3 citations · 11 across the 19 of their papers we have counts for
22 papers
Separating mixtures of single-fiber orientation distributions for increased sensitivity to crossing white matter fibers
Adam M. Saunders, Gaurav Rudravaram, Michael E. Kim +10
Intro: Diffusion MRI allows for in vivo probing of brain tissue architecture via micron-level diffusion aggregated at the millimeter scale, but crossing white matter fibers decreas…
Generalizable field of view extension for diffusion MRI via conditional flow matching
Gaurav Rudravaram, Lianrui Zuo, Ema Topolnjak +22
Incomplete field-of-view (FOV) diffusion MRI (dMRI) acquisitions compromise whole-brain white matter analysis by excluding brain regions from tractography and connectivity studies.…
Large-Scale Deployment and Analytical Implications of Structured Quality Control in Diffusion Magnetic Resonance Imaging
Michael E. Kim, Chenyu Gao, Karthik Ramadass +17
Purpose: Diffusion MRI (dMRI) provides a diverse set of quantitative measures and derived datatypes to assess white matter microstructure and macrostructure. Coupled with the incre…
Unsupervised learning of acquisition variability in structural connectomes via hybrid latent space modeling
Gaurav Rudravaram, Lianrui Zuo, Karthik Ramadass +17
Acquisition differences across sites, scanners, and protocols in dMRI introduce variability that complicates structural connectome analysis. This motivates deep learning models tha…
Evaluation of neuroCombat and deep learning harmonization for multi-site magnetic resonance neuroimaging in youth with prenatal alcohol exposure
Chloe Scholten, Elyssa M. McMaster, Adam M. Saunders +8
In cases of prevalent diseases and disorders, such as Prenatal Alcohol Exposure (PAE), multi-site data collection allows for increased study samples. However, multi-site studies in…
Harmonization mitigates diffusion MRI scanner effects in infancy: insights from the HEALthy Brain and Childhood Development (HBCD) study
Elyssa M. McMaster, Gaurav Rudravaram, Michael E. Kim +17
The HEALthy Brain and Childhood Development (HBCD) Study is an ongoing longitudinal initiative to understand population-level brain maturation; however, large-scale studies must ov…
Personalized White Matter Bundle Segmentation for Early Childhood
Elyssa M. McMaster, Michael E. Kim, Nancy R. Newlin +12
White matter segmentation methods from diffusion magnetic resonance imaging range from streamline clustering-based approaches to bundle mask delineation, but none have proposed a p…
Quality assurance of the Federal Interagency Traumatic Brain Injury Research (FITBIR) database for multi-site MRI analysis
Adam M. Saunders, Michael E. Kim, Gaurav Rudravaram +8
The Federal Interagency Traumatic Brain Injury Research (FITBIR) database is a centralized data repository for traumatic brain injury (TBI) research. It includes over 45,529 magnet…
Characterizing Continuous and Discrete Hybrid Latent Spaces for Structural Connectomes
Gaurav Rudravaram, Lianrui Zuo, Adam M. Saunders +12
Structural connectomes are detailed graphs that map how different brain regions are physically connected, offering critical insight into aging, cognition, and neurodegenerative dis…
DeepFixel: Crossing white matter fiber identification through spherical convolutional neural networks
Adam M. Saunders, Lucas W. Remedios, Elyssa M. McMaster +6
Diffusion-weighted magnetic resonance imaging allows for reconstruction of models for structural connectivity in the brain, such as fiber orientation distribution functions (ODFs)…
Phenotype discovery of traumatic brain injury segmentations from heterogeneous multi-site data
Adam M. Saunders, Michael E. Kim, Gaurav Rudravaram +8
Traumatic brain injury (TBI) is intrinsically heterogeneous, and typical clinical outcome measures like the Glasgow Coma Scale complicate this diversity. The large variability in s…
Lifespan Pancreas Morphology for Control vs Type 2 Diabetes using AI on Largescale Clinical Imaging
Lucas W. Remedios, Chloe Cho, Trent M. Schwartz +11
Purpose: Understanding how the pancreas changes is critical for detecting deviations in type 2 diabetes and other pancreatic disease. We measure pancreas size and shape using morph…
Data-Driven Abdominal Phenotypes of Type 2 Diabetes in Lean, Overweight, and Obese Cohorts
Lucas W. Remedios, Chloe Cho, Trent M. Schwartz +10
Purpose: Although elevated BMI is a well-known risk factor for type 2 diabetes, the disease's presence in some lean adults and absence in others with obesity suggests that detailed…
Multipath cycleGAN for harmonization of paired and unpaired low-dose lung computed tomography reconstruction kernels
Aravind R. Krishnan, Thomas Z. Li, Lucas W. Remedios +12
Reconstruction kernels in computed tomography (CT) affect spatial resolution and noise characteristics, introducing systematic variability in quantitative imaging measurements such…
Investigating the impact of kernel harmonization and deformable registration on inspiratory and expiratory chest CT images for people with COPD
Aravind R. Krishnan, Yihao Liu, Kaiwen Xu +9
Paired inspiratory-expiratory CT scans enable the quantification of gas trapping due to small airway disease and emphysema by analyzing lung tissue motion in COPD patients. Deforma…
Brain age identification from diffusion MRI synergistically predicts neurodegenerative disease
Chenyu Gao, Michael E. Kim, Karthik Ramadass +27
Estimated brain age from magnetic resonance image (MRI) and its deviation from chronological age can provide early insights into potential neurodegenerative diseases, supporting ea…
Sensitivity of quantitative diffusion MRI tractography and microstructure to anisotropic spatial sampling
Elyssa M. McMaster, Nancy R. Newlin, Chloe Cho +10
Purpose: Diffusion weighted MRI (dMRI) and its models of neural structure provide insight into human brain organization and variations in white matter. A recent study by McMaster,…
Influence of Early through Late Fusion on Pancreas Segmentation from Imperfectly Registered Multimodal MRI
Lucas W. Remedios, Han Liu, Samuel W. Remedios +7
Multimodal fusion promises better pancreas segmentation. However, where to perform fusion in models is still an open question. It is unclear if there is a best location to fuse inf…
Comparison and calibration of MP2RAGE quantitative T1 values to multi-TI inversion recovery T1 values
Adam M. Saunders, Michael E. Kim, Chenyu Gao +6
While typical qualitative T1-weighted magnetic resonance images reflect scanner and protocol differences, quantitative T1 mapping aims to measure T1 independent of these effects. C…
Harmonized connectome resampling for variance in voxel sizes
Elyssa M. McMaster, Nancy R. Newlin, Gaurav Rudravaram +10
To date, there has been no comprehensive study characterizing the effect of diffusion-weighted magnetic resonance imaging voxel resolution on the resulting connectome for high reso…
Data-driven Nucleus Subclassification on Colon H&E using Style-transferred Digital Pathology
Lucas W. Remedios, Shunxing Bao, Samuel W. Remedios +16
Understanding the way cells communicate, co-locate, and interrelate is essential to furthering our understanding of how the body functions. H&E is widely available, however, cell s…
Super-resolution multi-contrast unbiased eye atlases with deep probabilistic refinement
Ho Hin Lee, Adam M. Saunders, Michael E. Kim +15
Purpose: Eye morphology varies significantly across the population, especially for the orbit and optic nerve. These variations limit the feasibility and robustness of generalizing…