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Jupyter notebook with Python-based workflow for co-registration of radiographic imaging (MRI/CT etc.) with digitized pathology images, and mapping annotations from pathology onto imaging.

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Overview

This notebook provides an interactive workflow to load in a radiographic imaging volume (MRI, CT, etc.) with a corresponding digitized pathology image, and go through co-registration to map one onto the other. Functionalities include selecting corresponding sections, basic image manipulation and scaling as pre-processing steps, as well as selecting corresponding landmarks to run a deformable co-registration between the modalities. The deformation can then be applied to any annotation to map it from one to the other (e.g. map cancer annotation from pathology image onto MR image) within the noteboo. Results are visualized and fully editable and updatable within the notebook workflow.

References

If you make use of this implementation, please cite the following paper:

Antunes, JT, Viswanath, SE, Brady, JT, Crawshaw, B, Ros, P, Steele, S, Delaney, CP, Paspulati, RM, Willis, JE, Madabhushi, A, "Coregistration of Preoperative MRI with Ex Vivo Mesorectal Pathology Specimens to Spatially Map Post-treatment Changes in Rectal Cancer Onto In Vivo Imaging: Preliminary Findings", Acad Radiol, 2018 Jul;25(7):833-841.

Prerequisites

The below software and configurations will be needed to execute the notebooks:

  • Docker
    • Update docker with 8 gigs of memory
  • git

Getting started with Rad Path Fusion

Running with docker

First clone this repository

git clone https://github.com/Theta-Tech-AI/radpathfusion.git

Second, we will quickly configure the docker memory

Docker Setup:

  1. Open Docker Destop
  2. Open settings
  3. Click on resources as seen on the below screen shot
  4. Move the memory limit to 8 GB Docker Configuration

Lastly, we will run the docker image using either:

  1. docker-compose
  2. docker run

docker-compose

Run the following commands to start the docker container

cd docker
docker-compose up

docker run

With this step, you don't need to clone the url. Run the following commands to start the docker container

docker rm radxtools/radpathfusion-examples
docker pull radxtools/radpathfusion-examples
docker run -d -p 3000:3000 --name radpathfusion-examples radxtools/radpathfusion-examples

Tutorials

Once the docker image is up and running. You can view our notebooks. You can get started with the notebook to learn how to use the package. You should start with notebooks/Rad Path Fusion Final.ipynb

The notebooks can be viewed by opening the browser and visting the url http://localhost:3000

A walk through of the notebook with screen shots can be found here

Contribution Guide:

Please follow google style formatting for docstrings

Bugs and Feature Request

Please submit bugs and features to our github page.

Pull Requests

Create a issue on our board. Create a pull request with your changes. Tag your changes with the issue number (commit message should have issue number). Someone from the team will review your request and merge your changes for the next release.

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Jupyter notebook with Python-based workflow for co-registration of radiographic imaging (MRI/CT etc.) with digitized pathology images, and mapping annotations from pathology onto imaging.

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