This GUI includes is a set of multivariate image analysis methods for analyzing image data sets acquired at two variables. For example: emission excitation image data, spectral or dynamic (temporal) sequences of images acquired at different depths using microscopy.
Two approaches are included:
1. 2-step two-way MIA using PCA, MCR. MAF and Simplisma. In this method, image sequences as a function of variable1 at fixed variable2 are analyzed by two-way method during the 1st step and then the resulted score images at each variable 2 are combined into a new data set and are analyzed by the same two-way method at the 2nd step.
2. Three-way analysis using Parafac, Tucker,three-way augmented MCR and MAF methods. Nonnegativity constraints are imposed during all three model fitting. All three methods will result in score image and associated loadings as a function of both variables.
Classification is also added.
Please refer to a User Guide for more details.
Test image data set is included.
Memory extensive! Might need to spend some time to get your images into the GUI ? resize, subset or bin for it to work.
Requirements: Image Processing toolbox, PLS_toolbox.
GUI USES LARGE NUMBER OF SUBSET FUNCTIONS. I WAS TRYING NOT TO FORGET TO INCLUDE ALL OF THEM. BUT IF YOU GET AN ERROR MISSING ANY OF THEM, PLEASE E-MAIL ME DIRECTLY.
Kateryna Artyushkova (2021). GUI for Multivariate Image Analysis of 4-dimensional data (https://www.mathworks.com/matlabcentral/fileexchange/9310-gui-for-multivariate-image-analysis-of-4-dimensional-data), MATLAB Central File Exchange. Retrieved .
MATLAB Release Compatibility
Platform CompatibilityWindows macOS Linux
Community Treasure Hunt
Find the treasures in MATLAB Central and discover how the community can help you!Start Hunting!