Quantiphyse is designed for 3D medical imaging volumes. This might include imaging data, but also 3D volumes that define an ROI (binary values) or multiple ROI (integer/multi-level values). Quantiphyse recognises 4D (3+1D) imaging data as being three spatial dimensions and a fourth dimension of serial measurements at each 3D location - this would include timeseries data. This would be the normal format for use with many of the quantitative physiological image analysis tools, where multiple different measurements are needed to extract the relevant information. Quantiphyse can handle the special case of 2+1D data, i.e., a single slice of series data.
Quantiphyse directly supports Nifti volumes (both .nii and .nii.gz). There is some limited (and mainly experimental support) DICOM. But, if you have DICOM data we would suggest converting to Nifti yourself first.
Quantiphyse keeps all data on its original grad. But, for display purposes it will be interpolated onto the gird of the main data where necessary. Additionally, where an tool requires multiple data sources to be on the same grid to perform an analysis, interpolation will be used, the grid being determined by the tool.
We run a variety of courses, workshops and demonstrations to introduce physiological image analysis techniques and offer hands-on experience with Quantiphyse. See bleow for recent and upcoming events.
A one day hands-on course on Physiological Image Analysis using Quantiphyse and FSL tools.
12th September 2019 at the Johns Hopkins Medical Campus, prior to the ICP 2019 Symposium
We will be demonstrating Quantiphyse at the ESMRMB 2019 Congress in Rotterdam (3rd-5th October).
Come and see Quantiphyse in action at desk number 6 from 1-2pm on Thursday 3rd.