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Quantitative Imaging in Pathology (QuIP) Software Distribution

Description

QuIP is a web accessible toolset designed to support analysis, management, and exploration of whole slide tissue images for cancer research. The QuIP software consists of a set of docker containers, which provide analysis execution and data management backend services, and web applications to load and visualize whole slide tissue images (in OpenSlide supported formats), and visualize and explore the analysis results.

QuIP has several web applications to view whole slide tissue images, view and interact with analysis results, and edit and curate analysis results. caMicroscope, for example, facilitates the interactive exploration of whole slide tissue images and analysis results (overlaid on images as polygons or heatmaps).

Installing and running QuIP

Requirements

  1. docker and docker-compose. You should be able to run docker commands (e.g., pull, run).
  2. git
  3. Port 80 should be open to access and use the web applications remotely.

Cloning the distribution repository

Clone this repository.

git clone https://github.com/SBU-BMI/quip_distro

Building and running the containers

  1. Place yourself in quip_distro folder.
  2. Copy config/httpd.conf.template to config/httpd.conf
  3. Configure httpd.conf with your certificates to enable https.
  4. Build with, "docker-compose -f quip-pathdb.yml build"
  5. Run with, "docker-compose -f quip-pathdb.yml up -d"

Deep learning methods for histopathology image analysis

We have developed a collection of deep learning methods for analysis of whole slide tissue images. The methods include deep learning models for predicting spatial distribution of tumor infiltrating lymphocytes, segmentation and classification of tumor regions, and segmentation of nuclei.

More information about the deep learning models and links to the code repositories can be found at https://github.com/SBU-BMI/histopathology_analysis

Loading images and analysis results to QuIP

Image loader container

The image loader container is deployed when QuIP is installed.

Please see README at https://github.com/SBU-BMI/ImageLoader for user instructions to load images to QuIP.

Heatmap loader container

Results from the tumor infiltrating lymphocyte analysis methods and the tumor segmentation methods are probability maps. The probability maps can be loaded to QuIP as heatmaps using the heatmap loader container, which is deployed when QuIP is installed.

Please see README at https://github.com/SBU-BMI/uploadHeatmaps for user instructions to load heatmaps to QuIP.

Segmentation results loader container

The segmentation results container is deployed, when QuIP is installed. Nucleus segmentation resuilts can be loaded to QuIP using this container.

Please see README at https://github.com/SBU-BMI/SegmentationLoader for user instructions to load segmentation results to QuIP.

Support and Questions

For questions, comments, or any other discussion, please see the caMicroscope discussion forum.

PathDB

To use PathDB, use quip-pathdb.yml instead of caMicroscope.yml.

Running QuIP with PathDB (https://github.com/SBU-BMI/PathDB):

  1. place yourself in quip_distro folder.
  2. copy config/httpd.conf.template to config/httpd.conf
  3. configure httpd.conf with your certificates to enable https.
  4. build with, "docker-compose -f quip-pathdb.yml build"
  5. run with, "docker-compose -f quip-pathdb.yml up -d"

The default login for pathdb is admin with password bluecheese2018. Please change this password before exposing this service to the internet.

Using Keycloak as a self-contained Identity Provider

Alternatively, you can use kc_caMicroscope.yml for a keycloak configuration.

  • Set up Keycloak (covered by docker compose kc_caMicroscope.yml)
  • Set up realm
    • Add realm called ‘camic’
    • All following steps happen in this realm.
  • Set up client
    • Clients -> Add Client
    • Set client_id to camicroscope-test.
    • Openid connect with mostly default settings, but set client authentication to on
    • Once saved, Under the credentials tab, get the client secret
    • Add the client secret to config/keycloak_login.html for client_secret.
  • Add users
    • Users -> add user
    • Make sure to add an email to match user documents in mongo.
    • Set a password under credentials -> add password