Quantiphyse: Improved analysis of biomedical imaging data

Quantiphyse is an algorithm that can be applied to biomedical imaging data, such as MRI, to improve the accuracy of perfusion quantification and to supply information that is not possible with the current techniques.

Over the years, medical imaging techniques have undergone major advances. The most common types of imaging include X-rays, ultrasound, CT scans and MRI.

Quantiphyse is an advanced visual tool for 3D and 4D (time) biomedical imaging data. It is particularly suited for physiological or functional imaging data comprised of multi-volumes in a time series and /or multimodal imaging data. Applications of the software tool include highlighting features in the brain and cancerous growths associated with the underlying physiology.

The software is capable of generating spatially resolved measurements of physical or physiological processes from imaging data using either model-based or model-free methods. It relies, in large part, on 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.

Key features include:

  • 2D orthographic viewing and navigation of data, regions of interest (ROIs) and overlays
  • Universal analysis tools including clustering, supervoxel generation and curve comparison
  • Tools for CEST-MRI analysis and modelling
  • Tools for DCE-MRI analysis and modelling
  • Tools for ROI generation
  • Registration and motion correction
  • Extensible via plugins, in the future to include ASL MRI data, Bayesian modelling and more

Quantiphyse is now available directly through the Oxford University Innovation Software Store.

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