Open-source python package for the extraction of Radiomics features from 2D and 3D images and binary masks. Support: https://discourse.slicer.org/c/community/radiomics

Resources for phase recovery (also called phase imaging, phase retrieval, or phase reconstruction)

BART: Toolbox for Computational Magnetic Resonance Imaging

PyTorch library for solving imaging inverse problems using deep learning

Scientific computing library for optics, computer graphics and visual perception

Modular and scalable computational imaging in Python with GPU/out-of-core computing.

A curated list of resources on holographic displays.

Rank Minimization for Snapshot Compressive Imaging (TPAMI'19)

Scientific Computational Imaging COde

Official Demo Code for "Unlocking the Performance of Proximity Sensors by Utilizing Transient Histograms"

(Tensorflow Version) D-Flat is a forward and inverse design framework for flat optics. Although specially geared for the design of metasurface optics, it may be used for any end-to-end imaging and sensing task.

A Julia project demonstrating the fast f-k migration algorithm.

Plug-and-play Algorithms for Large-scale Snapshot Compressive Imaging (CVPR 2020, Oral)

DFlat is a forward and inverse design framework for flat optics. Although specially geared for the design of metasurface optics, it may be used for any end-to-end imaging and sensing task.

Deep Learning for Video Compressive Sensing

Compressed Sensing: From Research to Clinical Practice with Data-Driven Learning

Image-to-image regression with uncertainty quantification in PyTorch. Take any dataset and train a model to regress images to images with rigorous, distribution-free uncertainty quantification.

[CVPR'19] End-to-end Projector Photometric Compensation

Keras Implementation of the paper Residual Feature Distillation Network for Lightweight Image Super-Resolution

This repository contains Matlab scripts and functions for single-pixel imaging