Deep Learning in Medical Imaging

D. Shen*, G. Wu, and H.-I. Suk*, “Deep Learning in Medical Image Analysis,” Annual Review of Biomedical Engineering, Vol. 19, pp. 221-248, 2017. (*Co-first and Co-corresponding Authors, 2016-JCR-IF: 10.514, ENGINEERING, BIOMEDICAL: 1/77)

 


Functional Dynamics Modelling in Resting-State fMRI

H.-I. SUK, C.-Y. Wee, S.-W. Lee, and D. Shen, “State-Space Model with Deep Learning for Functional Dynamics Estimation in Resting-State fMRI,” NeuroImage, Vol. 129, pp. 292-307, April 2016 (2014-JCR-IF: 6.357, NEUROIMAGING: 1/14, RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING: 3/125)

 


Multi-Modal Feature Representation for Brain Disorder Diagnosis

H.-I. SUK, S.-W. Lee, and D. Shen, “Hierarchical Feature Representation and Multi-Modal Fusion with Deep Learning for AD/MCI Diagnosis,” NeuroImage, Vol. 101, pp. 569-582, Nov. 2014. (2012-JCR-IF: 6.252, RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING: 3/120, NEUROSCIENCE, 26/252, NEUROIMAGING: 2/14)

 


Bayesian Framework for Spatio-Spectral Filter Optimization in BCI

H.-I. SUK and S.-W. Lee, “A Novel Bayesian Framework for Discriminative Feature Extraction in Brain-Computer Interfaces,” IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 35, No. 2, pp. 286-299, Feb. 2013. (2011-JCR-IF: 4.908, COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE: 1/111, ENGINEERING, ELECTRICAL & ELECTRONIC: 6/245)