Visualization-DMIM
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DICOM 3D Medical Image Modeling (DMIM)
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.
- 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.
- Activate the new DMIM environment by typing:
$ conda activate DMIM
- Clone the repository:
$ git clone https://github.com/nis1/Visualization-DMIM.git
- Install MongoDB:
$ conda install mongodb
- Enter the repository folder, and install the requirements:
$ pip install -r requirements.txt
- Open new terminal window and start MongoDB:
$ mongod
- Finally, run the website from the repository main folder:
$ FLASK_APP=app.py FLASK_DEBUG=1 python -m flask run
- The website should be available at http://localhost:5000/
A successful installation will result in the following index page:
More images from the app
Store and analyze various cases
3D Analysis
Slice Analysis
Draw on slices
References
The X ToolKit: https://github.com/xtk/X
AMI: https://github.com/FNNDSC/ami
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