Detection and Retrieval of Follicles in Polycystic Ovarian Syndrome (PCOS) using Image Processing Techniques

Authors

  • Saranya D Department of Biotechnology, Sapthagiri College of Engineering (Affiliated to VTU, Belagavi) Bangalore, Karnataka, India
  • Prashanth Kumar H.P. Department of Biotechnology, Sapthagiri College of Engineering (Affiliated to VTU, Belagavi) Bangalore, Karnataka, India
  • Rohit K.C. Department of Biotechnology, Sapthagiri College of Engineering (Affiliated to VTU, Belagavi) Bangalore, Karnataka, India

DOI:

https://doi.org/10.37591/joipprp.v3i1.598

Keywords:

Polycystic ovarian syndrome (PCOS), contrast stretching, thresholding, canny

Abstract

About to 18% women of reproductive age are affected by PCOS (Poly Cystic Ovarian Syndrome), a common endocrinopathy. It is also known as PCOS (Poly Cystic Ovarian Syndrome) or Stein-Leventhal syndrome. An imbalance of woman’s female hormones like estrogen and progesterone occur which causes the infertility. There are various methods which are used to diagnose this condition but the most helpful method is the pelvic ultrasound which confirms the presence of multiple small cysts in the periphery of the ovaries. In most of the cases, overlapping of the follicles is found and due to the presence of electrical equipment’s, a noisy image is obtained. So, in this paper, we have discussed about an automated method for follicle detection and quantification, which includes image enhancement and image segmentation techniques.

Cite this Article
Saranya D, Prashanth Kumar HP, Rohit KC. Detection and retrieval of follicles in polycystic ovarian syndrome (PCOS) using image processing techniques. Journal of Image Processing & Pattern Recognition Progress. 2016; 3(1): 1–6p.

References

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Published

2016-01-28

Issue

Vol. 3 No. 1 (2016)

Section

Research Articles

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