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Eclipse SUMO is an open source, highly portable, microscopic and continuous traffic simulation package designed to handle large networks. It allows for intermodal simulation including pedestrians and comes with a large set of tools for scenario creation.
DirectXMath is an all inline SIMD C++ linear algebra library for use in games and graphics apps
Generation of protein sequences and evolutionary alignments via discrete diffusion models
Code for the Nature Scientific Reports paper "Pathologist-level classification of histologic patterns on resected lung adenocarcinoma slides with deep neural networks." A sliding window framework for classification of high resolution whole-slide images, often microscopy or histopathology images.
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Tools for computational pathology
Library for multiscale visualization of high-resolution multiplexed bioimaging data on the web. Directly renders Zarr and OME-TIFF.
Image restoration for fluorescence microscopy
Automated 3D cell detection in very large images
PyTorch Connectomics: segmentation toolbox for EM connectomics
A Python interface to access neuroanatomical atlases
Interoperable web-based DICOM slide microscopy viewer and annotation tool
Automated 3D brain registration with support for multiple species and atlases.
Accurate and efficient spot detection for microscopy data
Python package for image-based profiling
Axon/Myelin segmentation using Deep Learning
python functions for simulating optical transfer functions
Minerva Story is an image viewer that is designed specifically to make it easy for non-expert users to interact with complex tissue images.
Methods for Image-Based Cell Profiling
A powerful library extending VBA with over 100 functions for math, stats, finance, and data manipulation. It supports matrix operations, and user-defined functions, enhancing automation and analysis within Microsoft Office and LibreOffice environments for data management, financial calculations, an more.
A foundation model-driven whole slide image-scale cell phenotyping method with QuPath integration Resources
Single-cell fluorescence microscopy data analysis
Accurate segmentation of bacterial microscope images using deep learning synthetically generated image data.
DetecDiv provides a comprehensive set of tools to analyze time microscopy images using deep learning methods. The software structure is such that data can be processed either at the command line or using a graphical user-interface. Detecdiv classification models include : image classification and regression, semantic segmentation, LSTM networks to analyze data and image timeseries.