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# -*- coding: utf-8 -*- | ||
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# Copyright (C) 2013 Michael Hogg | ||
# Copyright (C) 2016 Michael Hogg | ||
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# This file is part of BMDanalyse - See LICENSE.txt for information on usage and redistribution | ||
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__version__ = '0.1.4' | ||
__version__ = '0.2.0' |
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REM Test build | ||
python setup.py sdist bdist_wheel | ||
REM Upload to PyPi | ||
REM python setup.py sdist bdist_wheel upload | ||
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========== | ||
BMDanalyse | ||
========== | ||
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.. image:: https://img.shields.io/pypi/v/bmdanalyse.svg | ||
:target: https://pypi.python.org/pypi/bmdanalyse/ | ||
:alt: Latest PyPI version | ||
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.. image:: https://img.shields.io/pypi/dm/bmdanalyse.svg | ||
:target: https://pypi.python.org/pypi/bmdanalyse/ | ||
:alt: Number of PyPI downloads | ||
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Copyright 2016, Michael Hogg (michael.christopher.hogg@gmail.com) | ||
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MIT license - See LICENSE.txt for details on usage and distribution | ||
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----- | ||
About | ||
----- | ||
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A graphical tool used for the regional analysis of a time series of 2D medical images. This was created for the analysis of virtual x-rays, created by companion tools `bonemapy`_ and `pyvXRAY`_ from the results of a computer simulation. Intended to be used to evaluate the bone gain / loss in a number of regions of interest (ROIs) over time, typically due to bone remodelling as a result of stress shielding around an orthopaedic implant. | ||
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Written in pure Python using PyQt/PySide, pyqtgraph, numpy, matplotlib and pillow. Should work on any platform, but has only been tested on Windows. | ||
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.. _bonemapy: https://github.com/mhogg/bonemapy | ||
.. _pyvxray: https://github.com/mhogg/pyvxray | ||
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------------ | ||
Requirements | ||
------------ | ||
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* Python 2.7 | ||
* PyQt >= 4.11 | ||
* pyqtgraph >= 0.9.10 | ||
* numpy >= 1.9 | ||
* matplotlib >= 1.4 | ||
* pillow >= 3.0 | ||
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**NOTE:** All these requirements are available within the Anaconda Python distribution | ||
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-------------------- | ||
Instructions for use | ||
-------------------- | ||
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- Load a time series of 2D medical images (in image format such as bmp, png etc). All images should be grayscale and of the same size. | ||
- Use the up / down arrows in the Image toolbox to place the images in chronological order. A time series of virtual X-rays is provided in the sampleMedicalImages directory. | ||
- Create some Regions of Interest (ROIs) and run the ROI analysis tool from the Analysis toolbox. A plot will be generated showing the change in the average grayscale value with each ROI over time. | ||
- Run the Image analysis tool from the Analysis toolbox. A contour will be displayed, showing regions of bone loss in blue and bone gain in red. |
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