Image data correction software tools | Mass spectrometry imaging analysis
Mass spectrometry Imaging (MSI) data contains structural information, where similar mass spectra come from the same object. However, during the acquisition, contaminations or other event can cause artifacts requiring software tools for correcting and enhancing quality of the resulting image.
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.
Allows users to analyze and process images captured with NanoSIMS 50 & 50L secondary ion mass spectrometers (Cameca). OpenMIMS is an ImageJ plugin that is developed for biomedical research. This tool is able to open, treat and save stacks of images for up to 7 different isotopes. Image ratios and Hue-Saturation-Intensity (HSI) maps of any combination of isotopes can be displayed. Moreover, it can display all data from any number of Regions of Interest (ROIs) extracted, analyzed and tabulated for single images.
Increases the local contrast of an image. CLAHE uses the contrast limited adaptive histogram equalization to process. The contrast amplification in the vicinity of a given pixel value is delivered by the slope of the transformation function. This ImageJ plugin has three main parameters: block size, histogram and max slope.
Presents an improved data analysis pipeline based on a new peak picking method for exploring imaging mass spectrometry data. EXIMS consists of five consecutive main steps: where the first step involves spectra preprocessing. Then, Sliding Window Normalization (SWN) is used to normalize the spectra and limit the influence of high intensity peaks. Third, image de-noising and contrast enhancement are used to improve the visualization of intensity images. Fourth, peak picking is performed by processing the individual intensity images. Finally, intensity images are clustered using the fuzzy cmeans clustering algorithm.
Assists users with the detection of peaks associated with non-realistic spatial distributions. SPUTNIK provides a series of filters which aim to select meaningful and informative peaks, given the information about the signal source. It offers an estimation of split peaks, a correlation-based filter, a pixel count-based filter and a series of tests based on complete spatial randomness.
Serves for matrix-assisted laser desorption/ionization (MALDI) imaging. MITICS is composed of MITICS Image for data processing and images reconstruction and MITICS control for data acquisition. This tool is workable with all type of data whatever the instrument used for both data acquisition when necessary. It uses two different interfaces: one to load all the spectra from each run into a single database, and the second to reconstruct and display interactively the molecular images of interest.
Serves for interactive and in-depth analysis of mass spectrometry imaging data. MassImager contains three subsystems: MassImager Solution, MassImager Visualization and MassImager Intelligence. The core design is aimed at user-friendly design, high throughput, instrument-independence, interactive visualization, various multivariate statistical analysis and pattern recognition of large mass spectrometry imaging (MSI) dataset. The tools provided by the MassImager solution can be classified in two categories: visual processing and image analysis.