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Project Description

Copyright 2016, Michael Hogg (michael.christopher.hogg@gmail.com)

MIT license - See LICENSE.txt for details on usage and distribution

About

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.

Requirements

  • 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.
Release History

Release History

0.2.0

This version

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0.1.3

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0.1.1

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0.1.0

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TODO: Figure out how to actually get changelog content.

Changelog content for this version goes here.

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File Name & Checksum SHA256 Checksum Help Version File Type Upload Date
BMDanalyse-0.2.0-py2-none-any.whl (789.2 kB) Copy SHA256 Checksum SHA256 py2 Wheel Jun 7, 2016
BMDanalyse-0.2.0.zip (791.0 kB) Copy SHA256 Checksum SHA256 Source Jun 7, 2016

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