Literature DB >> 15972198

Automated fetal head detection and measurement in ultrasound images by iterative randomized Hough transform.

Wei Lu1, Jinglu Tan, Randall Floyd.   

Abstract

An image-processing and object-detection method was developed to automate the measurements of biparietal diameter (BPD) and head circumference (HC) in ultrasound fetal images. The heads in 214 of 217 images were detected by an iterative randomized Hough transform. A head was assumed to have an elliptical shape with parameters progressively estimated by the iterative randomized Hough transform. No user input or size range of the head was required. The detection and measurement took 1.6 s on a personal computer. The interrun variations of the algorithm were small at 0.84% for BPD and 2.08% for HC. The differences between the automatic measurements and sonographers' manual measurements were 0.12% for BPD and -0.52% for HC. The 95% limits of agreement were -3.34%, 3.58% for BPD and -5.50%, 4.45% for HC. The results demonstrated that the automatic measurements were consistent and accurate. This method provides a valuable tool for fetal examinations.

Mesh:

Year:  2005        PMID: 15972198     DOI: 10.1016/j.ultrasmedbio.2005.04.002

Source DB:  PubMed          Journal:  Ultrasound Med Biol        ISSN: 0301-5629            Impact factor:   2.998


  10 in total

1.  Fetal ultrasound image segmentation system and its use in fetal weight estimation.

Authors:  Jinhua Yu; Yuanyuan Wang; Ping Chen
Journal:  Med Biol Eng Comput       Date:  2008-10-11       Impact factor: 2.602

2.  A fast automatic recognition and location algorithm for fetal genital organs in ultrasound images.

Authors:  Sheng Tang; Si-ping Chen
Journal:  J Zhejiang Univ Sci B       Date:  2009-09       Impact factor: 3.066

3.  Automatic image quality assessment and measurement of fetal head in two-dimensional ultrasound image.

Authors:  Lei Zhang; Nicholas J Dudley; Tryphon Lambrou; Nigel Allinson; Xujiong Ye
Journal:  J Med Imaging (Bellingham)       Date:  2017-04-17

4.  Learning to segment key clinical anatomical structures in fetal neurosonography informed by a region-based descriptor.

Authors:  Ruobing Huang; Ana Namburete; Alison Noble
Journal:  J Med Imaging (Bellingham)       Date:  2018-03-10

5.  An Automated Framework for Large Scale Retrospective Analysis of Ultrasound Images.

Authors:  Pradeeba Sridar; Ashnil Kumar; Ann Quinton; Narelle June Kennedy; Ralph Nanan; Jinman Kim
Journal:  IEEE J Transl Eng Health Med       Date:  2019-11-19       Impact factor: 3.316

6.  VP-Nets : Efficient automatic localization of key brain structures in 3D fetal neurosonography.

Authors:  Ruobing Huang; Weidi Xie; J Alison Noble
Journal:  Med Image Anal       Date:  2018-04-23       Impact factor: 8.545

7.  Fetal Ultrasound Image Segmentation for Automatic Head Circumference Biometry Using Deeply Supervised Attention-Gated V-Net.

Authors:  Yan Zeng; Po-Hsiang Tsui; Weiwei Wu; Zhuhuang Zhou; Shuicai Wu
Journal:  J Digit Imaging       Date:  2021-01-22       Impact factor: 4.056

8.  Feature-based fuzzy connectedness segmentation of ultrasound images with an object completion step.

Authors:  Sylvia Rueda; Caroline L Knight; Aris T Papageorghiou; J Alison Noble
Journal:  Med Image Anal       Date:  2015-07-17       Impact factor: 8.545

Review 9.  Automated Techniques for the Interpretation of Fetal Abnormalities: A Review.

Authors:  Vidhi Rawat; Alok Jain; Vibhakar Shrimali
Journal:  Appl Bionics Biomech       Date:  2018-06-10       Impact factor: 1.781

10.  Segmentation-Based vs. Regression-Based Biomarker Estimation: A Case Study of Fetus Head Circumference Assessment from Ultrasound Images.

Authors:  Jing Zhang; Caroline Petitjean; Samia Ainouz
Journal:  J Imaging       Date:  2022-01-25
  10 in total

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