A hybrid intelligent diagnostic system based on neural networks and image analysis techniques in the field of automated cytogenetics

We introduce a hybrid intelligent karyotyping system based on two different types of artificial neural networks (ANNs) and chromosome´s features obtained by digital image processing techniques. A microscope equipped with a CCTV camera and a microcomputer including a frame grabber are the basic components of our hardware set-up. The inputs to the ANN structure are obtained directly from digital chromosome images by using two recently developed object detection and object skeletonizing algorithms. Moreover, the band patterns of chromosomes are represented by applying wavelet transform techniques on the gray level profiles of chromosomes. The network parameters are determined by using the results of many training and testing experiments in order to reach an optimal state from the classification performance point of view