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Kuklisova-Murgasova, M.* ; Cifor, A.* ; Napolitano, R.* ; Papageorghiou, A.* ; Quaghebeur, G.* ; Rutherford, M.A.* ; Hajnal, J.V.* ; Noble, J.A.* ; Schnabel, J.A.*

Registration of 3D fetal neurosonography and MRI.

Med. Image Anal. 17, 1137-1150 (2013)
DOI PMC
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Open Access Green as soon as Postprint is submitted to ZB.
We propose a method for registration of 3D fetal brain ultrasound with a reconstructed magnetic resonance fetal brain volume. This method, for the first time, allows the alignment of models of the fetal brain built from magnetic resonance images with 3D fetal brain ultrasound, opening possibilities to develop new, prior information based image analysis methods for 3D fetal neurosonography. The reconstructed magnetic resonance volume is first segmented using a probabilistic atlas and a pseudo ultrasound image volume is simulated from the segmentation. This pseudo ultrasound image is then affinely aligned with clinical ultrasound fetal brain volumes using a robust block-matching approach that can deal with intensity artefacts and missing features in the ultrasound images. A qualitative and quantitative evaluation demonstrates good performance of the method for our application, in comparison with other tested approaches. The intensity average of 27 ultrasound images co-aligned with the pseudo ultrasound template shows good correlation with anatomy of the fetal brain as seen in the reconstructed magnetic resonance image.
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Publication type Article: Journal article
Document type Scientific Article
Keywords Block Matching ; Fetal 3d Ultrasound ; Fetal Neurosonography ; Mr Ultrasound Registration
Language english
Publication Year 2013
HGF-reported in Year 2013
ISSN (print) / ISBN 1361-8415
e-ISSN 1361-8415
Journal Medical Image Analysis
Quellenangaben Volume: 17, Issue: 8, Pages: 1137-1150 Article Number: , Supplement: ,
Publisher Elsevier
Reviewing status Peer reviewed
Institute(s) Institute for Machine Learning in Biomed Imaging (IML)
POF-Topic(s) 30205 - Bioengineering and Digital Health
Research field(s) Enabling and Novel Technologies
PSP Element(s) G-507100-001
DOI 10.1016/j.media.2013.07.004
Scopus ID 84882770964
PubMed ID 23969169
Erfassungsdatum 2022-09-06
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