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Computer Assisted Human Follicle Analysis for Fertility Prospects with 3D Ultrasound

  • Bart M. ter Haar Romeny
  • Bart Titulaer
  • Stiliyan Kalitzin
  • Gabriëlle Scheffer
  • Frank Broekmans
  • Joes Staal
  • Egbert te Velde
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1613)

Abstract

Knowledge about the status of the female reproductive system is important for fertility problems and age-related family planning. The volume of these fertility requests in our emancipated society is steadily increasing. Intravaginal 3D ultrasound imaging of the follicles in the ovary gives important information about the ovarian aging, i.e. number of follicles, size, position and response to hormonal stimulation. Manual analysis of the many follicles is laborious and error-prone. We present a multiscale analysis to automatically detect and quantify the number and shape of the patient’s follicles. Robust estimation of the centres of the follicles in the speckled echographic images is done by calculating so-called winding number of the intensity singularity, i.e. the path integral of the angular increment of the direction of the gradient vector over a closed neighbourhood around the point. The principal edges on 200–500 intensity traces radiating from the detected singularity points are calculated by a multiscale edge focussing technique on 1D winding numbers. They are fitted with 3D spherical harmonic functions, from which the volume and shape parameters are derived.

Keywords

Gradient Vector Large Follicle Ovarian Aging Follicle Centre Bovine Ovary 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

