ROC estimation using a binomial mixture model - lyngby_batch_bmr

Estimates and displays a number of ROC curves based on a binomial mixture model. Different estimation techniques can simultaneously be investigated by providing the algorithm with the corresponding activation summary images.

The underlying Matlab tool, lyngby_batch_bmr.m, is part of Lyngby, a Matlab Toolbox for the analysis of functional neuroimages. Created by Finn Nielsen and Thomas Kolenda. The wrapper for lyngby_batch_bmr.m was written by Rasmus Olsson. Technical University of Denmark, IMM.

Read more about the Lyngby Toolbox at http://hendrix.imm.dtu.dk/software/lyngby/.

 

See also:

DTU:Toolbox at http://isp.imm.dtu.dk/toolbox/. Lyngby Fiswidgets af http://mole.imm.dtu.dk/LyngbyFiswidgets/ - obsolete

Invocation

java lyngby_batch_bmr 

This starts up the java interpreter and the wrapper, which allows the user to parameterize the lyngby_batch_bmr.m tool. For each method investigated is selected N summary images from replicated experiments. A mask image (could be one of the summary images) is selected to define the voxels of interest.
You need to have set up your environment for java in order for this to work. Further, make sure that Matlab and the Lyngby toolbox can be called from the directory where the tool is called from.

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