| Name | xai4mri JSON |
| Version |
0.0.1
JSON |
| download |
| home_page | None |
| Summary | xai4mri is designed for advanced MRI analysis using deep learning combined with explainable A.I. (XAI). |
| upload_time | 2024-09-26 23:58:43 |
| maintainer | None |
| docs_url | None |
| author | None |
| requires_python | <3.12,>=3.9 |
| license | MIT License for xai4mri Copyright (c) 2024 Simon M. Hofmann Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. Cite this repository in your publications if you use this code. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. |
| keywords |
transfer-learning
xai
explainable-ai
explanation
interpretation
prediction
mri
smri
3d-conv
deep-learning
structure
brain
t1w
flair
swi
dwi
|
| VCS |
 |
| bugtrack_url |
|
| requirements |
No requirements were recorded.
|
| Travis-CI |
No Travis.
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| coveralls test coverage |
No coveralls.
|
# xai4mri
*Explainable A.I. for MRI research using deep learning.*
## What is `xai4mri`
`xai4mri` is designed for advanced MRI analysis combining deep learning with explainable A.I. (XAI).
It offers the following key functionalities:
- **Data Integration**: Effortlessly import new MRI datasets and apply the models to generate accurate predictions.
- **Model Loading**: load (pretrained) 3D-convolutional neural network models tailored for MRI predictions.
- **Interpretation Tools**: Utilize analyzer tools,
such as [Layer-wise Relevance Propagation (LRP)](https://doi.org/10.1038/s41467-019-08987-4),
to interpret model predictions through intuitive heatmaps.
With **xai4mri**, you can complement your MRI analysis pipeline, ensuring precise predictions and
insightful interpretations.
## Quick-start
```shell
pip install -U xai4mri
```
Get started with `xai4mri` in Python:
```python
import xai4mri as xai
```
Visit the [**documentation**](https://shescher.github.io/xai4mri/), for detailed information.
## Citation
When using `xai4mri`, please cite the following papers:
[`toolbox paper in prep`] and [Hofmann et al. (2022, *NeuroImage*)](https://doi.org/10.1016/j.neuroimage.2022.119504).
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