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

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

Diffusion MRI outside the brain

This manuscript provides an overview of recent developments in Diffusion-Weighted Imaging (DWI) outside the brain, focusing on liver, breast, prostate, muskuloskeletal (MSK) and cardiac applications. A general introduction to cross-cutting acquisition and image processing challenges is first provided. These often include short T2 relaxation times, the need to image a large field-of-view with the resulting complications in shimming the B0 field and achieving good fat suppression. Some of the strategies developed for dealing with motion, namely cardiac and respiratory motion are described. Specific sections are then presented for each of the aforementioned organs. A motivation for the clinical applicability of DWI is first provided, followed by specific image acquisition and processing considerations. Quantitative imaging is becoming standard in clinical practice, and the Apparent Diffusion Coefficient is routinely estimated in the liver, breast and prostate. Application of alternative signal models in these organs is being explored, including both the Intravoxel Incoherent Motion and Diffusion Kurtosis models. Ongoing efforts are focused on evaluating the potential clinical added value of the extra parameters and on improving their repeatability. MSK and cardiac DWI have shown potential for assessing pathological changes in fiber architecture, but further validation is required to enable application in the clinical setting.info:eu-repo/semantics/publishedVersio