Abstract: Machine readable instructions, a data processing apparatus and a method are provided to determine one or more properties of motor units of skeletal muscle by analyzing a time series of Magnetic Resonance, MR, images representing a slice of a body part to identify signal voids in one or more images of the series. A comparison of at least one characteristic of the identified signal voids in the images is performed with a control data set of MR images produced by applying a controlled stimulus to a motor nerve to establish inherent characteristics of signal voids corresponding to motor units of skeletal muscle. Properties of candidate motor units are analyzed to confirm or reject them as motor units and at least one of: a firing frequency of at least one of the confirmed motor units, a size of at least one of the confirmed motor units, a number of confirmed motor units in a given image area or a shape of at least one of the confirmed motor units is determined.

Abstract: Machine readable instructions, a data processing apparatus and a method are provided to determine one or more properties of motor units of skeletal muscle by analyzing a time series of Magnetic Resonance, MR, images representing a slice of a body part to identify signal voids in one or more images of the series. A comparison of at least one characteristic of the identified signal voids in the images is performed with a control data set of MR images produced by applying a controlled stimulus to a motor nerve to establish inherent characteristics of signal voids corresponding to motor units of skeletal muscle. Properties of candidate motor units are analyzed to confirm or reject them as motor units and at least one of: a firing frequency of at least one of the confirmed motor units, a size of at least one of the confirmed motor units, a number of confirmed motor units in a given image area or a shape of at least one of the confirmed motor units is determined.