Literature DB >> 28408290

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

Sébastien Tourbier1, Clemente Velasco-Annis2, Vahid Taimouri2, Patric Hagmann3, Reto Meuli3, Simon K Warfield2, Meritxell Bach Cuadra4, Ali Gholipour2.   

Abstract

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.
Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

Entities:  

Keywords:  B-Spline deformation; Block matching; Brain localization; Fetal brain MRI; Slice-by-slice brain extraction; Slice-to-template registration; Super-resolution reconstruction

Mesh:

Year:  2017        PMID: 28408290      PMCID: PMC5513844          DOI: 10.1016/j.neuroimage.2017.04.004

Source DB:  PubMed          Journal:  Neuroimage        ISSN: 1053-8119            Impact factor:   6.556


  29 in total

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8.  PVR: Patch-to-Volume Reconstruction for Large Area Motion Correction of Fetal MRI.

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9.  Automatic extraction of the intracranial volume in fetal and neonatal MR scans using convolutional neural networks.

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10.  Automated Brain Masking of Fetal Functional MRI with Open Data.

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  10 in total

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