/qStudy

Annotation portal for medical images made using magic of 3d slicer, VNC and web apps.

Primary LanguageJavaScript

qStudy

A web app to conduct studies for medical images made using magic of 3d slicer, VNC and web apps.

Installation

To proceed with installation docker and docker-compose are required.

Build the docker image from the docker-compose.yml file as follows:

docker-compose build

Usage

  1. Create a data direcotry and move all the DICOM files (.nii.gz files) to that data folder. Also, add db_nii.csv file to data directory with UID and DICOM file path for each data file inside the data directory.

    A sample of the db_nii.csv file should look like

    uid,filepath
    1.2.3.4.5,/root/data/1.2.3.4.5.nii.gz
    

    We mount this data volume to the data directory inside the docker container.

  2. Create and run a docker container based on the docker image we build.

    Run with logs.

    docker-compose up.
    

    Run in the detached mode.

    docker-compose up -d
    
  3. Once docker container is up and running, 3d slicer can be accessed via VNC viewer at 127.0.0.1:5900.

    VNC Viewer

    Note: The default password for VNC viewer is vncpassword@123 which can be configured in docker-compose.yml before building a docker image.

  4. Open a new tab in the terminal and interact with the Flask API. We can load data into the 3d slicer tool as follows:

    Load DICOM file

    Note: In case of a failure or issues faced, perform docker-compose down and docker-compose up.