BioImage-IT

BioImageIT is a France-BioImaging project. It aims at providing good IT practices, recipies and tools for imaging facilities to deploy interoperable image processing and data analysis solutions.

BioImageIT is also a set of tools to facilitate the installation of image management and analysis facility

OS: Windows, Mac OSX, Linux
Download: https://bioimageit.github.io/

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Motion saliency map estimation software

This software estimates motion saliency maps from video frames. Candidate salient regions are first extracted from motion boundaries. Saliency is then estimated with an optical flow inpainting step. The idea is that if the flow reconstructed in candidate regions from the surrounding flow is very different from the flow present originally, the region should be salient with respect to motion

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Motion saliency detection software

This software detects whether motion saliency is present for each frame of a video. In a first step, the dominant motion (that is supposed to correspond to camera motion) is compensated. In a second step, saliency detection is realised with a convolutional neural network. The 4 variants are RFS-Motion2D, RFS-DeepDOM, WS-Motion2D and WS-DeepDOM.

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AiryscanJ

AiryscanJ is a high resolution image reconstruction from array detector. High resolution images can be reconstructed by using detector linear combinations or deconvolution.

Image type: 2D/3D
Language: C/C++, ImageJ/Fiji
OS: Windows, Mac OSX
Download: GitLab

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Atlas

ATLAS is a spot detection method. The spots size is automatically selected and the detection threshold adapts to the local image dynamics. ATLAS relies on the Laplacian of Gaussian (LoG) filter, which both reduces noise and enhances spots. A multiscale representation of the image is built to automatically select the optimal LoG variance.

Image type: 2D
Language: C/C++
OS: Linux, Mac OSX
Try online: Allgo
Download: GitLab

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Backwarping

Warp sequence with parametric motion model (1995-2013) C/C++

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C-CRAFT

Vesicle segmentation and background estimation (2014) C/C++, Java

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Cryo-Seg

Segmentation of tomograms in cryo-electron microscopy (2010)

Flowscope

3D flow field estimation and assessment for live cell fluorescence microscopy (2019)

Image type: 3D + t
Language: C/C++
OS: Windows, Linux, Mac OSX
Try online: Allgo

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Flux estimation

Particle and intensity flux estimation (2015) C/C++

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GenLoc3D

3D high-precision gene localization algorithm in cell nuclei (2014-2015)     Java (ImageJ)

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GcoPS

3D Colocalization analysis (2017) Java

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HotSpotDetection

3D Robust detection of fluorescence accumulation over time in video-microscopy (2007-2008) C/C++

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HullkGround

3D Convex Hull for background subtraction (2008-2009) C/C++, Java

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KLTracker

Track vesicle and POI in image sequences (2012) C/C++

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Motion2D

Estimate 2D parametric motion model (2012)C/C++

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MS-Detect

Detecting moving objects in image sequences by background subtraction (2008/2011) C/C++

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ND-SAFIR

ND-SAFIR is a software for denoising n-dimentionnal images especially dedicated to microscopy image sequence analysis. It is able to deal with 2D, 3D, 2D+time, 3D+time images have one or more color channel. It is adapted to Gaussian and Poisson-Gaussian noise which are usually encountered in photonic imaging. Several papers describe the detail of the method used in ndsafir to recover noise free images.

Image type: 2D, 3D, 2D+time, 3D+time
Language: C/C++, Java, matlab
OS: Linux, Windows, Mac OSX
Try online: Allgo
Download: GitLab

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OpticalFlow

Optical flow (2012) C/C++

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OWF

Non-local means and optimal weights for noise removal (2017) Matlab  and C/C++

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PBED

Patch-Based Event Detection (2009) C/C++

QuantEv

Spatio-temporal distribution analysis (2017) C/C++, Java

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THOTH

Classification of particle trajectories into three types of diffusions (2017) Matlab

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CPAnalysis

Change point detection along particle trajectories (2018) Matlab

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TubuleJ

Toolbox to process electron cryo-microscope images of vitrified microtubules (2009) Java (imageJ)

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DeepFinder

DeepFinder is an original deep learning approach to localize macromolecules in cryo electron tomography images. The method is based on image segmentation using a 3D convolutional neural network.

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DenseMapping

DenseMapping software allows to estimate the diffusion and drift parameters attached to moving biomolecules within cells from 2D/3D individual trajectories.

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