you all about it in this edition of the newsletter! What Building AI Models from Scratch has Thought me One of the reasons why I did these experimentations was to understand some of the nitty gritty...
Hi Reader, I haven't sent you a newsletter email for some time now. This is because there are major events happening in my personal life. We just had our first kid, so I'm still trying to adapt to the new routine set by this cute little creature! I also changed my office! I used to work from home, but now I am working in a coworking space. I'm hoping that this will help me deliver more value to the newsletter subscribers as well as our clients at PYCAD. Now, back to the newsletter! I've got...
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 ↓ Applications of Machine Learning for Dentistry At PYCAD, we have worked a lot on the applications of AI to the dentistry domain. Here are 3 incredible ones. 1 - Diagnosis and...