JunYoung Choi, Sang-Eun Lee, YeIn Lee, Eunji Cho, Sunghoe Chang, and Won-Ki Jeong. IEEE Transactions on Visualization and Computer Graphics, 2021. [Bibtex]
@article{jun_tvcg_21,
title={DXplorer: A Unified Visualization Framework for Interactive Dendritic Spine Analysis using 3D Morphological Features},
author={Choi, JunYoung and Lee, Sang-Eun and Lee, YeIn and Cho, Eunji and Chang, Sunghoe and Jeong, Won-Ki},
journal={IEEE Transactions on Visualization and Computer Graphics},
year={2021},
publisher={IEEE},
doi={10.1109/TVCG.2021.3116656}
}
Sumin Hong, Ganghee Jang, and Won-Ki Jeong. SIAM Journal on Scientific Computing (SISC), 2021. [Bibtex]
@article{sumin_sisc2021_mgfim,
author={Hong, Sumin and Jang, Ganghee and Jeong, Won-Ki},
title={{MG-FIM: A Multi-GPU FIM using Adaptive Domain Decomposition}},
journal={{SIAM Journal on Scientific Computing (SISC)}},
publisher={Society for Industrial and Applied Mathematics},
volume = {},
year = {2021}
}
JunYoung Choi and Won-Ki Jeong. Journal of the Korea Computer Graphics Society, 27(4):1–9, 2021. [Bibtex]
@article{choi2021neuron,
title={Neuron Tracing-and Deep Learning-guided Interactive Proofreading for Neuron Structure Segmentation},
author={Choi, JunYoung and Jeong, Won-Ki},
journal={Journal of the Korea Computer Graphics Society},
volume={27},
number={4},
pages={1--9},
year={2021},
publisher={Korea Computer Graphics Society}
}
[Paper]
Kanggeun Lee and Won-Ki Jeong. IEEE Transactions on Medical Imaging, pages 1-1, 2021. [Bibtex]
@ARTICLE{lee2021iscl,
author={Lee, Kanggeun and Jeong, Won-Ki},
journal={IEEE Transactions on Medical Imaging},
title={ISCL: Interdependent Self-Cooperative Learning for Unpaired Image Denoising},
year={2021},
volume={},
number={},
pages={1-1},
doi={10.1109/TMI.2021.3096142}}
[Paper]
Yunsook Kang, Yoo Jung Kim, Seongkeun Park, Gun Ro, Choyeon Hong, Hyungjoon Jang, Sungduk Cho, Won Jae Hong, Dong Un Kang, Jonghoon Chun, Kyoungbun Lee, Gyeong Hoon Kang, Kyoung Chul Moon, Gheeyoung Choe, Kyu Sang Lee, Jeong Hwan Park, Won-Ki Jeong, Se Young Chun, Peom Park, and Jinwook Choi. BMC Medical Informatics and Decision Making, 21(1):1–8, 2021. [Bibtex]
@article{kang2021development,
title={Development and operation of a digital platform for sharing pathology image data},
author={Kang, Yunsook and Kim, Yoo Jung and Park, Seongkeun and Ro, Gun and Hong, Choyeon and Jang, Hyungjoon and Cho, Sungduk and Hong, Won Jae and Kang, Dong Un and Chun, Jonghoon and Lee, Kyoungbun and Kang, Gyeong Hoon and Moon, Kyoung Chul and Choe, Gheeyoung and Lee, Kyu Sang and Park, Jeong Hwan and Jeong, Won-Ki and Chun, Se Young and Park, Peom and Choi, Jinwook},
journal={BMC Medical Informatics and Decision Making},
volume={21},
number={1},
pages={1--8},
year={2021},
publisher={BioMed Central}
}
[Paper]
Junyoung Choi, David Grant Colburn Hildebrand, Jungmin Moon, Tran Minh Quan, Tran Anh Tuan, Sungahn Ko, and Won-Ki Jeong. IEEE Access, 9:78755-78763, 2021. [Bibtex]
@article{choi_access21,
author={Choi, Junyoung and Hildebrand, David Grant Colburn and Moon, Jungmin and Quan, Tran Minh and Tuan, Tran Anh and Ko, Sungahn and Jeong, Won-Ki},
journal={IEEE Access},
title={ZeVis: A Visual Analytics System for Exploration of a Larval Zebrafish Brain in Serial-Section Electron Microscopy Images},
year={2021},
volume={9},
number={},
pages={78755-78763},
doi={10.1109/ACCESS.2021.3084066}}
@article{lee2021quantitative,
title={Quantitative three-dimensional image analysis of the superior canal after surgical plugging to treat superior semicircular canal dehiscence},
author={Lee, Sang-Yeon and Lee, Yein and Choi, JunYoung and Bae, Yun Jung and Kim, MinJu and Song, Jae-Jin and Choi, Byung Yoon and Jeong, Won-Ki and Koo, Ja-Won},
