Abstract: A computer-implemented method of analysing nuclear magnetic resonance, NMR, data of a target object is provided. The method comprises receiving NMR data of the target object, and analysing the received NMR data using a model of the diffusive behaviour of particles within the target object. The model includes a time parameter and a space parameter, the time parameter describing temporal characteristics of the diffusive behaviour of particles in the model and the space parameter describing spatial characteristics of the diffusive behaviour of particles in the model. The model is constrained such that the value of the time parameter and the value of the space parameter are related according to a correlation function. An apparatus for analysing nuclear magnetic resonance, NMR, data of a target object is also provided.

Abstract: A computer-implemented method of analysing nuclear magnetic resonance, NMR, data of a target object is provided. The method comprises receiving NMR data of the target object, and analysing the received NMR data using a model of the diffusive behaviour of 5 particles within the target object. The model includes a time parameter and a space parameter, the time parameter describing temporal characteristics of the diffusive behaviour of particles in the model and the space parameter describing spatial characteristics of the diffusive behaviour of particles in the model. The model is constrained such that the value of the time parameter and the value of the space parameter 10 are related according to a correlation function. An apparatus for analysing nuclear magnetic resonance, NMR, data of a target object is also provided.

Abstract: Methods and apparatus for obtaining probability density functions representing expected distributions of values of a parameter associated with an imaging modality are disclosed. The probability density functions are derived using data obtained from reference tissue volumes using the same imaging modality and at least one other type of imaging modality. The probability density functions are used to analyze data obtained from a volume of tissue of a patient in order to classify the tissue according to tissue type. Methods and apparatus are also disclosed in which deviations from a mean of an arctangent of ratios of first and second metabolite intensities in voxels are used to identify tissue types.

Abstract: Methods and apparatus for obtaining probability density functions representing expected distributions of values of a parameter associated with an imaging modality are disclosed. The probability density functions are derived using data obtained from reference tissue volumes using the same imaging modality and at least one other type of imaging modality. The probability density functions are used to analyse data obtained from a volume of tissue of a patient in order to classify the tissue according to tissue type. Methods and apparatus are also disclosed in which deviations from a mean of an arctangent of ratios of first and second metabolite intensities in voxels are used to identify tissue types.