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A single-layer Random Forest model for voxel classification (volume segmentation). https://hms-idac.github.io/VoxelClass…
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A single-layer Random Forest model for voxel classification (volume segmentation). This code is based on https://github.com/HMS-IDAC/PixelClassifier, with straightforward extensions to 3D, and a bit more parallelization. The main scripts are: voxelClassifierTrain, used to train the model, and voxelClassifier, used to segment volumes after the model is trained. See those files for details and parameters to set. Labels/annotations can be created with VolumeAnnotationBot, available at https://www.mathworks.com/matlabcentral/fileexchange/64718-volumeannotationbot A sample dataset for a running demo is available at https://www.dropbox.com/s/zzjzpvpxro5dgd4/DataForVC.zip?dl=0 (Subset of original data acquired by Michael Weber, https://www.linkedin.com/in/webermic/, at the Nikon Imaging Center, http://nic.med.harvard.edu) This code uses 3-D steerable filters for feature detection, developed by Francois Aguet, available at http://www.francoisaguet.net/software.html It also uses code for platonic solid vertices (in computing offset features), adapted from code by Kevin Mattheus Moerman: https://www.mathworks.com/matlabcentral/fileexchange/28213-platonic-solid Dependency: this software requires the bfmatlab toolbox to read stacks, available at http://downloads.openmicroscopy.org/bio-formats/5.3.4/ Developed by: Marcelo Cicconet marceloc.net