A Conceptual Framework for Fetus Head Analysis Based on Ultrasound Images

Mahmood Alzubaidi, Marco Agus, Uzair Shah, Michel Makhlouf, Khalid Alyafei, Ali Zaidi, Mowafa Househ*

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Ultrasound images are the most used imaging methodologies in obstetrics to monitor the growth of a fetus during the gestation period. In particular, the obstetrician uses fetus head images to monitor the growth state and identify essential features such as Gestational age (GA), estimated fetus weight (EFW), and brain anatomical structures. However, this work requires an expert obstetrician, and it is time-consuming and costly. Therefore, we proposed an automatic framework by adopting a hybrid approach that combines three components i) automatic segmentation to segment the region of interest (ROI) in the fetus head, ii) measurement extraction to measure the segmented ROI, and iii) anomaly and features detection to predict fetus GA, EFW, and abnormality status.

Original languageEnglish
Title of host publicationAdvances in Informatics, Management and Technology in Healthcare
EditorsJohn Mantas, Parisis Gallos, Emmanouil Zoulias, Arie Hasman, Mowafa S. Househ, Marianna Diomidous, Joseph Liaskos, Martha Charalampidou
PublisherIOS Press BV
Pages574-577
Number of pages4
ISBN (Electronic)9781643682907
DOIs
Publication statusPublished - 2022

Publication series

NameStudies in Health Technology and Informatics
Volume295
ISSN (Print)0926-9630
ISSN (Electronic)1879-8365

Keywords

  • Estimated fetus weight
  • Gestational age
  • Image segmentation
  • Ultrasound
  • fetus abnormality
  • fetus head

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