GFAP classification

Published: 07-04-2017| Version 1 | DOI: 10.17632/3jz5zwnmmr.1
Contributor:
Aurora Campo

Description

Matlab application for classification of glioma tumours based on GFAP immunostaining of histological samples.

Files

Steps to reproduce

You must load a table to be classified in substitution to the "prediction" table loaded in the classifier by default. To create your own prediction table, you must run the GFAP segmentation first to extract the features and then create the indexes using the subset size as reference area. NOTE: Training performed on canine glioma tissue.