Abstract: PURPOSE: To develop an automatic computer algorithm for isolating the follicles in ovarian ultrasonographic images. METHODS: A semi-automatic algorithm has been developed as the first step in the development of a totally automatic follicle isolation tool for use with ovarian ultrasonographic imaging. The algorithm is knowledge-based and depends upon the use of a priori information about the structure of the follicle. Graph searching techniques are used along with a method of assigning graph node costs that represent edge information combined with the a priori knowledge.Interactive identification of the follicle of interest is followed by, in some cases, a manual editing of an automatically defined interior boundary. After the interior boundary has been defined, the outer follicle wall border is found without further human intervention. RESULTS: Based on a test with 31 ultrasonographic images of women's ovaries made in vivo, the algorithm is able to locate the outer follicle wall to an rms accuracy of 0.59 mm $POM 0.28 mm in comparison with human expert manual boundary tracing. BREAKTHROUGHS: The isolation of ovarian follicles in ultrasonographic imaging has heretofore only been accomplished by manual tracing. Our semi-automated follicle border finding algorithm is, to the best of our knowledge, the first computerized method capable of finding the outer wall boundary of the follicle. CONCLUSIONS: The success of our semi-automatic follicle isolation algorithm clearly demonstrates the feasibility of a totally automatic tool that should have wide application in ultrasonographic studies of ovarian follicular dynamics. !14
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