Phase-based feature detection in fetal ultrasound images

Weiming Wang, Lei Zhu, Yim Pan Chui, Jing Qin, Pheng Ann Heng

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

1 Citation (Scopus)


Detection of image features is an essential step in many medical applications. However, it is very challenging to accurately extract important features from ultrasound data that is corrupted by various imaging artifacts. Traditional intensity-based methods generally have poor performance in detecting salient features from ultrasound images. In contrast, phase-base approaches have been shown to perform well in these images because they are theoretically intensity invariant. In this paper, we extend previous phase-based methods to the field of fetal ultrasound images to detect both symmetric and asymmetric features, which correspond to ridge-like and step edge-like object boundaries, respectively. This is achieved by exploiting local phase-based measures computed from a 2D isotropic analytic signal: monogenic signal. Experimental results in clinical images demonstrate the outperformance of the proposed approach.
Original languageEnglish
Title of host publicationICIST 2014 - Proceedings of 2014 4th IEEE International Conference on Information Science and Technology
Number of pages4
ISBN (Electronic)9781479948086
Publication statusPublished - 1 Jan 2014
Externally publishedYes
Event2014 4th IEEE International Conference on Information Science and Technology, ICIST 2014 - Shenzhen, China
Duration: 26 Apr 201428 Apr 2014


Conference2014 4th IEEE International Conference on Information Science and Technology, ICIST 2014


  • analytic signal
  • Feature detection
  • fetal ultrasound images
  • local phase
  • symmetry and asymmetry

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Information Systems


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