Automated template-based brain localization and extraction for fetal brain MRI reconstruction.

Détails

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Etat: Public
Version: Final published version
ID Serval
serval:BIB_F129C2509552
Type
Article: article d'un périodique ou d'un magazine.
Collection
Publications
Titre
Automated template-based brain localization and extraction for fetal brain MRI reconstruction.
Périodique
NeuroImage
Auteur(s)
Tourbier S., Velasco-Annis C., Taimouri V., Hagmann P., Meuli R., Warfield S.K., Bach Cuadra M., Gholipour A.
ISSN
1095-9572 (Electronic)
ISSN-L
1053-8119
Statut éditorial
Publié
Date de publication
15/07/2017
Peer-reviewed
Oui
Volume
155
Pages
460-472
Langue
anglais
Notes
Publication types: Journal Article
Publication Status: ppublish
Résumé
Most fetal brain MRI reconstruction algorithms rely only on brain tissue-relevant voxels of low-resolution (LR) images to enhance the quality of inter-slice motion correction and image reconstruction. Consequently the fetal brain needs to be localized and extracted as a first step, which is usually a laborious and time consuming manual or semi-automatic task. We have proposed in this work to use age-matched template images as prior knowledge to automatize brain localization and extraction. This has been achieved through a novel automatic brain localization and extraction method based on robust template-to-slice block matching and deformable slice-to-template registration. Our template-based approach has also enabled the reconstruction of fetal brain images in standard radiological anatomical planes in a common coordinate space. We have integrated this approach into our new reconstruction pipeline that involves intensity normalization, inter-slice motion correction, and super-resolution (SR) reconstruction. To this end we have adopted a novel approach based on projection of every slice of the LR brain masks into the template space using a fusion strategy. This has enabled the refinement of brain masks in the LR images at each motion correction iteration. The overall brain localization and extraction algorithm has shown to produce brain masks that are very close to manually drawn brain masks, showing an average Dice overlap measure of 94.5%. We have also demonstrated that adopting a slice-to-template registration and propagation of the brain mask slice-by-slice leads to a significant improvement in brain extraction performance compared to global rigid brain extraction and consequently in the quality of the final reconstructed images. Ratings performed by two expert observers show that the proposed pipeline can achieve similar reconstruction quality to reference reconstruction based on manual slice-by-slice brain extraction. The proposed brain mask refinement and reconstruction method has shown to provide promising results in automatic fetal brain MRI segmentation and volumetry in 26 fetuses with gestational age range of 23 to 38 weeks.

Mots-clé
Brain/diagnostic imaging, Brain/embryology, Female, Gestational Age, Humans, Image Processing, Computer-Assisted/methods, Magnetic Resonance Imaging/methods, Neuroimaging/methods, Pregnancy, Prenatal Diagnosis/methods, B-Spline deformation, Block matching, Brain localization, Fetal brain MRI, Slice-by-slice brain extraction, Slice-to-template registration, Super-resolution reconstruction
Pubmed
Web of science
Open Access
Oui
Création de la notice
19/06/2017 14:00
Dernière modification de la notice
20/08/2019 16:18
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