| Name | dcmri JSON |
| Version |
0.6.13
JSON |
| download |
| home_page | None |
| Summary | A python toolbox for dynamic contrast MRI |
| upload_time | 2024-11-29 09:12:31 |
| maintainer | None |
| docs_url | None |
| author | None |
| requires_python | >=3.10 |
| license | None |
| keywords |
python
medical imaging
perfusion
mri
|
| VCS |
 |
| bugtrack_url |
|
| requirements |
No requirements were recorded.
|
| Travis-CI |
No Travis.
|
| coveralls test coverage |
No coveralls.
|
dcmri
=====
.. image:: https://github.com/dcmri/dcmri/actions/workflows/pytest-actions.yaml/badge.svg?branch=dev
:target: https://github.com/dcmri/dcmri/actions/workflows/pytest-actions.yaml
.. image:: https://codecov.io/gh/plaresmedima/dcmri/graph/badge.svg?token=DLVVTWQ0HA
:target: https://codecov.io/gh/plaresmedima/dcmri
.. image:: https://img.shields.io/pypi/v/dcmri?label=pypi%20package
:target: https://pypi.org/project/dcmri/
.. image:: https://img.shields.io/pypi/dm/dcmri
:target: https://pypistats.org/packages/dcmri
.. image:: https://img.shields.io/badge/License-Apache_2.0-blue.svg
:target: https://opensource.org/licenses/Apache-2.0
A python toolbox for dynamic contrast MRI
-----------------------------------------
- **Documentation:** https://dcmri.org
- **Source code:** https://github.com/dcmri/dcmri
*Note:* dcmri is under construction. At this stage, the API may still change
and features may be deprecated without warning.
Installation
------------
Install the latest version of dcmri:
.. code-block:: console
pip install dcmri
Typical usage: ROI-based analysis
---------------------------------
.. code-block:: python
import dcmri as dc
# Generate some test data
time, aif, roi, _ = dc.fake_tissue(CNR=50)
# Construct a tissue
tissue = dc.Tissue(aif=aif, t=time)
# Train the tissue on the data
tissue.train(time, roi)
# Check the fit to the data
tissue.plot(time, roi)
.. image:: https://dcmri.org/_images/tissue.png
:width: 800
.. code-block:: python
# Print the fitted parameters
tissue.print_params(round_to=3)
.. code-block:: console
--------------------------------
Free parameters with their stdev
--------------------------------
Blood volume (vb): 0.018 (0.002) mL/cm3
Interstitial volume (vi): 0.174 (0.004) mL/cm3
Permeability-surface area product (PS): 0.002 (0.0) mL/sec/cm3
----------------------------
Fixed and derived parameters
----------------------------
Plasma volume (vp): 0.01 mL/cm3
Interstitial mean transit time (Ti): 74.614 sec
Typical usage: pixel-based analysis
-----------------------------------
.. code-block:: python
# Generate some test data
n = 128
time, signal, aif, _ = dc.fake_brain(n)
# Construct an array of tissues
image = dc.TissueArray((n,n),
aif = aif, t = time,
kinetics = '2CU', verbose = 1)
# Train the tissue array on the data
image.train(time, signal)
# Plot the parameter maps
image.plot(time, signal)
.. image:: https://dcmri.org/_images/pixel_2cu.png
:width: 800
License
-------
Released under the `Apache 2.0 <https://opensource.org/licenses/Apache-2.0>`_
license::
Copyright (C) 2023-2024 dcmri developers
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