Quantiphyse is a visualization and analysis tool for medical imaging data, particularly supporting quantitive and physiological imaging methods. The aim is to bring advanced analysis methods to users in biomedical research via an easy-to-use interface, that also permits the creation of analysis pipelines to be used in research studies.
The software is designed a GUI that provides a range of visualisation and data interrogation tools, alongside various plug-ins that support a range of analysis methods. Quantiphyse also supports advanced usage via non-GUI batch processing and direct interaction with the underlying Python code.
Quantiphyse is particularly suited for quantitative, physiological or functional imaging data, typically these are comprised of multiple volumes in a 4D (time-) series and/or multimodal imaging data. Quantiphyse is built around the concept of making spatially resolved measurements of physical or physiological processes from imaging data using either model-based or model-free methods, in a large part exploiting Bayesian inference techniques. Quantiphyse can analyse data both voxelwise or within regions of interest that may be manually or automatically created, e.g. supervoxel or clustering methods.
Quantiphyse is free for non commercial use, available under an academic use licence. The license details are displayed on first use and the LICENSE file is included in the distribution. For further information see the OUI Software Store. If you are interested in commercial licensing you shold contact Oxford Universirty Innovation in the first instance, referencing project 14419.
Tools for quantification of physiological processes from MRI data available in quantiphyse are being used in various clinical research studies including stroke and tumour imaging