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Overview of an Ovarian Classification and Detection PCOS in Ultrasound Image: A Study

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Intelligent Computing Paradigm and Cutting-edge Technologies (ICICCT 2019)

Part of the book series: Learning and Analytics in Intelligent Systems ((LAIS,volume 9))

Abstract

PCOS (polycystic ovary syndrome) is the main cause of forming multiple follicles in ovaries which leads to infertility, obesity, diabetes, heart disease for women. Hormone level imbalance cause to get irregular periodic cyclic because of PCOS. According to the different disorder stages of Ovary, Cyst classified into three categories such as Normal Cyst, Ovarian Cyst and Poly Cyst Ovary. Currently Adult female is affected frequently by polycystic ovaries disease (PCOD). Doctors and Medical Analysts conforming the scan reports based on the number of cysts present in ovary. This may leads to inconsistency of finding proper count of follicles, prolonged time consumption and vulnerable error. To avoid this issue, computer based techniques helps the doctors for the easy detection of follicles and PCOS with different hormone issues. Based on study, Image processing and machine learning techniques play a vital role for PCOS detection and Ovary classification. In this paper, several techniques implemented by many researchers were discussed along with the features and metrics of Ovarian Classification and the detection of PCOS.

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Author information

Authors and Affiliations

  1. Department of Computer Science, S.D.N.B. Vaishnav College for Women, University of Madras, Chennai, India

    N. Priya & S. Jeevitha

  2. Department of Computer Application, S.D.N.B. Vaishnav College for Women, University of Madras, Chennai, 600 044, India

    N. Priya & S. Jeevitha

Authors
  1. N. Priya
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  2. S. Jeevitha
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Corresponding author

Correspondence to N. Priya .

Editor information

Editors and Affiliations

  1. University of Technology Sydney, Sydney, Australia

    Lakhmi C. Jain

  2. CSIE Department, National Dong Hwa University, New Taipei City, Taiwan

    Sheng-Lung Peng

  3. Al-Balqa’ Applied University, Salt, Jordan

    Basim Alhadidi

  4. Department of Computer Science, Brainware University, Kolkata, West Bengal, India

    Souvik Pal

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Priya, N., Jeevitha, S. (2020). Overview of an Ovarian Classification and Detection PCOS in Ultrasound Image: A Study. In: Jain, L., Peng, SL., Alhadidi, B., Pal, S. (eds) Intelligent Computing Paradigm and Cutting-edge Technologies. ICICCT 2019. Learning and Analytics in Intelligent Systems, vol 9. Springer, Cham. https://doi.org/10.1007/978-3-030-38501-9_36

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