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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MIPs for PSFs

Description

The macro generates orthogonal projections from bead images along the lateral and axial dimensions which are displayed using a customized look-up-table to color code intensities. A Gaussian curve is fit to the intensity profile of a fluorescent bead image and full-with-at-half-maximum (FWHM) values are extracted, and listed next to theoretical values for comparison. 

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.

Nessys

Description

Nessys: Nuclear Envelope Segmentation System

 

Nessys is a software written in Java for the automated identification of cell nuclei in biological images (3D + time). It is designed to perform well in complex samples, i.e when cells are particularly crowded and heterogeneous such as in embryos or in 3D cell cultures. Nessys is also fast and will work on large images which do not fit in memory.


Nessys also offers an interactive user interface for the curation and validation of segmentation results. Think of this as a 3D painter / editor. This editor can also be used to generate manually segmented images to use as ground truth for testing the accuracy of the automated segmentation method.


Finally Nessys, contains a utility for assessing the accuracy of the automated segmentation method. It works by comparing the result of the automated method to a manually generated ground truth. This utility will provide two types of output: a table with a number of metrics about the accuracy and an image representing a map of the mismatch between the result of the automated method and the ground truth.

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Minimum cost Z surface projection

Description

This plugin detects a minimum cost z-surface in a 3D volume. A z surface is a topographic map indicating the altitude z as a function of the position (x,y) in the image. The cost of the surface depends on pixel intensity the surface is going through. This plugin find the z-surface with the lowest intensity in an image.

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