  1. 1.
    Block, E.: Quantitative Morphological Investigations of the Follicular System in Women. Variations at Different Ages. Acta Anat. 14 (1952) 108–123Google Scholar
  2. 2.
    Broekmans, F.J., Scheffer, G.J., Dorland, M., Blankenstein, M.A., de Jong, F.H., te Velde, E.R.: “Ovarian Reserve Tests in Infertility and in Normal Fertile Women”, Maturitas, in press.Google Scholar
  3. 3.
    Chang, M.Y., Chang, C.H., Chiu, T.H., Hsieh, T.T., Soong, Y.K.: The Antral Follicle Count Predicts the Outcome of Pregnancy in a Controlled Ovarian Hyperstimulation/Intrauterine Insemination Program. J. Assisted Reprod. Genet. 15 (1998) 12–17CrossRefGoogle Scholar
  4. 4.
    Faddy, M.J., Gosden, R.G., Gougeon, A., Richardsen, S.J., Nelson, J.F.: Accelerated Disappearance of Ovarian Follicles in Mid-Life: Implications for Forecasting Menopause. Human Reproduction. 7 (1992) 1342–1346Google Scholar
  5. 5.
    Feichtinger, W.: Follicle Aspiration with Interactive Three-Dimensional Digital Imaging (Voluson): a Step toward Realtime Puncturing under Three-Dimensional Ultrasound Control. Fertil. Steril. Aug 70 (1998) 374–377CrossRefGoogle Scholar
  6. 6.
    Florack, L.M.J., ter Haar Romeny, B.M., Koenderink, J.J., Viergever, M.A.: Scale and the Differential Structure of Images, Image and Vis, Comp. 10 (1992) 376–388Google Scholar
  7. 7.
    Gore, M.A., Nayudu, P.L., Vlaisavljevic, V., Thomas, N.: Prediction of Ovarian Cycle Outcome by Follicular Characteristics, Stage I, Human Reproduction 10 (1995) 2313–2319Google Scholar
  8. 8.
    ter Haar Romeny, B.M., Florack, L.M.J., Koenderink, J.J., Viergever, M.A.: Scale-Space: Its Natural Operators and Differential Invariants, Colchester, A. C. F. and Hawkes, D. J. (Eds.), Proc. Information Processing in Medical Imaging, Lecture Notes in Computer Science 511, Springer Verlag, Berlin (1991) 239–255CrossRefGoogle Scholar
  9. 9.
    Kalitzin, S.: Topological Numbers and Singularities in Scalar Images. Scale-Space Evolution Properties. In: Gaussian Scale-Space Theory, Eds.: J. Sporring, M. Nielsen, L. Florack, P. Johansen, Kluwer Academic Publishers (1997) 181–189Google Scholar
  10. 10.
    Kalitzin, S., ter Haar Romeny, B.M., Viergever, M.A.: On Topological Deep-Structure Segmentation. In: Proc. Intern. Conf. on Image processing, Santa Barbara, CA (1997) 863–866Google Scholar
  11. 11.
    Kalitzin, S., ter Haar Romeny, B.M., Salden, A.H., Nacken, P.F.M., Viergever, M.A.: Topological Numbers and Singularities in Scalar Images: Scale-Space Evolution Properties. J. of Math. Imaging and Vision 7 (1998), In press.Google Scholar
  12. 12.
    Kemeter, P., Feichtinger, W.: Ultrasound Monitoring of Follicle Growth in IVF. Wien Med. Wochenschr. 141 (1991) 9–13Google Scholar
  13. 13.
    Marsden, J.E., Tromba, A.J.: “Vector Calculus”, W.H. Freeman and Company, New York, 4th edition (1996)MATHGoogle Scholar
  14. 14.
    Peluso, J.J., Damien, M., Nulsen, J.C., Luciano, A.A.: Identification of Follicles with Fertilizable Oocytes by Sequential Ultrasound Measurements during Follicular Development. J. In Vitro Fert. Embryo. Transf. 7 (1990) 304–309CrossRefGoogle Scholar
  15. 15.
    Potocnik, B., Zazula, D, and Korze, D.: Automated Computer-Assisted Detection of Follicles in Ultrasound Images of Ovary, Proceedings CBMS 97, Maribor, Slovenia, 11–13 June 1997, pp. 16–21. And in: J. Med. Syst. 21 (1997) 445–57Google Scholar
  16. 16.
    Potocnik, B., Zazula D., and Solina, F.: Classical Image Processing vs. Computer Vision Techniques in Automated Computer-Assisted Detection of Follicles in Ultrasound Images of Ovary, Proceedings IPA 97, Dublin, Ireland (1997) 551–555Google Scholar
  17. 17.
    Riccabona, M., Nelson, T.R., Pretorius, D.H.: Three-Dimensional Ultrasound: Accuracy of Distance and Volume Measurements. Ultrasound Obstet. Gynecol. 7 (1996) 429–434CrossRefGoogle Scholar
  18. 18.
    Richardsen, S.J., Senikas, V., Nelson, J.F.: Follicular Depletion during the Menopausal Transition: Evidence for Accelerated Loss and Ultimate Exhaustion. J. Clin. Endocrinol. Metab. 65 (1987) 1231–1237CrossRefGoogle Scholar
  19. 19.
    Robinson, R., Chakraborty, A., Johnson, M., Reuss, M.L., Duncan, J.: Segmentation of Ovarian Follicles using Geometric Properties, Texture Descriptions and Boundary Information, SPIE 2710 (1996) 321–330CrossRefGoogle Scholar
  20. 20.
    Ruess, M.L., Kline, J., Santos, R., Levin, B., Timor-Tritsch, I.: Age and the Ovarian Follicle Pool Assessed with Transvaginal Ultrasonography. Am. J. Obstet. Gynecol. 174 (1996) 624–627CrossRefGoogle Scholar
  21. 21.
    Sarty, G.E., Sonka, M., Liang, W., Pierson, R.A.: The Development of an Automatic Follicle Isolation Tool for Ovarian Ultrasonographic Images, Proc. SPIE Medical Imaging: Image Processing (1997) 822–829Google Scholar
  22. 22.
    Sarty, G.E., Liang, W., Sonka, M., Pierson, R.A.: Semi-automated Segmentation of Ovarian Follicular Ultrasound Images using a Knowledge-based Algorithm. Ultrasound Med. Biol. 24 (1998) 27–42CrossRefGoogle Scholar
  23. 23.
    Staib, L.H., Duncan, J.S.: Boundary Finding with Parametrically Deformable Models, IEEE Tr. PAMI 14 (1992) 1061–1075Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 1999

Authors and Affiliations

  • Bart M. ter Haar Romeny
    • 1
  • Bart Titulaer
    • 1
  • Stiliyan Kalitzin
    • 1
  • Gabriëlle Scheffer
    • 2
  • Frank Broekmans
    • 2
  • Joes Staal
    • 1
  • Egbert te Velde
    • 2
  1. 1.Image Sciences InstituteUtrecht UniversityUtrechtThe Netherlands
  2. 2.Division of Obstetrics and Gynaecology, Subdivision for Reproductive MedicineUniversity Hospital UtrechtThe Netherlands

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