Image reconstruction

FluoGAN is a fluorescence image deconvolution software combining the knowledge of acquisition physical model with gan. It takes a fluctuating sequence of blurred, undersampled and noisy images of the sample of interest  fixed sample as input from wide field or confocal and returns a super resolved image.

Voxelytic-Align is a commercial software provided as a service on cloud targetted to electron microscopy reconstruction (alignement, artifact correction...)

Holovibes is a free software dedicated to the calculation of holograms in real-time. Input interferogram data can be grabbed from a digital camera or loaded from files recorded beforehand. Massive amounts of data can be handled robustly at high throughput, saved to disk, and visualized in real-time without any risk of frame dropping thanks to the use of several configurable input and output memory buffers.

Main features

Image acquisition from several digital cameras or from data files
Choice of hologram rendering method
Blazing-fast hologram rendering
Real-time computation of spectrograms
Hologram autofocus
Image and video post-processing
High throughput saving to disc of massive datasets
Batch recording and communication with remote instruments via GPIB

Requirements

A PC with at least 8 GB of RAM
Microsoft Windows 7/10 64-bit operating system
A NVidia graphics card (GeForce GTX 700+ series)
NVidia CUDA 9
A supported digital camera, or raw interferogram files

Use case examples

Holographic microscopy
Holographic OCT
Holographic vibrometry
Holographic angiography
Holographic plethysmography

Paintera is a general visualization tool for 3D volumetric data and proof-reading in segmentation/reconstruction with a primary focus on neuron reconstruction from electron micrographs in connectomics. It features/supports:

•  Views of orthogonal 2D cross-sections of the data at arbitrary angles and zoom levels
•  Mipmaps for efficient display of arbitrarily large data at arbitrary scale levels
•  Label data
  •  Painting
  •  Manual agglomeration
  •  3D visualization as polygon meshes
    •  Meshes for each mipmap level
    •  Mesh generation on-the-fly via marching cubes to incorporate painted labels and agglomerations in 3D visualization. Marching Cubes is parallelized over small blocks. Only relevant blocks are considered (huge speed-up for sparse label data).

Paintera is implemented in Java and makes extensive use of the UI framework JavaFX

Deep learning for fluorescence image restoration (denoising, deconvolution). Requires training on your data set but the procedure is described.