Automated ovarian follicular monitoring: A novel real-time approach

Rose T. Faghih, Aaron K. Styer, Emery N. Brown

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    Abstract

    Ovarian follicular monitoring is an essential diagnostic tool in obstetrics and gynecology to evaluate ovarian reserve and to estimate follicular and ovarian response to fertility treatment. Given the significant time requirement, inconvenience measuring follicles and estimating follicular development during multiple examinations, and variable results of different clinicians performing monitoring, complete automation of follicular monitoring is necessary. Computerized follicle detection is currently either semi-automated or has low performance due to limiting factors: (1) noise, (2) detecting multiple follicles very close to each other as one follicle region without finding the boundary of individual follicles, and (3) not being fast enough to be used in real-time clinical practice. To overcome these limitations, we handle noise by singular value decomposition based image compression followed by an anisotropic diffusion scheme for multiplicative speckle, and detect follicles by performing different segmentation techniques depending on features of the image (such as pixel intensity level) and features of the detected follicle areas (such as roundness). This approach allows for rapid identification and measurement of individual follicles with the ability to differentiate between the borders of adjacent follicles and the boundary between the follicle and ovarian stroma.

    Original languageEnglish (US)
    Title of host publication2017 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society
    Subtitle of host publicationSmarter Technology for a Healthier World, EMBC 2017 - Proceedings
    PublisherInstitute of Electrical and Electronics Engineers Inc.
    Pages632-635
    Number of pages4
    ISBN (Electronic)9781509028092
    DOIs
    StatePublished - Sep 13 2017
    Event39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2017 - Jeju Island, Korea, Republic of
    Duration: Jul 11 2017Jul 15 2017

    Publication series

    NameProceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
    ISSN (Print)1557-170X

    Other

    Other39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2017
    Country/TerritoryKorea, Republic of
    CityJeju Island
    Period7/11/177/15/17

    ASJC Scopus subject areas

    • Signal Processing
    • Biomedical Engineering
    • Computer Vision and Pattern Recognition
    • Health Informatics

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