MONAI Tutorials

Skeletonize densely labeled 3D image segmentations.

Marching Cubes & Mesh Simplification on multi-label 3D images.

Understanding Deep Learning - Simon J.D. Prince

Google Research

AI Toolkit for Healthcare Imaging

A categorized list of C++ resources.

Fork of https://github.com/d3x0r/MarchingTetrahedra - adds texturing test

Notebooks for the third edition of Think Stats

Manuscript of the book "Tidy Text Mining with R" by Julia Silge and David Robinson

Public facing notes page

📜 33 JavaScript concepts every developer should know.

WebGL effects made easy.

Dijkstra's Shortest Path for 6, 18, and 26-Connected 3D Image Volumes

A list of papers on Generative Adversarial (Neural) Networks

Semi Supervised Learning for Medical Image Segmentation, a collection of literature reviews and code implementations.

An abundance of augmentation layers

A curated list of awesome resources for topics related to computational photography via deep learning, which mainly focuses on image alignment and stitching.

[ECCV'20] Self-supervision with Superpixels: Training Few-shot Medical Image Segmentation without Annotation (code&data-processing pipeline)

Collaborative Collection of C++ Best Practices. This online resource is part of Jason Turner's collection of C++ Best Practices resources. See README.md for more information.

An invigorating blend of 3D geometry tools in Python.

Efficient R programming: a book

Fast Base64 stream encoder/decoder in C99, with SIMD acceleration

Advanced R: a book

Simplifying deep learning for medical imaging

Optimization learning for image registration.

Mastering Bitcoin 2nd Edition - Programming the Open Blockchain

Differentiable elastic deformations for N-dimensional images (Python, SciPy, NumPy, TensorFlow, PyTorch).

[NeurIPS 2022] Non-rigid Point Cloud Registration with Neural Deformation Pyramid

1st Edition of Elegant SciPy (O'Reilly Publishers)