Metadata-Version: 2.1
Name: c-pmat
Version: 0.2.0
Summary: A short description of your package
Author-email: Priya Narayanan <priya.narayanan@icr.ac.uk>
Project-URL: Homepage, https://github.com/yourusername/c-pmat
Project-URL: Bug Tracker, https://github.com/yourusername/c-pmat/issues
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.8
Description-Content-Type: text/markdown
License-File: LICENSE.txt

# PMAT : PSR STAIN PREPROCESSING WORKFLOW 

This is a interactive user interface, allowing user to easily
generate tiles and the corresponding metadata from the whole slide images.

## Understanding data preparation

In this section we will summarize the organization of directory structure to enable 
the end user extract the information needed to directly interact with the annotations which comes as a string
or different names provided by the pathologists (generic).

In the below example we have a first whole slide image with 6 regions of interest and they are named as 
ROI1, ROI2, .... ROI6 respectively and the second whole slide image with 3 regions of interest
ROI1, ROI2, ROI3 respectively. These annotations are free hand polygon annotations drawn on the tissue by the 
pathologists to infer the changes in the extracellular matrix components with respect to the individual ROI and 
cater for inter-tumour and intra-tumour heterogeneity and its implication of features at slide and ROI levels.

<p align="center">
  <img src="screenshot_images/dp1.png" width="850" title="WSI-1">
  <img src="screenshot_images/dp2.png" width="850" title="WSI-2">
</p>


Currently, we have the support for the annotations performed by the pathologists using Imagescope on the
PSR stained whole slide images.
if you have annotations, it will retain the ROIs with respect to the individual slide automatically and extract the tiles
corresponding to each ROI.

Note: This code can be generically used for other brightfield images and extraction of the annotations performed on Imagescope.

## ROI stitching at low resolution

It also helps to restitch the ROI's at a lower resolution for sanity check so it can be further processed by TWOMBLI


## Extraction of features within PMAT framework
