Karthik Ramadass

According to our database, Karthik Ramadass authored at least 19 papers between 2022 and 2026.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2026

Unsupervised learning of acquisition variability in structural connectomes via hybrid latent space modeling.

Gaurav Rudravaram, Lianrui Zuo, Karthik Ramadass, Elyssa M. McMaster, Jongyeon Yoon, Aravind R. Krishnan, Adam M. Saunders, Chenyu Gao, Nancy R. Newlin, Praitayini Kanakaraj, Lori L. Beason-Held, Murat Bilgel, Laura A. Barquero, Micah D'Archangel, Tin Q. Nguyen, Laurie B. Cutting, Derek B. Archer, Timothy J. Hohman, Daniel Moyer, Bennett A. Landman

CoRR, May, 2026

An Artifact-based Agent Framework for Adaptive and Reproducible Medical Image Processing.

Lianrui Zuo, Yihao Liu, Gaurav Rudravaram, Karthik Ramadass, Aravind R. Krishnan, Michael D. Phillips, Yelena G. Bodien, Mayur B. Patel, Paula Trujillo, Yency Forero Martinez, Stephen A. Deppen, Eric L. Grogan, Fabien Maldonado, Kevin McGann, Hudson M. Holmes, Laurie E. Cutting, Yuankai Huo, Bennett A. Landman

CoRR, April, 2026

Harmonization Mitigates Diffusion MRI Scanner Effects in Infancy: Insights From the Healthy Brain and Child Development (HBCD) Study.

Elyssa M. McMaster, Gaurav Rudravaram, Michael E. Kim, Trent M. Schwartz, Chloe Scholten, Jongyeon Yoon, Adam M. Saunders, Andre T. S. Hucke, Karthik Ramadass, Emily M. Harriott, Steven L. Meisler, Simon N. Vandekar, Allen T. Newton, Seth A. Smith, Saikat Sengupta, Kathryn L. Humphreys, Sarah Osmundson, Daniel Moyer, Laurie E. Cutting, Bennett A. Landman

Proceedings of the 23rd IEEE International Symposium on Biomedical Imaging, 2026

2025

Secondary use of radiological imaging data: Vanderbilt's ImageVU approach.

David S. Smith, Karthik Ramadass, Laura M. Jones, Jennifer Morse, Daniel Fabbri, Joseph R. Coco, Shunxing Bao, Melissa A. Basford, Peter J. Embi, Reed A. Omary, John C. Gore, Jill M. Pulley, Bennett A. Landman

J. Biomed. Informatics, 2025

2024

Brain age identification from diffusion MRI synergistically predicts neurodegenerative disease.

Chenyu Gao, Michael E. Kim, Karthik Ramadass, Praitayini Kanakaraj, Aravind R. Krishnan, Adam M. Saunders, Nancy R. Newlin, Ho Hin Lee, Qi Yang, Warren D. Taylor, Brian D. Boyd, Lori L. Beason-Held, Susan M. Resnick, Lisa L. Barnes, David A. Bennett, Katherine D. Van Schaik, Derek B. Archer, Timothy J. Hohman, Angela L. Jefferson, Ivana Isgum, Daniel Moyer, Yuankai Huo, Kurt G. Schilling, Lianrui Zuo, Shunxing Bao, Nazirah Mohd Khairi, Zhiyuan Li, Christos Davatzikos, Bennett A. Landman

CoRR, 2024

Scalable quality control on processing of large diffusion-weighted and structural magnetic resonance imaging datasets.

Michael E. Kim, Chenyu Gao, Karthik Ramadass, Praitayini Kanakaraj, Nancy R. Newlin, Gaurav Rudravaram, Kurt G. Schilling, Blake E. Dewey, David A. Bennett, Sid OBryant, Robert C. Barber, Derek B. Archer, Timothy J. Hohman, Shunxing Bao, Zhiyuan Li, Bennett A. Landman, Nazirah Mohd Khairi, Alzheimer's Disease Neuroimaging Initiative, HABSHD Study Team

CoRR, 2024

Scalable, reproducible, and cost-effective processing of large-scale medical imaging datasets.

Michael E. Kim, Karthik Ramadass, Chenyu Gao, Praitayini Kanakaraj, Nancy R. Newlin, Gaurav Rudravaram, Kurt G. Schilling, Blake E. Dewey, Derek B. Archer, Timothy J. Hohman, Zhiyuan Li, Shunxing Bao, Bennett A. Landman, Nazirah Mohd Khairi

CoRR, 2024

2023

Robust Fiber ODF Estimation Using Deep Constrained Spherical Deconvolution for Diffusion MRI.

Tianyuan Yao, Francois Rheault, Leon Y. Cai, Vishwesh Nath, Zuhayr Asad, Nancy Newlin, Can Cui, Ruining Deng, Karthik Ramadass, Andrea T. Shafer, Susan M. Resnick, Kurt Schilling, Bennett A. Landman, Yuankai Huo

CoRR, 2023

Exploring shared memory architectures for end-to-end gigapixel deep learning.

