Several established imaging modalities such as positron emission tomography (PET), single photon emission computed tomography (SPECT), computed tomography (CT), and magnetic resonance imaging (MRI) employ triggering, gating, or synchronization schemes that only activate data acquisition during the same stage of the cardiac cycle. This effect would be possible in MSOT imaging too, but would require heart monitoring systems and external triggering of the laser source, causing added complexity and increased acquisition times because the laser would not fire at the maximum possible rate. Instead, MSOT offers a significant advantage in that full frames can be acquired from each laser pulse. Therefore, motion correction of MSOT can also be considered in the context of grouping motion insensitive single frames into sets of images corresponding to similar time points in the cardiac cycle, with the aim of producing images with reduced motion blurring. To this end we considered a -means clustering algorithm to classify multiple images acquired at different wavelengths according to the stage of the cardiac cycle. After subsequent spectral unmixing, we compared the results to MSOT images obtained without clustering.