FISH Image Analysis Using a Modified Radial Basis Function Network
Ioannis N. Kasampalidis, Ioannis Pitas, Georgia Karayannopoulou, Ioannis S. Kostopoulos, Paolo Aretini, Generoso Bevilacqua, Andrea O. Cavazzana, Michele Menicagli, Antonina Starita, Kleoniki Lyroudia · 2007
Fluorescent in situ hybridization (FISH) is a valuable method for determining Her-2/neu status in breast carcinoma samples, an important prognostic indicator. Visual evaluation of FISH images is a difficult task which involves manual counting of dots in multiple images, a procedure which is both time consuming and prone to human error. A number of algorithms have recently been developed dealing with (semi)-automated analysis of FISH images. These algorithms are quite promising but further improvement is required in improving their accuracy. Here, we present a novel method for analyzing FISH images based on the statistical properties of Radial Basis Functions. Our method was evaluated on a data set of 100 breast carcinoma cases provided by the Aristotle University of Thessaloniki and the University of Pisa, with promising results.