Name
Affiliation
Papers
YOUNGJIN YOO
Multimedia Lab, Samsung Advanced Institute of Technology, Yongin-si, Gyeonggi-do, Republic of Korea
16
Collaborators
Citations 
PageRank 
56
122
9.07
Referers 
Referees 
References 
585
433
147
Search Limit
100585
Title
Citations
PageRank
Year
Quantifying and leveraging predictive uncertainty for medical image assessment10.362021
Brain midline shift detection and quantification by a cascaded deep network pipeline on non-contrast computed tomography scans00.342021
Braided Networks for Scan-Aware MRI Brain Tissue Segmentation00.342020
Deep Learning Of Brain Lesion Patterns And User-Defined Clinical And Mri Features For Predicting Conversion To Multiple Sclerosis From Clinically Isolated Syndrome20.382019
Grey Matter Segmentation In Spinal Cord Mris Via 3d Convolutional Encoder Networks With Shortcut Connections00.342017
Hierarchical Multimodal Fusion of Deep-Learned Lesion and Tissue Integrity Features in Brain MRIs for Distinguishing Neuromyelitis Optica from Multiple Sclerosis.00.342017
Deep 3D Convolutional Encoder Networks With Shortcuts for Multiscale Feature Integration Applied to Multiple Sclerosis Lesion Segmentation.722.012016
Corpus Callosum Segmentation in Brain MRIs via Robust Target-Localization and Joint Supervised Feature Extraction and Prediction.00.342016
Deep Convolutional Encoder Networks for Multiple Sclerosis Lesion Segmentation221.292015
Deep Learning of Image Features from Unlabeled Data for Multiple Sclerosis Lesion Segmentation.70.712014
Modeling the variability in brain morphology and lesion distribution in multiple sclerosis by deep learning.120.652014
Non-local spatial regularization of MRI T2 relaxation images for myelin water quantification.10.402013
Low light imaging system with? Expanding spectrum band for digital camera10.462012
Wide-Band Image Guided Visible-Band Image Enhancement00.342011
Low-light imaging method with visible-band and wide-band image pair20.382009
Profile Based Fast Noise Estimation And High Iso Noise Reduction For Digital Cameras20.392008