GUI for Multivariate Image Analysis of 4-dimensional data 1.0

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.

Requirements:	No special requirements
Platforms:	Matlab
Keyword:	Added,  Classification,  Details,  Extensive,  Guide,  Loadings,  Memory,  Refer
Users rating:	0/10