Cited by 34Medical Image Segmentation TechniquesMedical Imaging and AnalysisPrenatal Screening and Diagnostics

A supervised texton based approach for automatic segmentation and measurement of the fetal head and femur in 2D ultrasound images

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Zhang, Lei, Ye, Xujiong, Lambrou, Tryphon, Duan, Wenting, Allinson, Nigel, Dudley, Nicholas J·2016·Physics in Medicine & Biology

Abstract

This paper presents a supervised texton based approach for the accurate segmentation and measurement of ultrasound fetal head (BPD, OFD, HC) and femur (FL). The method consists of several steps. First, a non-linear diffusion technique is utilized to reduce the speckle noise. Then, based on the assumption that cross sectional intensity profiles of skull and femur can be approximated by Gaussian-like curves, a multi-scale and multi-orientation filter bank is designed to extract texton features specific to ultrasound fetal anatomic structure. The extracted texton cues, together with multi-scale local brightness, are then built into a unified framework for boundary detection of ultrasound fetal head and femur. Finally, for fetal head, a direct least square ellipse fitting method is used to construct a closed head contour, whilst, for fetal femur a closed contour is produced by connecting the detected femur boundaries. The presented method is demonstrated to be promising for clinical applications. Overall the evaluation results of fetal head segmentation and measurement from our method are comparable with the inter-observer difference of experts, with the best average precision of 96.85%, the maximum symmetric contour distance (MSD) of 1.46 mm, average symmetric contour distance (ASD) of 0.53 mm; while for fetal femur, the overall performance of our method is better than the inter-observer difference of experts, with the average precision of 84.37%, MSD of 2.72 mm and ASD of 0.31 mm.

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Registry

Crossref · 10.1088/0031-9155/61/3/1095

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  • Ten studies assessed automated measurement of fetal abdominal circumference, femur length, head circumference and biparietal diameter.

    “Ten studies assessed automated measurement of the fetal abdominal circumference (AC), femur length (FL), head circumference and biparietal diameter.8,[32][33][34][35][36][37][38][39][40]”

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Authors
Zhang, L., Ye, X., Lambrou, T., Duan, W., Allinson, N., & Dudley, N. J.
Affiliations
  • University of Lincoln (GB)
  • Lincoln County Hospital (GB)
Corresponding author
Ye, Xujiong
Venue
Physics in Medicine & Biology
Published
2016-01-13
Volume
61
Issue
3
Pages
1095-1115
ISSN
  • 0031-9155 (ISSN-L)
  • 1361-6560
OpenAlex
W2211303824
Cited by
34
References
32
Citations by year
2026: 2 · 2025: 2 · 2024: 3 · 2023: 4 · 2022: 5 · 2021: 5 · 2020: 6 · 2019: 3 · 2018: 1 · 2017: 3
FWCI
1.59
Type
journal article
Language
en
Open access
Locations
  • Physics in Medicine and Biology (publishedVersion)
  • PubMed (publishedVersion)
  • Lincoln Repository (University of Lincoln) (acceptedVersion)
  • White Rose Research Online (University of Leeds, The University of Sheffield, University of York) (acceptedVersion)
  • Figshare (submittedVersion, cc-by)
Funders
The University Research Investment Funding (RIF2014-21 A16988)
Topics
  • Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Medical Image Segmentation Techniques
  • Physical Sciences › Engineering › Biomedical Engineering › Medical Imaging and Analysis
  • Health Sciences › Medicine › Pediatrics, Perinatology and Child Health › Prenatal Screening and Diagnostics
Keywords
fetal head segmentation, femur segmentation, ultrasound fetal biometry, texton features, speckle reduction, boundary detection, ellipse fitting, fetal head circumference, femur length
MeSH terms
Algorithms, Female, Femur, Head, Humans, Image Processing, Computer-Assisted, Pregnancy, Ultrasonography, Prenatal, Signal-To-Noise Ratio

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