GELFISH - Graphical environment for labelling fluorescence in-situ hybridization images

Signal (dot) counting in fluorescence in-situ hybridization (FISH) images t hat relies on an automatic focusing method for obtaining clearly defined im ages is a time-consuming procedure prone to errors. Our recently developed system has dispensed with automatic focusing, and instead relies on a neura l network classifying focused and unfocused signals into valid and artefact data, respectively, and thereby discriminating between in- and out-of-focu s images. However, to train the classifier accurate labelling of the image signals is required. GELFISH is a Graphical Environment for Labelling FISH images that enables the rejection of unanalysable nuclei and labelling of F ISH signals simply and rapidly. GELFISH is flexible and can be modified eas ily for additional FISH applications. Also, implemented using popular softw are, the environment can be employed on any computer by any user. Finally, GELFISH is proposed in controlling a classifier-based dot counting system.