Xultra - Software for Computer-Assisted Detection of Ovarian Follicles in Ultrasound Images
Coordinators: B. Potočnik and D. Zazula
Algorithm (recognition system) "xultra" is a system
designed for automated follicle detection in the ovarian
ultrasound images. Algorithm input is an ovarian ultrasound
image, as a result is returned a set of regions which are most
probable ovarian follicles. Recognition system xultra consist of
three major parts: pre-processing (from points 1 do 6),
segmentation (from points 7 to 9), and classification (point 10). Algorithm's
- Speckle noise reduction using HRGMF filter.
- Edge detection using Kirsch operator.
- Binarisation of resulting image with OPTIMAL thresholding method.
- Morphological edge thinning.
- Heuristic edge filling.
- Estimation of ovary position based on histograms of edge pixels along rows and columns.
- Segmentation of ovary using OPTIMAL thresholding method.
- Labeling (identifying) dark regions.
- Describing regions with features (area etc.).
- Recognising regions using partial decision based on area, compactness, and a ratio between regions area and its bounding box.
Figure 1 presents a sector of 200x300
pixels extracted from the original ovarian ultrasound image (in
256 grey-levels). The expert readings are denoted with a solid
line, while the follicles obtained using algorithm xultra are
depicted with dotted line.
Figure 1: Ovarian ultrasound subimage. The obtained follicles using
algorithm xultra are denoted with dotted line, the follicle
reference positions provided by an expert are depicted with solid
More about xultra
Xultra with some sample ultrasound images
- B. Potočnik, D. Zazula and D. Korze, "Automated Computer-Assisted Detection of Follicles in Ultrasound Images of Ovary", Journal of Medical Systems, Vol. 21, No. 6, December 1997, pp. 445-457.
- B. Potočnik, "Uporaba segmentacije pri analizi medicinskih slik (Application of Segmentation for Medical Image Analysis)", Masters thesis, 1998, University of Maribor, Faculty of EE and CS. (in Slovene)