A system for allowing assessment of tissue of a subject, the system comprising: one or more processors; and memory having instructions stored thereon, the instructions, when executed by the one or more processors, cause the system to: receive a time series of signal intensity data capturing transit of an imaging agent through tissue over a period of time, wherein the time series of signal intensity data define a plurality of calculation regions and wherein signal intensity in each calculation region over the period of time may be approximated by a time-intensity curve corresponding to that calculation region; determine, for each calculation region, a first coefficient value that is related to a first portion of the time-intensity curve corresponding to the calculation region, and convert the first coefficient values across the plurality of calculation regions into a first coefficient-derived image map; determine, for each calculation region, a second coefficient value that is related to a second portion of the time-intensity curve corresponding to the calculation region, and convert the second coefficient values across the plurality of calculation regions into a second coefficient-derived image map; and generate a quantitative predictor of the progress of healing of tissue, based on the first and second coefficient-derived image maps. one or more processors; and memory having instructions stored thereon, the instructions, when executed by the one or more processors, cause the system to: receive a time series of signal intensity data capturing transit of an imaging agent through tissue over a period of time, wherein the time series of signal intensity data define a plurality of calculation regions and wherein signal intensity in each calculation region over the period of time may be approximated by a time-intensity curve corresponding to that calculation region; determine, for each calculation region, a first coefficient value that is related to a first portion of the time-intensity curve corresponding to the calculation region, and convert the first coefficient values across the plurality of calculation regions into a first coefficient-derived image map; determine, for each calculation region, a second coefficient value that is related to a second portion of the time-intensity curve corresponding to the calculation region, and convert the second coefficient values across the plurality of calculation regions into a second coefficient-derived image map; and generate a quantitative predictor of the progress of healing of tissue, based on the first and second coefficient-derived image maps. receive a time series of signal intensity data capturing transit of an imaging agent through tissue over a period of time, wherein the time series of signal intensity data define a plurality of calculation regions and wherein signal intensity in each calculation region over the period of time may be approximated by a time-intensity curve corresponding to that calculation region; determine, for each calculation region, a first coefficient value that is related to a first portion of the time-intensity curve corresponding to the calculation region, and convert the first coefficient values across the plurality of calculation regions into a first coefficient-derived image map; determine, for each calculation region, a second coefficient value that is related to a second portion of the time-intensity curve corresponding to the calculation region, and convert the second coefficient values across the plurality of calculation regions into a second coefficient-derived image map; and generate a quantitative predictor of the progress of healing of tissue, based on the first and second coefficient-derived image maps. <EOS>