Image Processing and Analysis Lab.

We believe that knowledge from big data is a golden key to improve our society in cost-effective way. We focus on image and signal processing and analysis researches in various domains, such as medicine, security, and natural science.

We welcome your kind feedback and suggestions on our research. Our door is always open to highly motivated students at all stages.

Contact: Jaeil Kim, Ph.D. threeyears@gmail.com , E9-527 Kyungpook National University (Daegu, South Korea)

Research Projects

  • Computer-aided Cerebral Hemorrhage Diagnosis in Brain CT
    • 2018 ~ Current, with Kyungpook National University Hospital
  • Development of Deep Learning Framework for Massive Video Processing
    • 2019 ~ Current, with Korea Institute of Ocean Science and Technology
  • 3D Shape Modeling of Foot Joint using Plain Radiographs
    • 2016 ~ Current, with Asan Medical Center
  • Automatic Femur Segmentation and Bone Shape Modeling
    • 2018 ~ Current, with Asan Medical Center
  • Development of Encrypted Malware Traffic Detection Algorithms (2018)
  • Development of Longitudinal Prediction Model for Early Development (2017~2018)
  • Longitudinal Diffusion Atlas Construction for Infant Brain (2016~2017)
20190503_OpenLab_IPA

Recent Publications

2019

Jungrae Cho, Inchul Choi, Jaeil Kim, Sungmoon Jeong, Young-Sup Lee, Jaechan Park, Minho Lee. "Affinity Graph based End-to-End Deep Convolutional Networks for CT Hemorrhage Segmentation", ICONIP 2019 (Accepted)

Doyoung Kwon, Jaesin Ahn, Jaeil Kim, Inchul Choi, Sungmoon Jeong, Young-Sup Lee, Jaechan Park, Minho Lee. Siamese U-Net with Healthy Template for Accurate Segmentation of Intracranial Hemorrhage, MICCAI 2019 (Accepted)

Taekyung Kim, Jaeil Kim, Jinah Kim. Hydrodynamic scene separation from video imagery of ocean wave using autoencoder. J Korea Comput Graph Soc 2019;25(4):9-16.

Kim D, Kim J, "Elastic Multiple Parametric Exponential Linear Units for Convolutional Neural Networks", Journal of KIISE, Vol. 46, No. 5, 469-477, 2019.

Chen G, Hong Y, Kim J, Zhang Y, Ma J, Shen D, Yap PT, “Prediction of Multi-Shell from Single-Shell Diffusion MRI Data via Graph Convolutional Neural Networks”, OHBM, Rome, Italy, June 9-13, 2019.

Kim J, Hong Y, Chen G, Lin W, Yap PT, Shen D. "Graph-Based Deep Learning for Prediction of Longitudinal Infant Diffusion MRI Data". Computational Diffusion MRI. 2019:133.

Hong Y, Kim J, Chen G, Lin W, Yap PT, Shen D, "Longitudinal Prediction of Infant Diffusion MRI Data via Graph Convolutional Adversarial Networks", IEEE Transactions on Medical Imaging, 17 April, 2019

Shao Y, Kim J, Gao Y, Wang Q, Lin W, Shen D. Hippocampal Segmentation from Longitudinal Infant Brain MR Images via Classification-guided Boundary Regression. IEEE Access. 2019 Mar 11.

Huh D, Kim T, Kim J, "Patch-wise Weakly Supervised Learning for Object Localization in Video", The 1st International Conference on AI in Information and Communication (ICAIIC 2019) , Japan, Feb.11-13, 2019

2018

Yoon S, Seo S, Kim J, "Automatic Foot Bone Segmentation in Plain Radiographs for Diagnosis of Foot Disorders", Korea Software Congress 2018 (KSC2018), Dec.19-21, 2018 (Domestic Conference)

Kim J, Hong Y, Chen G, Lin W, Yap PT, Shen D, "Graph-Based Deep Learning for Prediction of Longitudinal Infant Diffusion MRI Data", MICCAI 2018 Workshop on Computational Diffusion MRI, Spain, Sept.20, 2018

Kim J, Hong Y, Chen G, Lin W, Yap PT, Shen D, "Longitudinal Prediction of Pediatric Diffusion MRI Data using Graph-Based Deep Learning", 104th RSNA Scientific Assembly and Annual Meeting, Chicago, USA, Nov. 25-30, 2018.

Li G, Wang L, Yap PT, Wang F, Wu Z, Meng Y, Dong P, Kim J, Shi F, Rekik I, Lin W. Shen D, "Computational Neuroanatomy of Baby Brains: A review". NeuroImage. Mar. 21, 2018

Kim J, Chen G, Lin W, Yap PT, Shen D, "Prediction of Diffusion-Weighted Appearance in Developing Infant Brain using Cycle-Consist Models", OHBM, Singapore, 17-21 June, 2018