Tool to analyse regional changes in a time series of 2D medical images.
Copyright 2016, Michael Hogg (firstname.lastname@example.org)
MIT license - See LICENSE.txt for details on usage and distribution
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.
Written in pure Python using PyQt/PySide, pyqtgraph, numpy, matplotlib and pillow. Should work on any platform, but has only been tested on Windows.
- Python 2.7
- PyQt >= 4.11
- pyqtgraph >= 0.9.10
- numpy >= 1.9
- matplotlib >= 1.4
- pillow >= 3.0
NOTE: All these requirements are available within the Anaconda Python distribution
Instructions for use
- 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.
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Hashes for BMDanalyse-0.2.0-py2-none-any.whl