Lucas W. Remedios, Leon Y. Cai, Samuel W. Remedios, Karthik Ramadass, Aravind R. Krishnan, Ruining Deng, Can Cui, Shunxing Bao, Lori A. Coburn, Yuankai Huo, Bennett A. Landman

CoRR, 2023

A Unified Single-stage Learning Model for Estimating Fiber Orientation Distribution Functions on Heterogeneous Multi-shell Diffusion-weighted MRI.

Tianyuan Yao, Nancy Newlin, Praitayini Kanakaraj, Vishwesh Nath, Leon Y. Cai, Karthik Ramadass, Kurt Schilling, Bennett A. Landman, Yuankai Huo

CoRR, 2023

Deep constrained spherical deconvolution for robust harmonization.

Tianyuan Yao, Francois Rheault, Leon Y. Cai, Vishwesh Nath, Zuhayr Asad, Nancy Newlin, Can Cui, Ruining Deng, Karthik Ramadass, Kurt Schilling, Bennett A. Landman, Yuankai Huo

Proceedings of the Medical Imaging 2023: Image Processing, 2023

Deep whole brain segmentation of 7T structural MRI.

Karthik Ramadass, Xin Yu, Leon Y. Cai, Yucheng Tang, Shunxing Bao, Cailey I. Kerley, Micah D'Archangel, Laura A. Barquero, Allen T. Newton, Isabel Gauthier, Rankin W. McGugin, Benoit M. Dawant, Laurie E. Cutting, Yuankai Huo, Bennett A. Landman

Proceedings of the Medical Imaging 2023: Image Processing, 2023

A Unified Learning Model for Estimating Fiber Orientation Distribution Functions on Heterogeneous Multi-shell Diffusion-Weighted MRI.

Tianyuan Yao, Nancy Newlin, Praitayini Kanakaraj, Vishwesh Nath, Leon Y. Cai, Karthik Ramadass, Kurt Schilling, Bennett A. Landman, Yuankai Huo

Proceedings of the Computational Diffusion MRI - 14th International Workshop, 2023

2022

SLANT-TICV (Skull stripped): Generalizing deep learning brain segmentation for skull removal and intracranial measurements.

Liu Yue, Karthik Ramadass, Michael Kim, Chenyu Gao, Adam M. Saunders, Shunxing Bao, Yuankai Huo, Ilwoo Lyu, Bennett A. Landman

Dataset, May, 2022

Workflow Integration of Research AI Tools into a Hospital Radiology Rapid Prototyping Environment.

Praitayini Kanakaraj, Karthik Ramadass, Shunxing Bao, Melissa A. Basford, Laura M. Jones, Ho Hin Lee, Kaiwen Xu, Kurt G. Schilling, John Jeffrey Carr, James G. Terry, Yuankai Huo, Kim L. Sandler, Allen T. Netwon, Bennett A. Landman

J. Digit. Imaging, 2022

Integrating the BIDS Neuroimaging Data Format and Workflow Optimization for Large-Scale Medical Image Analysis.

Shunxing Bao, Brian D. Boyd, Praitayini Kanakaraj, Karthik Ramadass, Francisco A. C. Meyer, Yuqian Liu, William E. Duett, Yuankai Huo, Ilwoo Lyu, David H. Zald, Seth A. Smith, Baxter P. Rogers, Bennett A. Landman

J. Digit. Imaging, 2022

Ultra-high-resolution mapping of cortical layers 3T-guided 7T MRI.

Karthik Ramadass, Francois Rheault, Leon Y. Cai, Lucas W. Remedios, Micah D'Archangel, Ilwoo Lyu, Laura A. Barquero, Allen T. Newton, Laurie E. Cutting, Yuankai Huo, Bennett A. Landman

Proceedings of the Medical Imaging 2022: Image Processing, 2022

Mapping the impact of non-linear gradient fields on diffusion MRI tensor estimation.

Praitayini Kanakaraj, Colin B. Hansen, Francois Rheault, Leon Y. Cai, Karthik Ramadass, Baxter P. Rogers, Kurt G. Schilling, Bennett A. Landman

Proceedings of the Medical Imaging 2022: Image Processing, 2022

Multimodal neuroimaging in pediatric type 1 diabetes: a pilot multisite feasibility study of acquisition quality, motion, and variability.

Leon Y. Cai, Costin Tanase, Adam W. Anderson, Karthik Ramadass, Francois Rheault, Chelsea A. Lee, Niral J. Patel, Sky Jones, Lauren M. LeStourgeon, Alix Mahon, Sumit Pruthi, Kriti Gwal, Arzu Ozturk, Hakmook Kang, Nicole Glaser, Simona Ghetti, Sarah S. Jaser, Lori C. Jordan, Bennett A. Landman

Proceedings of the Medical Imaging 2022: Image Processing, 2022