Yaël Balbastre

This study uses fast fMRI to characterize voxelwise auditory hemodynamic response functions (HRFs) and finds diverse, reliable, and regionally specific HRFs not captured by standard models.

The paper presents a multimodal imaging pipeline that combines diffusion MRI and high-resolution X-ray microscopy to map the human connectome across multiple scales.

This paper introduces VesSynth, a vessel segmentation framework trained on synthetic data that achieves state-of-the-art accuracy across multiple imaging modalities and spatial resolutions.

This paper uses HiP-CT to image microstructural fiber orientations in the human brain, showing greater complexity than dMRI while being non-destructive.

The paper presents a high-resolution isotropic human brain dataset and demonstrates its use for neuroanatomy analysis and visualization.

The paper introduces a fast segmentation tool for brain MRI scans using a hybrid method, achieving comparable accuracy to a Bayesian approach but with significantly reduced runtime.

The paper uses deformable cortical surfaces to evaluate MEG source reconstruction algorithms and fit metrics.

The paper introduces ISME, a sampling strategy that reduces cardiac-induced noise in brain maps of R2* and magnetic susceptibility, improving reproducibility.

The paper introduces NextBrain, a probabilistic histological atlas of the human brain, and presents a tool for automated MRI segmentation of anatomical regions.

The paper develops open-source tools for 3D analysis of brain dissection photographs and surface scans, achieving accurate reconstructions and segmentations comparable to MRI.

This paper introduces a semi-supervised segmentation model for identifying supragranular and infragranular layers in human cerebral cortex MRI scans with high precision.

The paper develops an imaging pipeline to create a cell census of the human cerebral cortex using MRI, immunohistochemistry, and light-sheet fluorescence microscopy.