generated from fastai/nbdev-template
-
Notifications
You must be signed in to change notification settings - Fork 16
Commit
This commit does not belong to any branch on this repository, and may belong to a fork outside of the repository.
- Loading branch information
Sathiesh Kaliyugarasan
authored
Aug 27, 2023
1 parent
388f80e
commit 4cb3897
Showing
1 changed file
with
30 additions
and
0 deletions.
There are no files selected for viewing
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
Original file line number | Diff line number | Diff line change |
---|---|---|
@@ -0,0 +1,30 @@ | ||
# Multi-Center CNN-based spine segmentation from T2w MRI using small amounts of data | ||
The source code, designed to reproduce our test results and facilitate training and running inference on your own data. | ||
The trained weights and exported learners are available on [Huggin Face](https://huggingface.co/skaliy/spine-segmentation). | ||
|
||
## Getting started | ||
### Quick Start | ||
Yyou can run the notebooks directly in Google Colab. | ||
|
||
### Local Setup (Optional) | ||
1. Clone this repository: | ||
```bash | ||
git clone https://github.com/MMIV-ML/fastMONAI | ||
``` | ||
2. Install fastMONAI by following the instructions provided [here](https://github.com/MMIV-ML/fastMONAI/tree/master). | ||
3. (<b>Optional</b>) Run the `00-spine-segmentation-training-evaluation.ipynb` notebook to train your own model or to reproduce the test results reported in our paper. | ||
4. Run the `01-spine-segmentation-inference.ipynb` or `inference_script.py` to perform inference with the trained model on own data | ||
|
||
If you choose to use `inference_script.py` | ||
- Make the script executable using the following command in the terminal: | ||
```bash | ||
chmod +x inference_script.py | ||
``` | ||
- Run the script by executing the following command in the terminal: | ||
```bash | ||
python inference_script.py IMG_PATH | ||
``` | ||
|
||
## Research PACS | ||
Our spine segmentation application deployed in the research PACS system at our hospital: | ||
![](figs/research_pacs.png) |