quantiphyse 0.9.3.post39

Quantiphyse is a data viewer and analysis platform for volumetric medical imaging data

Quantiphyse

Viewer and data processing for 3D/4D medical imaging data

Overview

Quantiphyse provides tools for modelling and analysis of 3D/4D volumetric data, principally MRI data.

Core features:

• Loading/Saving 3D/4D NIFTI files
• Analysis tools including single/multiple voxel analysis and data comparison
• Generic processing including smoothing, resampling, clustering

Features available via plugins

• Registration, motion correction
• Modelling tools for DCE, ASL, DSC and CEST MRI
• Integration of selected FSL tools

See: http://quantiphyse.readthedocs.org/en/latest/ for full documentation.

License

Quantiphyse is available free under an academic (non-commercial) license. See the LICENSE file for full details, and contact OUI if interested in commercial licensing.

Installation

See https://quantiphyse.readthedocs.io/en/latest/basics/install.html for current installation instructions

Running from source code (for developers)

Running from source is recommended only if your are interested in developing the software further.

1. Install the dependencies:

The list of Python dependencies is in requirements.txt

For example:

pip install -r requirements.txt

2. Build extensions

python setup.py build_ext --inplace

3. Run from source directory

python qp.py

Packaging

The scripts packaging/build.py is used to build a frozen distribution package in the form of a compressed archive (tar.gz or .zip) and a platform-dependent package (deb, msi or dpg). It should run autonomously, however you may need to input the sudo password on Linux in order to build a deb package.

The --snapshot option removes the version number from package filenames so you can provided them for download without having to change the link URLs.

The --maxi option builds a package which includes selected plugins, assuming these are downloaded

To Do list

Issue tracker

Current issues can be viewed on the GitHub issue tracker (https://github.com/ibme-qubic/quantiphyse/issues)

Roadmap

v0.6 (Released June 2018)

• ASL tools first version (preprocess, model fit, calibration, multiphase)
• Improved viewer (full resolution, aligned)

v0.8 (Target Mar 2019)

• Integration of selected FSL tools (FLIRT, FAST, BET, FSL_ANAT?) DONE
• Improved registration support (apply transform) DONE
• Improved ASL tools based on oxasl (inc. ENABLE, VEASL, DEBLUR) DONE
• Fabber T1 DONE
• Fabber DCE DONE
• DSC widget DONE
• Improvements to ROI builder - working 'paint' tool DONE
• Motion simulation DONE
• Add noise DONE

v1.0 (Target June 2019)

• Stable interface for QpWidget, QpData, Process
• Python 3 DONE needs testing
• Support PySide and PySide2 - ideally the latter by default pyside2 branch needs testing
• Improved manual data alignment tools PART DONE
• Otherwise no firm plans yet - selection from 'Vague plans' below

Migration to PySide2

• The current implementation uses PySide which is based on Qt4
• Update to PySide2 when released which uses Qt5
• Will provide support for HiDPI screens and proper scaling in OSx
• PyQtgraph is currently the stumbling block as release version does not support Pyside2
• Current git version has PySide2 modifications but not yet tested
• Consider move to VisPy if this does not come to fruition

Vague Plans for Future

• Refactoring of view classes

  • This is a mess at the moment. Need all view options to be stored as metadata and cleaner separation between the ImageView widget and the individual OrthoView widgets.

• MoCo/Registration

  • Bartek's MC method

• 3D view

  • Probably not that useful but fun and may be easy(?) with vispy. Reliant on good refactoring of ImageView
  • Application to surfaces (Tom K?)

• Add Jola's texture analysis which sounds cool, whatever it is

• PK modelling validation

  • QIBA in progress
  • QIN

• Simplify/rewrite generic Fabber interface

• Improve memory usage by swapping out data which are not being displayed?

• All widgets which process within ROI should work with the subimage within the bounding box of the ROI, not the whole image.

  • Supervoxels does this already with great performance improvement.

• Support other file formats using NIBABEL.

  • DICOM conversion included where DCMSTACK is available

• Add semiquantitative measures

  • Area under the curve
  • Enhancing fraction

• Simulation tools

  • Fabber test data
  • 'Simulated brain'