https://github.com/mstorath/dcebe
Estimation of bolus arrival times for DCE-MRI signals
https://github.com/mstorath/dcebe
bolus-arrival-time dce-mri splines
Last synced: 9 months ago
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Estimation of bolus arrival times for DCE-MRI signals
- Host: GitHub
- URL: https://github.com/mstorath/dcebe
- Owner: mstorath
- License: other
- Created: 2018-11-05T13:05:17.000Z (over 7 years ago)
- Default Branch: master
- Last Pushed: 2025-01-10T10:02:25.000Z (over 1 year ago)
- Last Synced: 2025-01-10T11:23:21.876Z (over 1 year ago)
- Topics: bolus-arrival-time, dce-mri, splines
- Language: MATLAB
- Homepage:
- Size: 235 KB
- Stars: 3
- Watchers: 1
- Forks: 1
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# Bolus arrival time estimation for DCE-MRI signals (DCEBE)
## 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.
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). [](https://de.mathworks.com/matlabcentral/fileexchange/69526-dcebe)
## Quickstart
- Run "DCEC_install.m" or add subfolders manually to Matlab path
- Run a demo script 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
## Acknowledgement
Thanks to T. Driscoll for sharing his code for [computing finite difference weights.](https://de.mathworks.com/matlabcentral/fileexchange/13878-finite-difference-weights)