A single-layer Random Forest model for voxel classification (volume segmentation).


Updated Mon, 04 Dec 2017 06:01:18 +0000

From GitHub

View License on GitHub

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

Cite As

Marcelo Cicconet (2023). VoxelClassifier (https://github.com/HMS-IDAC/VoxelClassifier), GitHub. Retrieved .

MATLAB Release Compatibility
Created with R2017a
Compatible with any release
Platform Compatibility
Windows macOS Linux

Inspired by: platonic_solid

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!

Versions that use the GitHub default branch cannot be downloaded

Version Published Release Notes

Added image.

To view or report issues in this GitHub add-on, visit the GitHub Repository.
To view or report issues in this GitHub add-on, visit the GitHub Repository.