This project includes an analysis of a database of patients with brain metastases from the Bratz 2023 database. In this project we will perform image processing and segmentation of brain metastases/glioma tumors from MRI brain scans of patients.
In the heart of this project lies A deep learning model of segmentation using a transformer network for each patient at each point in time when scanned with T1, T2, FLAIR and T1-contrast enhanced scans. We would like to understand which method gives us the best performance.
We would like to have following information: identification of the number of metastases, the volume of the metastases and their location. In addition, we would like to receive the detailed information for each patient in a format that will allow us to enter the information in a computerized database. Also, a user-friendly UI tool will be developed in order to allow us to analyze segmentation from MRI scans for additional patients who are not in the current database.
Pull requests are welcome. For major changes, please open an issue first to discuss what you would like to change. Please make sure to update tests as appropriate.
notise the "mission.txt" file in "public" directory to see futre features which planned to be added!.
- Fork the repository to your own Github account.
- Clone the project to your machine.
- Create a branch locally with a succinct but descriptive name.
- Commit changes to the branch.
- Following any formatting and testing guidelines specific to this repo.
- Push changes to your fork.
- Open a Pull Request in my repository.
- Dor Liberman (dorlib)
- Shachar Gabbay (gshachar12)
If you have any questions or feedback, I would be glad if you will contact me via mail.
This project was created for educational purposes, for personal and open-source use.
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