The paper deals with the problem of processing and interpretation of clinically recorded ultrasound images for the reason of following the growth of dominant ovarian follicles in a day-to-day manner. A part of the XUltra project achievements is presented. We propose three different automatic computer-based follicle identification algorithms. The first one is based on cellular neural networks. The second one is based on region growing segmentation method, while the third one processes entire image sequence with a predictor-corrector recognition scheme. The recognition rate of follicles with these algorithms goes up to 78%, while the misidentification rate is around 15%.