A hybrid system for cell detection in digital micrographs

To analyze large sets of digital micrographs from high-throughput screening studies with constant accuracy, advanced image processing algorithms are necessary. In the literature, systems have been proposed applying modelbased fitting algorithms, morphological operators and artificial neural networks (ANN). Because single approaches show limited performance, we propose a hybrid system that combines the Hough transform with a multi-layer perceptron (MLP) network. Our results show, that the combination of both approaches improves the performance and the positions of cell bodies are obtained with increased sensitivity and positive predictive value.