Fluorescence in situ hybridization (FISH) is a molecular diagnostic technique in 
which a fluorescent labeled probe hybridizes to a target nucleotide sequence of 
deoxyribose nucleic acid. Upon excitation, each chromosome containing the target 
sequence produces a fluorescent signal (spot). Because fluorescent spot counting 
is tedious and often subjective, automated digital algorithms to count spots are 
desirable. New technology provides a stack of images on multiple focal planes 
throughout a tissue sample. Multiple-focal-plane imaging helps overcome the 
biases and imprecision inherent in single-focal-plane methods. This paper 
proposes an algorithm for global spot counting in stacked three-dimensional 
slice FISH images without the necessity of nuclei segmentation. It is designed 
to work in complex backgrounds, when there are agglomerated nuclei, and in the 
presence of illumination gradients. It is based on the morphological top-hat 
transform, which locates intensity spikes on irregular backgrounds. After 
finding signals in the slice images, the algorithm groups these together to form 
three-dimensional spots. Filters are employed to separate legitimate spots from 
fluorescent noise. The algorithm is set in a comprehensive toolbox that provides 
visualization and analytic facilities. It includes simulation software that 
allows examination of algorithm performance for various image and algorithm 
parameter settings, including signal size, signal density, and the number of 
slices.