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Automatic Detection of Fetal Abnormality Using Head and Abdominal Circumference

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Computational Collective Intelligence (ICCCI 2016)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 9876))

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Abstract

In present scenario women’s are suffering from thyroid, diabetes and high blood pressure and therefore early detection and diagnosis of fetal abnormality can save lives and reduce cost of treatment. In this paper we propose an artificial neural network (ANN) based method for the detection of fetal abnormality in 2-D ultrasound images of 14–40 weeks. The accurate values of fetal anatomical structures are found by segmentation techniques and these values transferred to neural model for detection of possible abnormalities from 2D fetal ultrasound images. The ANN model is able to find Intrauterine Growth Retardation (IUGR) and abnormal fetus using head and abdominal circumference.

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Author information

Authors and Affiliations

  1. Department of Biomedical Engineering, Samrat Ashok Technological Institute, Vidisha, India

    Vidhi Rawat

  2. Department of Electronics and Instrumentation Engineering, Samrat Ashok Technological Institute, Vidisha, India

    Alok Jain

  3. Department of Electronics and Communication Engineering, G. B. Pant Government Engineering College, Delhi, India

    Vibhakar Shrimali

  4. Department of Electrical Engineering, IITRAM, Ahmedabad, India

    Abhishek Rawat

Authors
  1. Vidhi Rawat
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  2. Alok Jain
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  3. Vibhakar Shrimali
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  4. Abhishek Rawat
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Corresponding author

Correspondence to Vidhi Rawat .

Editor information

Editors and Affiliations

  1. Wroclaw University of Technology , Wroclaw, Poland

    Ngoc Thanh Nguyen

  2. Aristotle University of Thessaloniki , Thessaloniki, Greece

    Lazaros Iliadis

  3. Department of Forestry and Manageme, Democritus University of Thrace Department of Forestry and Manageme, Orestiada Thrace, Greece

    Yannis Manolopoulos

  4. Wrocław University of Technology , Wrocław, Poland

    Bogdan Trawiński

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© 2016 Springer International Publishing Switzerland

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Rawat, V., Jain, A., Shrimali, V., Rawat, A. (2016). Automatic Detection of Fetal Abnormality Using Head and Abdominal Circumference. In: Nguyen, N., Iliadis, L., Manolopoulos, Y., Trawiński, B. (eds) Computational Collective Intelligence. ICCCI 2016. Lecture Notes in Computer Science(), vol 9876. Springer, Cham. https://doi.org/10.1007/978-3-319-45246-3_50

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  • DOI: https://doi.org/10.1007/978-3-319-45246-3_50

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-45245-6

  • Online ISBN: 978-3-319-45246-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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