Lucile Brun

Elbé Consulting

An accurate fibroglandular tissue (FGT) segmentation model was designed using of a deep learning strategy on T1w series without fat suppression. The proposed method combined a dedicated preprocessing and the training of a two-dimensional U-Net architecture on a multi-centric representative database to achieve an automatic FGT segmentation. The fina...

Sulcal pits are the points of maximal depth within the folds of the cortical surface. These shape descriptors give a unique opportunity to access to a rich, fine-scale rep- resentation of the geometry and the developmental milestones of the cortical surface. However, using sulcal pits analysis at group level requires new numerical tools to establis...

Diffusion MR images are prone to severe geometric distortions induced by head movement, eddy-current and inhomogeneity of magnetic susceptibility. Various correction methods have been proposed that depend on the choice of the acquisition settings and potentially provide highly different data quality. However, the impact of this choice has not been...

Despite the large variability of sulcal folds, their deepest points, namely the sulcal pits, provide a sparse and reproducible description of the cortical surface. Their role during the antenatal and pediatric development of the brain remains unclear. This work is the first study of the evolution of all sulcal pits during healthy pediatric developm...

Studying the topography of the cortex has proved valuable in order to characterize populations of subjects. In particular, the recent interest towards the deepest parts of the cortical sulci – the so-called sulcal pits – has opened new avenues in that regard. In this paper, we introduce the first fully automatic brain morphometry method based on th...

Background: Recent neuroimaging studies suggest that autism spectrum disorder results from abnormalities in the cortical folding pattern. Usual morphometric measurements have failed to provide reliable neuroanatomic markers. Here, we propose that sulcal pits, which are the deepest points in each fold, are suitable candidates to uncover this atypic...

This article contains data related to the research article Auzias et al. (2015) [1]. This data can be used as a benchmark for quantitative evaluation of sulcal pits extraction algorithm. In particular, it allows a quantitative comparison with our method, and the assessment of the consistency of the sulcal pits extraction across two well-matched pop...

Studying cortical anatomy by examining the deepest part of cortical sulci, the sulcal pits, has recently raised a growing interest. In particular, constructing structural representations from patterns of pits has proved a promising approach. This study follows up in this direction and brings two main contri-butions. First, we introduce a graph kern...

Recent interest has been growing concerning points of maximum depth within folds, the sulcal pits, that can be used as reliable cortical landmarks. These remarkable points on the cortical surface are defined algorithmically as the outcome of an automatic extraction procedure. The influence of several crucial parameters of the reference technique (I...