Amy F.D. Howard

The paper integrates 3D light-sheet microscopy with diffusion MRI to predict cellular features from MRI data across multiple mouse strains.

This paper develops a deep learning model using domain adaptation to predict high-resolution fibre orientations from diffusion MRI, informed by microscopy data, improving connectivity mapping in human brains.

This paper develops a hybrid diffusion MRI-microscopy tractography method to improve 3D brain connectivity reconstruction by combining high-resolution microscopy with diffusion MRI data.

The paper applies the BENCH framework to link diffusion MRI signal changes to microstructural features in brain tissue using histology data.

This study compares hippocampal structure and function across humans and macaques to show conservation of micro- and macro-structure but evolutionary reconfiguration in functional connectivity.

The paper introduces the BigMac dataset, combining multi-contrast MRI and microscopy data from a macaque brain, enabling multimodal analysis across scales and tissue states.

The paper introduces an automated pipeline for registering stand-alone histology sections to whole-brain MRI data with sub-voxel accuracy.

This paper introduces an automated pipeline to extract quantitative histological metrics for voxelwise MRI-histology comparisons and finds activated microglia strongly predicts DTI FA, suggesting diffusion MRI sensitivity to neuroinflammation.

This paper estimates axial diffusivity in the NODDI model using high b-value data and shows the impact of noise assumptions on parameter estimates.

This paper reviews post mortem methods to validate diffusion MRI tractography and microstructural properties of axon bundles.

The paper introduces the Digital Brain Bank, an open access platform providing curated post-mortem neuroimaging datasets across species and modalities for neuroanatomical and neuropathological research.

This paper proposes a joint model for diffusion MRI and microscopy data to improve microstructural analysis by combining complementary information from both modalities.