/Visualization-DMIM

DICOM 3D Medical Image Modeling (DMIM)

Primary LanguageJavaScriptMIT LicenseMIT

DICOM 3D Medical Image Modeling (DMIM)

Nowadays, patients are sent to MRI, PET, and CT scans more than before. Each scan produces a large amount of information of a patient, normally as a set of 2D slices, that will be inspected by a doctor or a technician. The project aims to visualize any DICOM images by creating a 3D model in addition to the classic slice-by-slice inspection.

Demo: https://www.youtube.com/watch?v=Xz3xwpmoMHg

 

Installation

This tutorial uses Conda and PIP. Please make sure to install them before you proceed the next steps.

  1. Create virtual environment with the following instruction:
$ conda create -n DMIM python=3.5.4

“DMIM” is the name of the new environment. Please make sure to install Python 3.5.4, and not other version.

  1. Activate the new DMIM environment by typing:
$ conda activate DMIM
  1. Clone the repository:
$ git clone https://github.com/nis1/Visualization-DMIM.git
  1. Install MongoDB:
$ conda install mongodb
  1. Enter the repository folder, and install the requirements:
$ pip install -r requirements.txt
  1. Open new terminal window and start MongoDB:
$ mongod
  1. Finally, run the website from the repository main folder:
$ FLASK_APP=app.py FLASK_DEBUG=1 python -m flask run
  1. The website should be available at http://localhost:5000/

A successful installation will result in the following index page:

Home Page   

More images from the app

Store and analyze various cases

Store and analyze various cases  

3D Analysis

3D Analysis  

Slice Analysis

Slice Analysis  

Draw on slices

Draw on slices   

References

The X ToolKit: https://github.com/xtk/X

AMI: https://github.com/FNNDSC/ami