Suk Jin Lee

Suk Jin Lee (S’11-M’13) received the B.Eng. degree in electronic engineering and M.Eng. degree in telematics engineering from Pukyong National University, Busan, Korea, in 2003 and 2005, respectively, and the Ph.D. degree in electrical and computer engineering from Virginia Commonwealth University, Richmond, VA, USA, in 2012. He is currently an Assistant Professor of Computer Science at Texas A&M University – Texarkana, Texarkana, TX, USA. In 2007, he was a Visiting Research Scientist with GW Center for Networks Research, George Washington University, Washington, DC, USA. His research interests include network protocols, neural network, target estimate, and classification.

Associated articles

JTEHM, Articles, Published Articles
Elastographic Tomosynthesis from X-ray Strain Imaging of Breast Cancer
Noncancerous breast tissue and cancerous breast tissue have different elastic properties. In particular, cancerous breast tumors are stiff when compared to the noncancerous surrounding tissue. This difference in elasticity can be used as a means for detection through the method... Read more
JTEHM, Articles, Published Articles
Intra- and Inter-Fractional Variation Prediction of Lung Tumors using Fuzzy Deep Learning
Tumor movements should be accurately predicted to improve delivery accuracy and reduce unnecessary radiation exposure to healthy tissue during radiotherapy. The tumor movements pertaining to respiration are divided into intra-fractional variation occurring in a single treatment session and inter-fractional variation... Read more
JTEHM, Articles
Autoencoder-Inspired Convolutional Network-Based Super-Resolution Method in MRI
Objective: To introduce an MRI in-plane resolution enhancement method that estimates High-Resolution (HR) MRIs from Low-Resolution (LR) MRIs. Method & Materials: Previous CNN-based MRI super-resolution methods cause loss of input image information due to the pooling layer. An Autoencoder-inspired Convolutional... Read more