Bruce R. Fischl

This study identifies and characterizes fifteen subnetworks within subcortical brain regions, revealing their functional organization and potential applications in understanding neuropsychiatric disorders.

The paper predicts age and MMSE scores from brain connectivity graphs using a graph-based deep learning model, showing improved performance over existing methods.

This paper introduces a deep-learning method that improves cortical registration by integrating structural and diffusion MRI data with connectivity features, showing better functional alignment than FreeSurfer.

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.

This paper estimates spatial image gradients from diffusion MRI signals by modeling relaxation-time properties, showing significant correlation with gold-standard gradients across multiple datasets.

This paper introduces a distribution-matching method to harmonize structural brain connectivity across sites and scanners, showing competitive performance compared to existing methods.

This paper evaluates two methods for automatically estimating the locus coeruleus region from standard T1-weighted MRI scans using non-contrast neuroanatomical data.

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.

This paper introduces a multi-scale imaging technique combining PSOCT and 2PM to enable label-free, high-resolution analysis of human brain structure and pathology.

This paper introduces a method to measure 3D fiber orientation in the human brain using two illumination angles in PS-OCT, achieving high angular precision and detailed 3D maps.

The paper explores correlations between human structural brain connectivity and non-MRI variables in Alzheimer's disease, finding stronger associations with augmented connectivity and age-related decreases in connectivity.

The paper maps brainstem connections sustaining wakefulness using ex vivo diffusion MRI, immunohistochemistry, and in vivo 7 Tesla functional MRI.

This paper introduces a method to normalize MRI intensity values across scans, improving consistency in volume measurements and spatial overlap between images.

This paper quantifies myelin content and neuron density in the human brain using OCT, finding a strong linear relationship between scattering coefficient and myelin content.

This paper maps subcortical connectivity of the human default mode network using rs-fMRI and a novel tensor decomposition method, identifying key subcortical regions correlated with the DMN.

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

This study quantifies volumetric morphometry and optical properties of human cerebellar cortex at micrometer resolution using as-PSOCT, revealing layer-specific variations and cross-subject variability.

This study validates compressed sensing for DSI reconstruction, showing high fidelity at R=3 with reduced acquisition time, but degradation at higher acceleration factors.

This paper quantifies structural brain connectivity using diffusion MRI in aging and dementia, finding age-related trends and regional effects that suggest potential for age prediction and studying structural connections.

This paper compares two whole-brain segmentation methods, ASEG and SAMSEG, in FreeSurfer, finding SAMSEG provides more reliable and sensitive measurements for detecting longitudinal changes and Alzheimer's disease-related atrophy.

This study uses ex vivo diffusion MRI and histopathology to correlate tract disruptions with axonal injury in a TBI patient.

This paper introduces an algorithm to optimize generalized gamma distributed multiplicative noise in OCT images, improving speckle removal and contrast-to-noise ratio.

This study introduces a lesion correction method for cortical volumetric analysis in TBI patients, improving accuracy and enabling inclusion of lesioned brains in network-based analyses.

The paper presents an ultra-high resolution MRI dataset of an ex vivo human brain and provides it in both native and stereotactic spaces for research and educational use.

This paper introduces a new structural connectivity measure that better correlates with functional connectivity and improves Alzheimer's disease staging compared to streamline tractography.

This paper evaluates methods for mapping between MNI152/Colin27 and fsaverage coordinate systems, finding that registration fusion with ANTs performs best for new subjects.