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Volumetric Segmentation of Key Fetal Brain Structures in 3D Ultrasound

  • Mohammad Yaqub
  • Remi Cuingnet
  • Raffaele Napolitano
  • David Roundhill
  • Aris Papageorghiou
  • Roberto Ardon
  • J. Alison Noble
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8184)

Abstract

Neurosonography is the most widely used imaging technique for assessing neuro-development of the growing fetus in clinical practice. 3D neurosonography has an advantage of quick acquisition but is yet to demonstrate improvements in clinical workflow. In this paper we propose an automatic technique to segment four important fetal brain structures in 3D ultrasound. The technique is built within a Random Decision Forests framework. Our solution includes novel pre-processing and new features. The pre-processing step makes sure that all volumes are in the same coordinate. The new features constrain the appearance framework by adding a novel distance feature. Validation on 51 3D fetal neurosonography images shows that the proposed technique is capable of segmenting fetal brain structures and providing promising qualitative and quantitative results.

Keywords

3D ultrasound segmentation fetal brain random decision forests 

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Copyright information

© Springer International Publishing Switzerland 2013

Authors and Affiliations

  • Mohammad Yaqub
    • 1
  • Remi Cuingnet
    • 2
  • Raffaele Napolitano
    • 3
  • David Roundhill
    • 4
  • Aris Papageorghiou
    • 3
  • Roberto Ardon
    • 2
  • J. Alison Noble
    • 1
  1. 1.Institute of Biomedical EngineeringUniversity of OxfordOxfordUK
  2. 2.Medisys Research Lab, Philips ResearchParisFrance
  3. 3.Nuffield Department of Obstetrics and GynaecologyUniversity of OxfordOxfordUK
  4. 4.Philips UltrasoundBothellUSA

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