Literature DB >> 19964738

Improved segmentation of ultrasound images for fetal biometry, using morphological operators.

Vibhakar Shrimali1, R S Anand, Vinod Kumar.   

Abstract

Currently, radiologists indicate the femur endpoints with an interactive marker device; however, these measurements are subjective and have proved to be inconsistent. The main objective of this work is to obtain a time-efficient morphology-based algorithm to recognize femur contour in fetal ultrasound images, refine its shape for automatic length measurement, and thus, attaining accuracy and reproducibility of measurement. To achieve these objectives a cross-sectional study with subjects belonging to different family units of different communities was carried out. The images obtained from the subjects were initially processed using morphological operators to remove the background from the image. Thereafter, to refine the shape of the femur, the images were metamorphosed, using the morphological operators, till a single pixel - wide skeleton of the femur was available in the most time-effective manner. The skeleton-end-points are assumed to be the femur-end-points, and the femur length is calculated as the distance between the end-points to estimate gestational age. The mean execution time of the proposed algorithm was around 4 seconds. Measurements, performed using the automation algorithm, were found to be closely correlated to those obtained manually. The proposed algorithm was found to be time-efficient, and the results obtained were comparable to those derived through the existing methods for estimation of gestational age.

Mesh:

Year:  2009        PMID: 19964738     DOI: 10.1109/IEMBS.2009.5334470

Source DB:  PubMed          Journal:  Conf Proc IEEE Eng Med Biol Soc        ISSN: 1557-170X


  4 in total

1.  Automated region mask for four-chamber fetal heart biometry.

Authors:  S Vijayalakshmi; N Sriraam; S Suresh; S Muttan
Journal:  J Clin Monit Comput       Date:  2012-10-21       Impact factor: 2.502

2.  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

3.  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 4.  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

  4 in total

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