Image segmentation software tools | Mass spectrometry imaging analysis
Mass Spectrometric Imaging (MSI) is a molecular imaging technique that allows the generation of 2D ion density maps for a large complement of the active molecules present in cells and sectioned tissues. Automatic segmentation of such maps according to patterns of co-expression of individual molecules can be used for discovery of novel molecular signatures (molecules that are specifically expressed in particular spatial regions).
A mass spectrometry imaging toolbox for statistical analysis. Cardinal is an R package that implements statistical and computational tools for analyzing mass spectrometry imaging datasets, including methods for efficient pre-processing, spatial segmentation, and classification.
A series of tools written in C++ that allows you to segment your mass spectrometry imaging dataset into regions with similar molecular signatures. The software allows for user input at each step of the process and returns the regions as well as the associated molecular signatures. It is composed of two dynamic libraries and a series of executables using the libraries as a base.
Captures the mass spectrometry (MS) lesion spatial distribution and identifies lesions regardless of their orientation, shape or size. RMNMS detects MS lesions using a training library containing T2-weighted (T2W) and FLAIR images along with manual T2W lesion masks. Moreover, it assists users in the detection of presence of lesions as lesion-wise measures.
Segments nearly elliptic objects via parametric active contour. E-Snake applies an active contour (named snake) segmentation method by using exponential splines as basis functions to represent the outline of the shape. This ImageJ plugin emulates elliptical and circular shapes and can produce an approximation of any closed curve in the plane. These proprieties can be useful to delineate cross sections of cylindrical-like conduits and to outline blob-like objects.
Serves for automated detection of tumour heterogeneity in matrix-assisted laser desorption ionization-image mass spectrometry (MALDI IMS experiments). 'Divisive ik-means algorithm for MALDI IMS' allows users to discover squamous cell carcinoma and keratinized stratified squamous epithelium.
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