DeepCell

Description

 

DeepCell is neural network library for single cell analysis, written in Python and built using TensorFlow and Keras.

DeepCell aids in biological analysis by automatically segmenting and classifying cells in optical microscopy images. This framework consumes raw images and provides uniquely annotated files as an output.

The jupyter session in the read docs are broken, but the one from the GitHub are functional (see usage example )

deepcell

Filopodyan

Description

Fiji plugin for detecting, tracking and quantifying filopodia

Tumor Blood Vessels: 3D Tubular Network Analysis

Bioimage Analyst
Developer

In this session, we will implement a simple ImageJ macro to segment and analyze the blood vessel network of a subcutaneous tumor. The analysis is fully performed in 3D, and possible strategies to extract statistics of the network geometry and interactively visualize the results are also discussed and implemented.

MSRC Registration Toolbox

Description

This python toolbox performs registration between 2-D microscopy images from the same tissue section or serial sections in several ways to achieve imaging mass spectrometry (IMS) experimental goals.

This code supports the following works and enables others to perform the workflows outlined in the following works, please cite them if you use this toolbox:

  • Advanced Registration and Analysis of MALDI Imaging Mass Spectrometry Measurements through Autofluorescence Microscopy10.1021/acs.analchem.8b02884

  • Next Generation Histology-directed Imaging Mass Spectrometry Driven by Autofluorescence Microscopy10.1021/acs.analchem.8b02885

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NanoJ

Description

Set of Tools for super resolution microscopy

HAWK

Description

Preprocessing step for high-density analysis methods in super resolution localisation microscopy: it aims at correcting artefacts due to these approaches with based on Haar Wavelet Kernel Analysis.

Chromagnon

Description

Image correction software for chromatic shifts in fluorescence microscopy

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Daybook2

Description

Daybook 2 is the analysis software linked to argoligth slides. It tests the performance of microscopes on various levels: illumination homogeneity, field distortion, lateral resolving power, stage drift, chromatic aberrations, intensity response... It works with various file formats but requires the use of an argolight test slide. 

ConfocalCheck

Description

Assess the performance of the lasers, the objective lenses and other key components required for optimum confocal operation.

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MetroloJ

Description

This plugin allows measuring relevant parameters which helps testing, following and comparing microscopes performances. This is achieved by extracting four indicators out of standardized images, acquired from standardized samples: the estimation of the detector sensitivity, the evaluation of the field illumination homogeneity, the system resolution, and finally the characterization of its spectral registration.