Although conventional autofluorescence spectroscopy, in which fluorescence emission spectra are recorded for fixed excitation wavelengths, has demonstrated good performance in tissue diagnosis, it suffers from prolonged data acquisition time and broad-band fluorescence features. Synchronous spectroscopy has been proposed to overcome the limitations of conventional fluorescence spectroscopy but has not been applied to imaging for tissue diagnosis in vivo. Our group has developed a synchronous fluorescence imaging system to combine the great diagnostic potential of synchronous spectroscopy and the large field of view of imaging for cancer diagnosis. This system has been tested in a mouse skin model to capture synchronous fluorescence images. A simple discriminant analysis method and a more complicated multi-variate statistical method have been developed to generate a single diagnostic image from a large number of raw fluorescence images. Moreover, it was demonstrated that the diagnostic image generated from synchronous data is comparable to that generated from full spectral data in classification accuracy.