Automated analysis of a sequence of ovarian ultrasound images. Part I: segmentation of single 2D images
An improved algorithm is presented for ovarian follicle detection in ultrasound images. This fully automated recognition algorithm is composed of three successive steps. First, initial homogeneous regions are determined. Then, these initial regions are grown. The growing is controlled by average grey-level and by a newly introduced weighted image gradient. In the last stage, those regions are extracted that probably correspond to the follicles. The algorithm has been tested on 50 ovarian ultrasound images. The recognition rate of follicles using this procedure was around 78%. A possible extension of the algorithm deals with the entire information in the ultrasound image sequence, which is covered in Part II of this paper.
ultrasound images region growing weighted gradient ovarian follicle segmentation