Data processing algorithms for tomography: https://algotom.readthedocs.io

Imagej macro to calculate the MTF based on a knife edge measurement

A Python-based 3D CT Simulation library for single and dual energy X-ray image generation. This library is designed to aid in the development and testing of single / dual energy CT based object detectors for airport baggage screening and other CT imaging applications.

MBIRJAX is a Python package for Model Based Iterative Reconstruction (MBIR) of images from tomographic data.

C++ implementation of several image contrast enhancement techniques for clinical and normal images.

ADJUST: A Dictionary-Based Joint Reconstruction and Unmixing Method for Spectral Tomography

Source code for "Detail Restoration and Tone Mapping Networks for X-Ray Security Inspection."

A collection of C++ source code modules for forward and inverse simulations of Unified Tomographic Reconstruction.

CMInject: A framework for particle injection trajectory simulations

Solid-state hybrid detectors with hexagonal sampling.

Python tool for Simulation of Phase Contrast Imaging and reconstruction of Talbot-Lau images.

A FastAPI-based service for X-ray image enhancement using RealESRGAN. Supports DICOM and standard images with preprocessing, super-resolution inference, and optional CLAHE postprocessing.

Deep Learning and AI Enthusiasts to contribute to improving COVID-19 detection using just Chest X-rays.

Convolutional Neural Network Architecture to classify Bone Fractures from X-Ray Images

Code for generating deep learning data through X-ray tomography for object detection

EGSnrc expansion for the simulation of X-ray grating interferometry

Code for applying hyperspectral data reduction in deep learning

Developing an X-RAY ray tracer

MIEP - A Time-Resolved X-Ray Image Evaluation Program. To cite this Original Software Publication: https://www.sciencedirect.com/science/article/pii/S2352711021000509

This Google Colab script implements a Convolutional Neural Network to classify chest X-ray images for pneumonia detection, featuring data preparation, model training, performance evaluation, and result visualization.