Stars
An open source re-implementation of RollerCoaster Tycoon 2 🎢
Fully automatic censorship removal for language models
Integrating SAM2 with DINOv2/v3 for segmentation
The repository provides code for running inference with the Meta Segment Anything Model 2 (SAM 2), links for downloading the trained model checkpoints, and example notebooks that show how to use th…
👏Mask-Enhanced Segment Anything Model for Tumor Lesion Semantic Segmentation[MICCAI 2024]
Discover best root apps, Magisk & LSPosed(xposed) modules with step-by-step rooting guides
Bake a cake with care, follow steps the recipe gives, that’s an algorithm.
Software asset for "Rethinking Pulmonary Embolism Segmentation: A Study of Current Approaches and Challenges with an Open Weight Model"
Code accompanying the paper 'Automatic Coronary Artery Plaque Quantification and CAD-RADS Prediction using Mesh Priors' (IEEE-TMI)
Official repository of the paper "RRWNet: Recursive Refinement Network for Effective Retinal Artery/Vein Segmentation and Classification", published in Expert Systems with Applications (Dec 2024).
Winning method of the Generalized Analysis of Vessels in Eye (GAVE) Challenge at MICCAI 2025.
Pytorch Implementation of Low-Dose CT with a Residual Encoder-Decoder Convolutional Neural Network (RED-CNN)
A foundation model for universal 3D blood vessel segmentation. Paper accepted @ CVPR25.
Hierarchical Part-based Generative Model for Realistic 3D Blood Vessel (MICCAI 2025)
The materials of "Hypervisor 101 in Rust", a one-day long course, to quickly learn hardware-assisted virtualization technology and its application for high-performance fuzzing on Intel/AMD processors.
Code for the MICCAI 2025 paper "HyperSORT: Self-Organising Robust Training with hyper-networks"
A software to edit, model and mesh vascular networks from centerlines.
High-level DICOM abstractions for the Python programming language
A curated list of project-based tutorials in C
An extremely fast Python package and project manager, written in Rust.
Publicly available medical imaging datasets for research and analysis.