localtoasty/preprocessing

preProcessing

This repository contains two main scripts for the preProcessing of the Whole Slide Images (WSIs) as an initial step for histopathological deep learning.

1. extractTiles-ws : This script is used to tessellate the WSIs. The main required inputs for this function:

Input Variable name	Description
-s	Path to the WSI folder
-o	Path to the output folder, to save the tiles
--skipws	To skip the tessellation of WSI if annotation is missing. Default value is False.
-px	Size of image patches to analyze, in pixels
-um	Size of image patches to analyze, in microns.
--num_threads	Number of threads to use when tessellating.
--augment	Augment extracted tiles with flipping/rotating.
--ov	The Size of overlappig for extracted tiles. It can be values between 0 and 1.

2. Normalize : This script is used to normalize the extracted tiles using Macenko method. The main required inputs for this function:

Input Variable name	Description
-inputPath	Path to the BLOCKS folder, where the tiles are saved
-outputPath	Path to the output folder, to save the normalized tiles
--sampleImagePath	Path to one sample tile, which it's color distribution will used as a template for all the tiles.

In this script, we are using the Macenko normalization method from https://github.com/wanghao14/Stain_Normalization.git repository.