A method for using a neural network to deconvolute the effects due to
surface topography from the effects due to the other physical property
being measured in a scanning probe microscopy (SPM) or atomic force
microscopy (AFM) image. In the case of a thermal SPM, the SPM probe is
scanned across the surface of a sample having known uniform thermal
properties, measuring both the surface topography and thermal properties
of the sample. The data thus collected forms a training data set. Several
training data sets can be collected, preferably on samples having
different surface topographies. A neural network is applied to the
training data sets, such that the neural network learns how to
deconvolute the effects dues to surface topography from the effects dues
to the variations in thermal properties of a sample.