Papers
[Machine Learning / Data Analytics]
[C14] J. Ku, J. Oh, Y. Lee, G. Pooniwala, S. Lee, "A Selective Survey on Versatile Knowledge Distillation Paradigm for Neural Network Models," arXiv 2020.
[C13] J. Oh. S. Lee, M. Park, P. Walagaurav, K. Kwon, "Weight Equalizing Shift Scaler-Coupled Post-training Quantization," arXiv 2020.
[C12] J. Oh, K. Cho, J. Bruna, "Advanced GraphSAGE with A Data-driven Node Sampling," ICLR (2019) workshop on Representation Learning on Graphs and Manifolds.
[Medical Imaging]
[J11] J. Oh, G. Kim, J. Lee, M. Cheon, Y. Park, S. Kim, J. Yi, H.Y. Lee, "Automated Detection of Bone Metastatic Changes using Serial CT Scans," Computerized Medical Imaging and Graphics, Vol. 58, p 62-74 (2017).
[C10] W. Nam, J. Oh, et al., "Improved B-spline image registration between exhale and inhale lung CT images based on intensity and gradient orientation information," Proc. SPIE, Vol. 9784, 978400-1, Medical Imaging 2016.
[C9] J. Oh, J. Lee, G. Kim, M. Cheon, Y. Park, "Chest Bone Registration using Weighted-Demons in Serial CT Scans," Computer Assisted Radiology and Surgery (CARS) 2015 Proceedings, Barcelona, June 24-27, 2015.
[C8] G. Kim, J. Oh, J. Lee, M. Cheon, "Automatic Bone Metastases Quantification Method using Follow-up CT," Computer Assisted Radiology and Surgery (CARS) 2015 Proceedings, Barcelona, June 24-27, 2015.
[J7] J. Oh, D. Martin, and X. Hu, "Partitioned Edge Function-Scaled Region-based Active Contour (p-ESRAC): Automated Liver Segmentation in Contrast-Enhanced MRI," Medical Physics, Vol. 41, No. 4, 041914 (2014).
[C6] J. Oh, X. Kang, E. Wilson, C. Peters, T. Kane, R. Shekhar, "Stereoscopic Augmented Reality using Ultrasound Volume Rendering for Laparoscopic Surgery in Children," Proc. SPIE, Vol. 9036, 90360Y (2014), Medical Imaging 2014, Oral presented.
[C5] X. Kang, J. Oh, E. Wilson, Z. Yaniv, T.D. Kane, C. Peters, R. Shekhar, "Towards A Clinical Stereoscopic Augmented Reality System for Laparoscopic Surgery," MICCAI CLIP 2013, Sept. 22nd. Best paper.
[C4] J. Oh, D. Martin, and X. Hu, "Signal Intensity and Texture Analysis in Contrast-Enhanced Liver MRI for Chronic Liver Disease Diagnosis," ISMRM 2013, Salt Lake, April 20-26.
[C3] J. Oh, D. Martin, and O. Skrinjar, "Liver 2D Histology to 3D MR Image Registration using Segmentation and Point Landmarks," Proc. SPIE Medical Imaging 2012.
[C2] J. Oh, D. Martin, and O. Skrinjar, "GPU-based Motion Correction of Contrast-Enhanced Liver MRI Scans: An OpenCL Implementation," Biomedical Imaging: From Nano to Macro, 2011 IEEE International Symposium, p 783 - 786.
[C1] J. Oh, D. Martin, and O. Skrinjar, "LCC demons with divergence term for liver MRI motion correction," Proc. SPIE, Vol. 7623, 76232T (2010), Medical Imaging 2010.
PhD Thesis
"Contrast-Enhanced Magnetic Resonance Liver Image Registration, Segmentation, and Feature Analysis for Liver Disease Diagnosis," Georgia Institute of Technology, 2012
Patents
[P1] 10,360,678, Image processing apparatus, image processing method and recording medium thereof
[P2] 10,413,253, Method and apparatus for processing medical image
P2202398, 영상처리 및 그의 영상처리방법
[P3] 10,719,935, Image processing apparatus and image processing method thereof
[P4] 11,051,715, Image processing apparatus, image processing method, and recording medium recording same
[P5] US20180235563A1, Medical image display device and medical image processing method
[P6] US20180338159A1 Super-resolution Processing Method for Moving Image and Image Processing Apparatus Therefor
[P7] P20160017484, Predictive Modeling and Measuring of Kinetic Function by Registration of Respiratory CT
[P8] US63/026960, PCT/KR2021/002302, A Hardware-friendly Channel-wise Shift Scaling for Weight Quantization
[P9] P20210083107, Recursive Reconfiguration Method of Neural Network Model for Mixed Precision
Source Codes
https://github.com/oj9040