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Showing results (251-260 of 282) with videos related to

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Research Square|November 28, 2023
DeepN4: Learning N4ITK Bias Field Correction for T1-weighted ImagesPraitayini Kanakaraj, Tianyuan Yao, Leon Y Cai, et al.
Current Biology : CB|December 5, 2006
Molecular evidence for species-level distinctions in clouded leopardsValerie A Buckley-Beason, Warren E Johnson, Willliam G Nash, et al.
Neuroinformatics|March 25, 2024
DeepN4: Learning N4ITK Bias Field Correction for T1-weighted ImagesPraitayini Kanakaraj, Tianyuan Yao, Leon Y Cai, et al.
Proceedings of Spie--The International Society for Optical Engineering|February 25, 2020
Harmonizing 1.5T/3T Diffusion Weighted MRI through Development of Deep Learning Stabilized Microarchitecture EstimatorsVishwesh Nath, Samuel Remedios, Prasanna Parvathaneni, 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.
Biorxiv : the Preprint Server for Biology|June 9, 2023
Leveraging longitudinal diffusion MRI data to quantify differences in white matter microstructural decline in normal and abnormal agingDerek B Archer, Kurt Schilling, Niranjana Shashikumar, et al.
Alzheimer'S & Dementia (Amsterdam, Netherlands)|October 2, 2023
Leveraging longitudinal diffusion MRI data to quantify differences in white matter microstructural decline in normal and abnormal agingDerek B Archer, Kurt Schilling, Niranjana Shashikumar, 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.
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.
Pageof 29

Showing results (251-260 of 282) with videos related to

Sort By:
Pageof 29
Research Square|November 28, 2023
DeepN4: Learning N4ITK Bias Field Correction for T1-weighted ImagesPraitayini Kanakaraj, Tianyuan Yao, Leon Y Cai, et al.
Current Biology : CB|December 5, 2006
Molecular evidence for species-level distinctions in clouded leopardsValerie A Buckley-Beason, Warren E Johnson, Willliam G Nash, et al.
Neuroinformatics|March 25, 2024
DeepN4: Learning N4ITK Bias Field Correction for T1-weighted ImagesPraitayini Kanakaraj, Tianyuan Yao, Leon Y Cai, et al.
Proceedings of Spie--The International Society for Optical Engineering|February 25, 2020
Harmonizing 1.5T/3T Diffusion Weighted MRI through Development of Deep Learning Stabilized Microarchitecture EstimatorsVishwesh Nath, Samuel Remedios, Prasanna Parvathaneni, 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.
Biorxiv : the Preprint Server for Biology|June 9, 2023
Leveraging longitudinal diffusion MRI data to quantify differences in white matter microstructural decline in normal and abnormal agingDerek B Archer, Kurt Schilling, Niranjana Shashikumar, et al.
Alzheimer'S & Dementia (Amsterdam, Netherlands)|October 2, 2023
Leveraging longitudinal diffusion MRI data to quantify differences in white matter microstructural decline in normal and abnormal agingDerek B Archer, Kurt Schilling, Niranjana Shashikumar, 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.
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.
Pageof 29