Yogesh Rathi A

This paper introduces DIFFUSE, a framework for joint k-q-TE image reconstruction in diffusion MRI, showing improved error reduction and multi-contrast reconstruction.

ROVER-dMRI improves high-SNR whole-brain mesoscale diffusion MRI with reduced scan time and preserved fiber details.

This study evaluates whether cross-population white matter atlases improve test-retest reproducibility compared to single-population atlases in diffusion MRI tractography.

This paper introduces FCG, a technique that corrects spatiotemporal-varying phase errors in EPI using an MLP, improving image quality on high-performance systems.

MaxEnt-DTD estimates diffusion tensor distributions from dMRI data, providing reliable joint fiber-orientation and microstructure analysis.

This study systematically evaluates U-fiber organization in the rhesus monkey brain using tract tracing, revealing sulcus-dependent prevalence and diverse trajectories, challenging the notion of a uniform U-fiber system.

ACCURAT provides an open framework and neuroanatomical reference for reconstructing cerebellar pathways using diffusion MRI and anatomical priors.

This study identifies sex differences in white matter tracts using diffusion MRI tractography and finds associations with motor function in a large cohort.

This study evaluates diffusion MRI contrasts for cerebellar segmentation, finding that spherical mean images outperform traditional microstructure maps.

This study examines the role of superficial white matter connections of Broca's area in language performance across children and adults, finding bilateral associations with language tasks.

This paper introduces RISH-GLM, a method to harmonize diffusion MRI data across sites without requiring matched training subjects, showing effectiveness with unmatched groups and multiple sites.

This study examines cerebellar pathway microstructure and cognitive performance in over 9,000 participants, finding consistent associations across pre-adolescents and young adults.

This paper introduces FMQ Regression to analyze white matter microstructure and its relationship to cognitive and motor factors, finding stronger associations in bundle periphery and sex-specific differences.

This paper introduces DeepRGVP, a deep learning framework for automatically identifying the retinogeniculate visual pathway from diffusion MRI tractography data, showing superior performance compared to existing methods.

This study compares multi-echo and time-division multiplexing sequences for relaxation-diffusion MRI, finding TDM provides more accurate T2 estimates and microstructure measures with faster acquisition.

The paper harmonizes diffusion MRI data from the ABCD study and provides white matter measures for structural connectivity research in adolescents.

This paper introduces a domain-agnostic MR reconstruction framework using a randomly weighted neural network that achieves performance comparable to state-of-the-art methods with minimal training data.

This paper introduces a method to model combined relaxation diffusion MRI data by characterizing b-value dependent T2 relaxation rates to improve neurite microstructure characterization.

This study investigates the role of superficial white matter microstructure in processing speed in cerebral small vessel disease, finding that free-water measures in SWM strongly correlate with cognitive decline.

This study evaluates variability in white matter bundle segmentation across 42 groups using the same dataset, finding protocol variability exceeds other sources of inconsistency.

This study compares four tractography methods for reconstructing the retinogeniculate visual pathway using diffusion MRI data from 57 subjects, finding that UKF-2T and iFOD1 provide the best results.

The paper evaluates the ComBat method for multi-site diffusion MRI harmonization, finding that it preserves biological variability in some sites but not others and is sensitive to preprocessing differences.

The paper maps individual deviations from normative brain structure in schizophrenia patients and finds high heterogeneity, with most patients showing infra-normal deviations in at least one region.

The paper introduces a novel parcellation system for the rhesus monkey brain based on a standardized ontology, aiming to facilitate comparative studies with the human brain.

This paper creates a novel trigeminal tractography atlas for automated trigeminal nerve identification using dMRI data, showing comparable results to manual methods with advantages in efficiency and robustness.

This study creates a detailed 3D map of the human brainstem using high-resolution MRI and validates it against histological atlases.

This paper introduces REDIM, a method to compute joint moments of relaxation-diffusion to characterize neural microstructure, showing it can distinguish fiber bundles with similar orientations but different relaxation rates.

This study uses diffusion MRI tractography to map individual variations of the human corticospinal tract and hand-related motor fibers, creating a database of their volume, length, and biophysical parameters.

This study evaluates modern diffusion tractography methods using a standardized challenge, finding no significant improvement in anatomical accuracy despite methodological advances.

This paper presents a diffusion MRI harmonization method that removes scanner-specific effects across sites while preserving inter-subject variability, validated on two clinical cohorts.