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Youngjin Yoo

Showing results (1-10 of 21) with videos related to

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Medical Image Computing and Computer-Assisted Intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention|February 8, 2014
Non-local spatial regularization of MRI T2 relaxation images for myelin water quantificationYoungjin Yoo, Roger Tam
Studies in Health Technology and Informatics|January 13, 2006
Evaluation methods of a middleware for networked surgical simulationsQingbo Cai, Vincenzo Liberatore, M Cenk Cavuşoğlu, et al.
Medical Image Computing and Computer-Assisted Intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention|December 9, 2014
Modeling the variability in brain morphology and lesion distribution in multiple sclerosis by deep learningTom Brosch, Youngjin Yoo, David K B Li, et al.
Journal of Medical Imaging (Bellingham, Wash.)|May 27, 2021
Evaluating deep learning methods in detecting and segmenting different sizes of brain metastases on 3D post-contrast T1-weighted imagesYoungjin Yoo, Pascal Ceccaldi, Siqi Liu, et al.
IEEE Transactions on Medical Imaging|February 18, 2016
Deep 3D Convolutional Encoder Networks With Shortcuts for Multiscale Feature Integration Applied to Multiple Sclerosis Lesion SegmentationTom Brosch, Lisa Y W Tang, Youngjin Yoo, et al.
Journal of Magnetic Resonance Imaging : JMRI|March 1, 2014
Fast computation of myelin maps from MRI T₂ relaxation data using multicore CPU and graphics card parallelizationYoungjin Yoo, Thomas Prasloski, Irene Vavasour, et al.
Magnetic Resonance in Medicine|September 24, 2017
Rapid myelin water imaging in human cervical spinal cordEmil Ljungberg, Irene Vavasour, Roger Tam, et al.
Journal of Medical Imaging (Bellingham, Wash.)|December 5, 2022
Contrastive self-supervised learning from 100 million medical images with optional supervisionFlorin C Ghesu, Bogdan Georgescu, Awais Mansoor, et al.
Neuroimage. Clinical|October 27, 2017
Deep learning of joint myelin and T1w MRI features in normal-appearing brain tissue to distinguish between multiple sclerosis patients and healthy controlsYoungjin Yoo, Lisa Y W Tang, Tom Brosch, et al.
Journal of Alzheimer'S Disease : JAD|February 1, 2021
Exploring the Contribution of Myelin Content in Normal Appearing White Matter to Cognitive Outcomes in Cerebral Small Vessel DiseaseElizabeth Dao, Roger Tam, Ging-Yuek R Hsiung, et al.
Pageof 3

Showing results (1-10 of 21) with videos related to

Sort By:
Pageof 3
Medical Image Computing and Computer-Assisted Intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention|February 8, 2014
Non-local spatial regularization of MRI T2 relaxation images for myelin water quantificationYoungjin Yoo, Roger Tam
Studies in Health Technology and Informatics|January 13, 2006
Evaluation methods of a middleware for networked surgical simulationsQingbo Cai, Vincenzo Liberatore, M Cenk Cavuşoğlu, et al.
Medical Image Computing and Computer-Assisted Intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention|December 9, 2014
Modeling the variability in brain morphology and lesion distribution in multiple sclerosis by deep learningTom Brosch, Youngjin Yoo, David K B Li, et al.
Journal of Medical Imaging (Bellingham, Wash.)|May 27, 2021
Evaluating deep learning methods in detecting and segmenting different sizes of brain metastases on 3D post-contrast T1-weighted imagesYoungjin Yoo, Pascal Ceccaldi, Siqi Liu, et al.
IEEE Transactions on Medical Imaging|February 18, 2016
Deep 3D Convolutional Encoder Networks With Shortcuts for Multiscale Feature Integration Applied to Multiple Sclerosis Lesion SegmentationTom Brosch, Lisa Y W Tang, Youngjin Yoo, et al.
Journal of Magnetic Resonance Imaging : JMRI|March 1, 2014
Fast computation of myelin maps from MRI T₂ relaxation data using multicore CPU and graphics card parallelizationYoungjin Yoo, Thomas Prasloski, Irene Vavasour, et al.
Magnetic Resonance in Medicine|September 24, 2017
Rapid myelin water imaging in human cervical spinal cordEmil Ljungberg, Irene Vavasour, Roger Tam, et al.
Journal of Medical Imaging (Bellingham, Wash.)|December 5, 2022
Contrastive self-supervised learning from 100 million medical images with optional supervisionFlorin C Ghesu, Bogdan Georgescu, Awais Mansoor, et al.
Neuroimage. Clinical|October 27, 2017
Deep learning of joint myelin and T1w MRI features in normal-appearing brain tissue to distinguish between multiple sclerosis patients and healthy controlsYoungjin Yoo, Lisa Y W Tang, Tom Brosch, et al.
Journal of Alzheimer'S Disease : JAD|February 1, 2021
Exploring the Contribution of Myelin Content in Normal Appearing White Matter to Cognitive Outcomes in Cerebral Small Vessel DiseaseElizabeth Dao, Roger Tam, Ging-Yuek R Hsiung, et al.
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