Control over neuronal growth is a prerequisite for the creation of defined in vitro neuronal networks as assays for the elucidation of interneuronal communication. Neuronal growth has been directed by focusing a near-infrared laser beam at a nerve cell’s leading edge [A. Ehrlicher, T. Betz, B. Stuhrmann, D. Koch, V. Milner, M. G. Raizen, and J. Käs, Proc. Natl. Acad. Sci. U.S.A. 99, 16024 (2002)]. The setup reported by Ehrlicher et al. was limited to local laser irradiation and relied on a great deal of subjective interaction since the laser beam could only be steered manually. To overcome the drawbacks of the reported setup, we developed and here present a fully automated low-contrast edge detection software package, which responds to detected cell morphological changes by rapidly actuating laser steering devices, such as acousto-optical deflectors or moving mirrors, thus enabling experiments with minimum human interference. The resulting radiation patterns can be arbitrary functions of space, time, and cell morphology, and are calculated by experiment specific feedback routines. Data processing is repeated on the order of 1s allowing rapid reactions to morphological changes. The strengths of our program are the combination of real-time low contrast shape detection with complex feedback mechanisms, as well as easy adaptability due to a modular programming concept. In this article we demonstrate automated optical guidance; however, the software is easily adaptable to other problems requiring automated rapid responses of equipment to changes in the morphology of low contrast objects.