Automated Techniques for the Interpretation of Fetal Abnormalities: A Review

Ultrasound (US) image segmentation methods, focusing on techniques developed for fetal biometric parameters and nuchal translucency, are briefly reviewed. Ultrasound medical images can easily identify the fetus using segmentation techniques and calculate fetal parameters. It can timely find the feta...

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Main Authors: Vidhi Rawat, Alok Jain, Vibhakar Shrimali
Format: Article
Language:English
Published: Wiley 2018-01-01
Series:Applied Bionics and Biomechanics
Online Access:http://dx.doi.org/10.1155/2018/6452050
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author Vidhi Rawat
Alok Jain
Vibhakar Shrimali
author_facet Vidhi Rawat
Alok Jain
Vibhakar Shrimali
author_sort Vidhi Rawat
collection DOAJ
description Ultrasound (US) image segmentation methods, focusing on techniques developed for fetal biometric parameters and nuchal translucency, are briefly reviewed. Ultrasound medical images can easily identify the fetus using segmentation techniques and calculate fetal parameters. It can timely find the fetal abnormality so that necessary action can be taken by the pregnant woman. Firstly, a detailed literature has been offered on fetal biometric parameters and nuchal translucency to highlight the investigation approaches with a degree of validation in diverse clinical domains. Then, a categorization of the bibliographic assessment of recent research effort in the segmentation field of ultrasound 2D fetal images has been presented. The fetal images of high-risk pregnant women have been taken into the routine and continuous monitoring of fetal parameters. These parameters are used for detection of fetal weight, fetal growth, gestational age, and any possible abnormality detection.
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spelling doaj.art-1728a7e239684f59a0ef18fb74fa937f2025-02-03T01:26:38ZengWileyApplied Bionics and Biomechanics1176-23221754-21032018-01-01201810.1155/2018/64520506452050Automated Techniques for the Interpretation of Fetal Abnormalities: A ReviewVidhi Rawat0Alok Jain1Vibhakar Shrimali2Department of Bio Medical Engineering, Samrat Ashok Technological Institute, Vidisha, IndiaDepartment of Electronics and Instrumentation Engineering, Samrat Ashok Technological Institute, Vidisha, IndiaDepartment of Electronics and Communication Engineering, G. B. Pant Government Engineering College, Delhi, IndiaUltrasound (US) image segmentation methods, focusing on techniques developed for fetal biometric parameters and nuchal translucency, are briefly reviewed. Ultrasound medical images can easily identify the fetus using segmentation techniques and calculate fetal parameters. It can timely find the fetal abnormality so that necessary action can be taken by the pregnant woman. Firstly, a detailed literature has been offered on fetal biometric parameters and nuchal translucency to highlight the investigation approaches with a degree of validation in diverse clinical domains. Then, a categorization of the bibliographic assessment of recent research effort in the segmentation field of ultrasound 2D fetal images has been presented. The fetal images of high-risk pregnant women have been taken into the routine and continuous monitoring of fetal parameters. These parameters are used for detection of fetal weight, fetal growth, gestational age, and any possible abnormality detection.http://dx.doi.org/10.1155/2018/6452050
spellingShingle Vidhi Rawat
Alok Jain
Vibhakar Shrimali
Automated Techniques for the Interpretation of Fetal Abnormalities: A Review
Applied Bionics and Biomechanics
title Automated Techniques for the Interpretation of Fetal Abnormalities: A Review
title_full Automated Techniques for the Interpretation of Fetal Abnormalities: A Review
title_fullStr Automated Techniques for the Interpretation of Fetal Abnormalities: A Review
title_full_unstemmed Automated Techniques for the Interpretation of Fetal Abnormalities: A Review
title_short Automated Techniques for the Interpretation of Fetal Abnormalities: A Review
title_sort automated techniques for the interpretation of fetal abnormalities a review
url http://dx.doi.org/10.1155/2018/6452050
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