Prospects of deep learning for medical imaging J Kim, J Hong, H Park Precision and Future Medicine 2 (2), 37-52, 2018 | 82 | 2018 |
Convolutional neural network classifier for distinguishing Barrett's esophagus and neoplasia endomicroscopy images J Hong, BY Park, H Park 2017 39th Annual international conference of the IEEE engineering in …, 2017 | 76 | 2017 |
Two-step deep neural network for segmentation of deep white matter hyperintensities in migraineurs J Hong, B Park, MJ Lee, CS Chung, J Cha, H Park Computer methods and programs in biomedicine 183, 105065, 2020 | 36 | 2020 |
Neuroimaging biomarkers to associate obesity and negative emotions B Park, J Hong, H Park Scientific reports 7 (1), 7664, 2017 | 24 | 2017 |
Functional connectivity of child and adolescent attention deficit hyperactivity disorder patients: correlation with IQ B Park, J Hong, SH Lee, H Park Frontiers in Human Neuroscience 10, 565, 2016 | 23 | 2016 |
Artificial neural network inspired by neuroimaging connectivity: application in autism spectrum disorder K Byeon, J Kwon, J Hong, H Park 2020 IEEE International Conference on Big Data and Smart Computing (BigComp …, 2020 | 17 | 2020 |
Age-related connectivity differences between attention deficit and hyperactivity disorder patients and typically developing subjects: a resting-state functional MRI study J Hong, B Park, H Cho, H Park Neural regeneration research 12 (10), 1640-1647, 2017 | 17 | 2017 |
Non-linear approach for mri to intra-operative us registration using structural skeleton J Hong, H Park Simulation, Image Processing, and Ultrasound Systems for Assisted Diagnosis …, 2018 | 9 | 2018 |
注意缺陷多动障碍与正常发育患者年龄相关的脑网络连接差异: 静息态功能 MRI 研究 J Hong, B Park, H Cho, H Park 中国神经再生研究 (英文版) 12 (10), 1640, 2017 | | 2017 |