Harmonise README + clean LICENSE clause

LICENSE

@@ -11,9 +11,4 @@ Copyright 2018 Alina Bendinger, Martin Storath
    distributed under the License is distributed on an "AS IS" BASIS,
    WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
    See the License for the specific language governing permissions and
-   limitations under the License.
-
-   Additionally, if this code is used in any scientific publication, 
-   the following paper shall be cited:
-        A. Bendinger, C. Debus, C. Glowa, C. Karger, J. Peter, M. Storath. 
-        Bolus arrival time estimation in dynamic contrast-enhanced MRI of small animals based on spline models. 2018
+   limitations under the License.

README.md

@@ -1,31 +1,77 @@
-# Bolus arrival time estimation for DCE-MRI signals (DCEBE)
+# DCEBE — Bolus arrival time estimation for DCE-MRI signals
 
-## Description
-This Matlab code estimates the bolus arrival time (BAT) of DCE-MRI signals.
-It is particularly intended to work with signals that do not have a fast upslope
-as it is often the case for data of small animals.
-The proposed method employs a spline-based approximation model.
-Parameter estimation is done by generalized cross validation.
+[![PyPI](https://img.shields.io/pypi/v/dcebe.svg)](https://pypi.org/project/dcebe/)
+[![Python](https://img.shields.io/pypi/pyversions/dcebe.svg)](https://pypi.org/project/dcebe/)
+[![License: Apache-2.0](https://img.shields.io/badge/license-Apache--2.0-blue.svg)](LICENSE)
+[![CI](https://github.com/mstorath/DCEBE/actions/workflows/ci.yml/badge.svg)](https://github.com/mstorath/DCEBE/actions/workflows/ci.yml)
+[![MATLAB](https://img.shields.io/badge/MATLAB-supported-orange.svg)](#matlab)
+[![View DCEBE on File Exchange](https://www.mathworks.com/matlabcentral/images/matlab-file-exchange.svg)](https://de.mathworks.com/matlabcentral/fileexchange/69526-dcebe)
 
-A detailed documentation of the method is given in
-the paper A. Bendinger, C. Debus, C. Glowa, C. Karger, J. Peter, M. Storath,
-[Bolus arrival time estimation in dynamic contrast-enhanced MRI of small animals based on spline models,](https://doi.org/10.1088/1361-6560/aafce7)
-Physics in Medicine & Biology, Volume 64, Number 4, 2019. 
-[preprint link](https://arxiv.org/pdf/1811.10672.pdf). [![View DCEBE on File Exchange](https://www.mathworks.com/matlabcentral/images/matlab-file-exchange.svg)](https://de.mathworks.com/matlabcentral/fileexchange/69526-dcebe)
+Spline-based estimator for the bolus arrival time (BAT) of DCE-MRI signals — particularly intended for signals without a fast upslope, as is typical for small-animal data. Parameters are selected via generalised cross-validation.
 
 <img src="docs/example.png" width="80%">
 
+## Paper
+
+> A. Bendinger, C. Debus, C. Glowa, C. Karger, J. Peter, M. Storath.
+> [*Bolus arrival time estimation in dynamic contrast-enhanced MRI of small animals based on spline models.*](https://doi.org/10.1088/1361-6560/aafce7)
+> Physics in Medicine & Biology 64(4), 2019. [preprint](https://arxiv.org/pdf/1811.10672.pdf).
+
 ## Quickstart
-- Run "DCEBE_install.m" or add subfolders manually to Matlab path 
-- Run a demo script from the demos folder, e.g. "DCEBE_demo.m"
+
+### Python
+
+```bash
+pip install dcebe
+```
+
+```python
+import numpy as np
+from dcebe import estimate_bat
+
+# y: (N,) or (N, M) array of DCE-MRI signals
+result = estimate_bat(y, search_interval=(10, 30))
+
+# 1-based BAT in sample units; convert to seconds via:
+bat_sec = (result.bat - 1) * delta_t
+```
+
+The package is pure Python (NumPy + SciPy); no compiled wheels, no Rust, no MATLAB runtime required.
+See [`README_PYTHON.md`](README_PYTHON.md) for the full Python API, including
+the `EstimateResult` fields, and [`demos_py/`](demos_py/) for usage examples.
+
+### MATLAB
+
+The original MATLAB reference implementation is in this same repository:
+
+1. Run `DCEBE_install.m` (or add subfolders manually to the MATLAB path).
+2. Run a demo from the `demos/` folder, e.g. `DCEBE_demo.m`.
 
 ## How to cite
-The method is described in the paper
 
-- A. Bendinger, C. Debus, C. Glowa, C. Karger, J. Peter, M. Storath,
-[Bolus arrival time estimation in dynamic contrast-enhanced MRI of small animals based on spline models](https://doi.org/10.1088/1361-6560/aafce7)
-Physics in Medicine & Biology, Volume 64, Number 4, 2019
+If you use this software, please cite the paper above. GitHub's "Cite this repository" button on the repo page reads the `version` and `date-released` fields from [`CITATION.cff`](CITATION.cff) and renders BibTeX/APA.
+
+## See also
+
+Sibling projects from the same research program on variational methods for signal and image processing:
+
+- [Pottslab](https://github.com/mstorath/Pottslab) — multilabel image segmentation via the Potts / piecewise-constant Mumford-Shah model
+- [L1TV](https://github.com/mstorath/L1TV) — exact L1-TV regularisation of real- or circle-valued signals
+- [CSSD](https://github.com/mstorath/CSSD) — cubic smoothing splines for signals with discontinuities
+- [MumfordShah2D](https://github.com/mstorath/MumfordShah2D) — edge-preserving image restoration via the Mumford-Shah model
+- [CircleMedianFilter](https://github.com/mstorath/CircleMedianFilter) — fast median filtering for phase or orientation data
+
+## Acknowledgement
+
+Thanks to T. Driscoll for sharing his code for [computing finite difference weights](https://de.mathworks.com/matlabcentral/fileexchange/13878-finite-difference-weights).
+
+## License
+
+Released under the Apache License 2.0. See [LICENSE](LICENSE).
+
+---
 
+### Project history
 
-## Acknowledgement 
-Thanks to T. Driscoll for sharing his code for [computing finite difference weights.](https://de.mathworks.com/matlabcentral/fileexchange/13878-finite-difference-weights)
+The Python re-implementation of this codebase was generated from the original MATLAB reference by a Claude coding agent in 2026.
+See [`PORTED_BY.md`](PORTED_BY.md) for full attribution.