Menuka M. Pallebage‐Gamarallage

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.

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 develops a Kinetic Tensor model to correct T2 inhomogeneity in post-mortem brain imaging by accounting for fixative outflux, showing improved alignment with histological markers.

The paper describes a pipeline for quantitative susceptibility and R2* mapping in post-mortem brains and compares results between ALS patients and controls using histology validation.

The paper introduces a pipeline for automatically aligning histological images with whole-brain MRI data, achieving sub-millimetre accuracy and outperforming manual methods.

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

This study investigates white matter degeneration in the perforant path of ALS patients using diffusion MRI, polarized light imaging, and immunohistochemistry, finding significant changes in fractional anisotropy and myelin density.