"deepmriprep: VBM preprocessing via deep neural networks" is published in Nature Computational Science 🧠💻 🔗 Paper: rdcu.be/e1t4N VBM preprocessing in ~10 seconds per #brain image 🚀 🔗 GitHub: github.com/wwu-mmll/deepm… Install via "pip install deepmriprep"

Try "pip install flashrl" to make it even faster (on CPU and GPU). Write 6 lines of code to trains Pong in a few seconds!

After "pip install viiew" it also supports scrolling through your array/tensor/dataframe

🧐view(your_data) in the terminal🧐 "pip install viiew" for a - colorfull - scrollable - sortable view of your array/Tensor/DataFrame! Supports numpy, pandas, torch, jax & @__tinygrad__ and is tiny: 4.1kB (0 dependencies)!

Running RL was never easier! Here is the whole script run in the GIF

🚀 flashrl version 0.2.0 released 🚀 ✅ RL with millions of steps/second 💨 ✅ Play against your RL agent ⚔️ ✅ Wanna add your env? Add one .pyx file! ...and it uses emoji rendering 😙👌

🚀 Launching flashrl: RL in seconds 🚀 ✅ Train with ~3M steps per second 💨 ✅ Contains only ~200 lines of code 🤯 ✅ Wanna add your env? Add one .pyx file! Free your 🧠 RAM from boilerplate!

🧠 Releasing mriaug: Fast data augmentations for 3D MRIs! Useful for deep learning to ✅ Increase the amount training data ✅ Make models more robust wrt scanner effects 🔥 GPU-support -> 50x faster than torchio

🧠 niftiai is here! Training neural nets on 3D images just got way easier! Using #fastai it enables you to ✅ Train MRI classifiers in 15 lines ✅ Train UNets in 12 lines ✅ Easily view & augment 3D images 1. Dive into the Colab Tutorials 👀 2. pip install niftiai & try it 💻

🎉 Today I release #brain-stl 🎉 🧠 Turn your MRI into a 3D printable model 🖨️ Easily add custom text, adjust the tissue threshold and smooth the surface 🤯 Try the demo (non-programmer friendly) linked on GitHub (next post) or "pip install brain-stl"