Abstract: A method of analysing MRI images is described. The method comprising acquiring at least three medical MR images of a subject; analysing the at least three medical MR images to determine a water T1 map; applying a field strength correction and an iron correction to the determined water T1 map to generate a corrected water T1 map; generating one or more simulated MRI images based on the water T1 map; fitting the one or more simulated MR images to determine a standard cT1 image for the subject.

Abstract: A method of analysing MRI images is described. The method comprising the steps of: acquiring a first medical MR image, and a second medical MR image, of a subject at the same nominal magnetic field strength; analysing the first and second MR images to determine a wT1 map from the first and second images; applying a field strength correction based on modification of the nominal field strength used for the first and second MR image acquisitions, and an iron correction to correct for differences in the iron concentration from a normal level using a T2*map, to the wT1 map from the first and second images to generate a corrected wT1 map; using the corrected wT1 map to determine simulated signals for a subject with normal iron levels, and fitting the simulated signals to a standard cT1 to determine a standard cT1 image for the subject.

Abstract: A method and apparatus for analysing MRI data of breast tissue is described. The method comprising the steps of: acquiring a plurality of quantitative non-contrast MRI scan images of at least part of the breast area using different MR pulse sequences for each MRI scan image; determining a plurality of MRI metrics from the acquired quantitative MRI scans; using the determined metrics to generate a plurality of MRI metric maps; calculating at least one of: a breast composite map and a heterogeneity map, from the metric maps to show tissue characteristics of fat and non-fat tissue in the MRI image; determining breast tissue heterogeneity characteristics from at least one of the breast composite map and the heterogeneity map; and identifying clusters of data from at least one of the breast composite map, breast hetereogeneity map and the breast tissue hetereogeneity characteristics.

Abstract: A method of analysing the magnitude of Magnetic Resonance Imaging (MRI) data is described. The method comprising: using the magnitude only of the multi-echo MRI data of images from the subject, where images are acquired at arbitrarily timed echoes including at least one echo time where water and fat are not substantially in-phase; fitting the magnitude of said multi-echo MRI data to a single signal model to produce a plurality of potential solutions for the relative signal contributions for each of the at least two species from the model, by using a plurality of different starting conditions to generate a particular cost function value for each of the plurality of starting conditions, where said cost function values are independent of a field map term for the MRI data; analysing said cost function values to calculate relative signal separation contribution for each species at each voxel of the images.

Abstract: A method of quantifying changes in a visceral organ comprises acquiring first (310) and second (410) medical scans of a visceral organ at first and second timepoints. At least part of the visceral organ in the first medical scan is parcellated into a first set of one or more subregions (420), based on image content, each subregion comprising a plurality of voxels. The first medical scan (310) is aligned to the second medical scan (410), before or after parcellating the first medical scan (310). Then the second medical scan is parcellated into a second set of one or more subregions. A metric is evaluated for a subregion in the first medical scan (310), and for the corresponding subregion in the second medical scan (410). A difference in the metric values provides a measure of a change that has occurred in the subregion, between the first and second timepoints.

Abstract: A method of providing a quantitative volumetric assessment of organ health or a quantitative map of an organ. The method comprises obtaining a volumetric map of organ health comprising information defining a state of tissue health across at least part of an organ, receiving an input defining at least one organ section, determining an assessment organ volume based at least partly on the at least one defined organ section, calculating an organ-viability measure for the assessment organ volume based at least partly on information within the volumetric map defining the state of tissue health across the organ volume, and outputting an indication of the organ-viability measure.

Abstract: A method (200) and apparatus (1100) for generating quantitative data for biliary tree structures from volumetric medical imaging scan data. The method comprises performing segmentation (230; 300) of a volume of the medical imaging scan data to identify tubular biliary structures within the volume of the medical imaging scan data; for at least one segmented tubular biliary structure within the volume of the medical imaging scan data, computing (240; 800) at least one set of quantitative structural parameters for at least one location along the length of the tubular biliary structure; and outputting (250) quantitative biliary tree data comprising the at least one set of quantitative structural parameters for the at least one segmented tubular biliary structure.