1. A processor-implemented imaging method, comprising: obtaining imaging data corresponding to an imaged region and acquired by at least first and second sensor elements; and using a processor, fitting a parameterized model to the imaging data, wherein the parameterized model includes a first sensor-dependent noise model generated by the first sensor element in a first portion of the imaging data acquired by the first sensor element, and a second sensor-dependent noise model generated by the second sensor element in a second portion of the imaging data acquired by the second sensor element, wherein: the first sensor-dependent noise model differs, at least in part, from the second sensor-dependent noise model; and fitting the parameterized model to the imaging data comprises: combining the first sensor-dependent noise model with a parameter-dependent photon shot noise model to obtain an estimate of sensor-dependent noise and photon shot noise in the first portion of the imaging data; and combining the second sensor-dependent noise model with the parameter-dependent photon shot noise model to obtain an estimate of sensor-dependent noise and photon shot noise in the second portion of the imaging data.