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Daniel Moyer

Showing results (41-50 of 56) with videos related to

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Medrxiv : the Preprint Server for Health Sciences|September 4, 2023
Characterizing patterns of diffusion tensor imaging variance in aging brainsChenyu Gao, Qi Yang, Michael E Kim, et al.
Journal of Medical Imaging (Bellingham, Wash.)|August 26, 2024
Characterizing patterns of diffusion tensor imaging variance in aging brainsChenyu Gao, Qi Yang, Michael E Kim, et al.
Research Square|November 28, 2023
DeepN4: Learning N4ITK Bias Field Correction for T1-weighted ImagesPraitayini Kanakaraj, Tianyuan Yao, Leon Y Cai, et al.
Neuroinformatics|March 25, 2024
DeepN4: Learning N4ITK Bias Field Correction for T1-weighted ImagesPraitayini Kanakaraj, Tianyuan Yao, Leon Y Cai, et al.
Journal of Medical Imaging (Bellingham, Wash.)|April 24, 2024
Empirical assessment of the assumptions of ComBat with diffusion tensor imagingMichael E Kim, Chenyu Gao, Leon Y Cai, et al.
Journal of Medical Imaging (Bellingham, Wash.)|November 10, 2025
Harmonizing 10,000 connectomes: site-invariant representation learning for multi-site analysis of network connectivity and cognitive impairmentNancy R Newlin, Michael E Kim, Praitayini Kanakaraj, et al.
Proceedings. IEEE International Symposium on Biomedical Imaging|May 25, 2026
HARMONIZATION MITIGATES DIFFUSION MRI SCANNER EFFECTS IN INFANCY: INSIGHTS FROM THE HEALTHY BRAIN AND CHILD DEVELOPMENT (HBCD) STUDYElyssa M McMaster, Gaurav Rudravaram, Michael E Kim, et al.
Proceedings of Spie--The International Society for Optical Engineering|September 23, 2024
Predicting Age from White Matter Diffusivity with Residual LearningChenyu Gao, Michael E Kim, Ho Hin Lee, et al.
Arxiv|November 21, 2023
Predicting Age from White Matter Diffusivity with Residual LearningChenyu Gao, Michael E Kim, Ho Hin Lee, et al.
Arxiv|April 10, 2026
Harmonization mitigates diffusion MRI scanner effects in infancy: insights from the HEALthy Brain and Childhood Development (HBCD) studyElyssa M McMaster, Gaurav Rudravaram, Michael E Kim, et al.
Pageof 6

Showing results (41-50 of 56) with videos related to

Sort By:
Pageof 6
Medrxiv : the Preprint Server for Health Sciences|September 4, 2023
Characterizing patterns of diffusion tensor imaging variance in aging brainsChenyu Gao, Qi Yang, Michael E Kim, et al.
Journal of Medical Imaging (Bellingham, Wash.)|August 26, 2024
Characterizing patterns of diffusion tensor imaging variance in aging brainsChenyu Gao, Qi Yang, Michael E Kim, et al.
Research Square|November 28, 2023
DeepN4: Learning N4ITK Bias Field Correction for T1-weighted ImagesPraitayini Kanakaraj, Tianyuan Yao, Leon Y Cai, et al.
Neuroinformatics|March 25, 2024
DeepN4: Learning N4ITK Bias Field Correction for T1-weighted ImagesPraitayini Kanakaraj, Tianyuan Yao, Leon Y Cai, et al.
Journal of Medical Imaging (Bellingham, Wash.)|April 24, 2024
Empirical assessment of the assumptions of ComBat with diffusion tensor imagingMichael E Kim, Chenyu Gao, Leon Y Cai, et al.
Journal of Medical Imaging (Bellingham, Wash.)|November 10, 2025
Harmonizing 10,000 connectomes: site-invariant representation learning for multi-site analysis of network connectivity and cognitive impairmentNancy R Newlin, Michael E Kim, Praitayini Kanakaraj, et al.
Proceedings. IEEE International Symposium on Biomedical Imaging|May 25, 2026
HARMONIZATION MITIGATES DIFFUSION MRI SCANNER EFFECTS IN INFANCY: INSIGHTS FROM THE HEALTHY BRAIN AND CHILD DEVELOPMENT (HBCD) STUDYElyssa M McMaster, Gaurav Rudravaram, Michael E Kim, et al.
Proceedings of Spie--The International Society for Optical Engineering|September 23, 2024
Predicting Age from White Matter Diffusivity with Residual LearningChenyu Gao, Michael E Kim, Ho Hin Lee, et al.
Arxiv|November 21, 2023
Predicting Age from White Matter Diffusivity with Residual LearningChenyu Gao, Michael E Kim, Ho Hin Lee, et al.
Arxiv|April 10, 2026
Harmonization mitigates diffusion MRI scanner effects in infancy: insights from the HEALthy Brain and Childhood Development (HBCD) studyElyssa M McMaster, Gaurav Rudravaram, Michael E Kim, et al.
Pageof 6