Metadata-Version: 2.1
Name: psmoe
Version: 0.1.4.5
Summary: A simple module for prostate segmentation of T2-W MRI sequences in Nifti format
Home-page: https://github.com/mpierangeli/prostate_segmentation_moe
Author: Martin Pierangeli
Author-email: marespierangeli@gmail.com
Project-URL: Source, https://github.com/mpierangeli/prostate_segmentation_moe
Keywords: UNet,ML,Prostate,Segmentations
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: numpy>=1.23.5
Requires-Dist: matplotlib>=3.6.2
Requires-Dist: opencv-python>=4.6.0.66
Requires-Dist: nibabel>=5.2.0
Requires-Dist: scipy>=1.9.3
Requires-Dist: gdown>=4.7.3
Requires-Dist: keras>=2.15.0
Requires-Dist: tensorflow>=2.15.0

# Prostate Segmentation MoE

A simple Python module for easy segmentation of the prostate in T2-weighted MRI images in NIfTI format. This module utilizes a mixture of U-Net architectures for segmentation tasks and aims to provide a straightforward solution for users working with prostate MRI data.

## Features

- Segmentation of prostate regions in T2-weighted MRI images.
- Uses a combination of trained U-Net models for accurate and efficient segmentation.
- Supports input in the NIfTI format, a common format for medical imaging.
- Returns 3D masks aswell as the volume estimation.

## Recommended before installation (Windows)

### Install virtualenv if not already
```pip install virtualenv```
### Create a virtual environment
```python -m venv venv```
### Activate it
```venv\Scripts\activate```
- You may need to run ```Set-ExecutionPolicy Unrestricted -Scope Process``` before activation
- If creating your own repository don't forget to ignore the `venv` folder in the `.gitignore` file


## Installation

Install the library using pip:

```pip install psmoe```

## Usage
### Example
Check for `example.py` 
### Scripted Download
You can also download a T2-weighted MRI sequence using the provided function in the example.

## License
This project is licensed under the MIT License - see the LICENSE file for details.


For more details, visit the [GitHub repository](https://github.com/mpierangeli/prostate_segmentation_moe).