journal={Scientific Reports},
volume={11},
number={1},
pages={1--10},
year={2021},
publisher={Nature Publishing Group}
}
[Paper]
Tuan Tran Anh, Khoa Nguyen-Tuan, Tran Minh Quan, and Won-Ki Jeong. In IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021. [Bibtex]
@inproceedings{anh2020reinforced,
title={ColorRL: Reinforced Coloring for End-to-End Instance Segmentation},
author={Tuan Tran Anh and Khoa Nguyen-Tuan and Tran Minh Quan and Won-Ki Jeong},
booktitle={IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
pages={},
year={2021}
}
Jing Wei Tan, Kanggeun Lee, Kyoungbun Lee, and Won-Ki Jeong. In 2021 IEEE 18th International Symposium on Biomedical Imaging (podium presentation, ISBI 2021). IEEE,, 2021. [Bibtex]
@inproceedings{tan2021hiddenlabel,
title={Improving the Accuracy of Intrahepatic Cholangiocarcinoma Subtype Classification by Hidden
Class Detection via Label Smoothing},
author={Tan, Jing Wei and Lee, Kanggeun and Lee, Kyoungbun and Jeong, Won-Ki},
booktitle={2021 IEEE 18th International Symposium on Biomedical Imaging (podium presentation, ISBI 2021)},
pages=N/A,
year={2021},
organization={IEEE}
}
Sungduk Cho, Hyungjoon Jang, Jing Wei Tan, and Won-Ki Jeong. In 2021 IEEE 18th International Symposium on Biomedical Imaging (ISBI 2021). IEEE,, 2021. [Bibtex]
@inproceedings{castleduck_deepscribble_isbi21,
title={DeepScribble: Interactive Pathology Image Segmentation Using Deep Neural Networks with Scribbles},
author={Cho, Sungduk and Jang, Hyungjoon and Tan, Jing Wei and Jeong, Won-Ki},
booktitle={2021 IEEE 18th International Symposium on Biomedical Imaging (ISBI 2021)},
pages=N/A,
year={2021},
organization={IEEE}
}
Chanmin Park, Kanggeun Lee, Suyeon Kim, Fatma Sema Canbakis Cecen, Seok-Kyu Kwon, and Won-Ki Jeong. In 2021 IEEE 18th International Symposium on Biomedical Imaging (ISBI 2021). IEEE,, 2021. [Bibtex]
@inproceedings{chan2021noiseloss,
title={Neuron Segmentation using Incomplete and Noisy Labels via Adaptive Learning with Structure Priors},
author={Park , Chanmin and Lee, Kanggeun and Kim, Suyeon and Fatma Sema Canbakis Cecen and Kwon ,Seok-Kyu and Jeong, Won-Ki},
booktitle={2021 IEEE 18th International Symposium on Biomedical Imaging (ISBI 2021)},
pages=N/A,
year={2021},
organization={IEEE}
}
Gyuhyun Lee, Jeong-Woo Oh, Nam-Gu Her, and Won-Ki Jeong. Medical Image Analysis, page 101995, 2021. [Bibtex]
@article{lee2021deephcs++,
title={DeepHCS++: Bright-Field to Fluorescence Microscopy Image Conversion using Multi-Task Learning with Adversarial Losses for Label-free High-Content Screening},
author={Lee, Gyuhyun and Oh, Jeong-Woo and Her, Nam-Gu and Jeong, Won-Ki},
journal={Medical Image Analysis},
pages={101995},
year={2021},
publisher={Elsevier}
}
T. Thi Kim, N. T. M. Huong, N. D. Q. Huy, P. A. Tai, S. Hong, T. M. Quan, N. T. Bay, W. -K. Jeong, and N. K. Phung. Water, 2020. [Bibtex]
@article{kim2020paip,
title={Assessment of the Impact of Sand Mining on Bottom Morphology in the Mekong River in An Giang Province, Vietnam, Using a Hydro-Morphological Model with GPU Computing},
author={Thi Kim, T. and Huong, N.T.M. and Huy, N.D.Q. and Tai, P.A. and Hong, S. and Quan, T.M. and Bay, N.T. and Jeong, W.-K. and Phung, N.K},
journal={Water},
pages={},
year={2020},
publisher={}
}
[Paper]
Yoo Jung Kim, Hyungjoon Jang, Kyoungbun Lee, Seongkeun Park, Sung-Gyu Min, Choyeon Hong, Jeong Hwan Park, Kanggeun Lee, Jisoo Kim, Wonjae Hong, and others. Medical Image Analysis, page 101854, 2020. [Bibtex]
@article{kim2020paip,
title={PAIP 2019: Liver Cancer Segmentation Challenge},
author={Kim, Yoo Jung and Jang, Hyungjoon and Lee, Kyoungbun and Park, Seongkeun and Min, Sung-Gyu and Hong, Choyeon and Park, Jeong Hwan and Lee, Kanggeun and Kim, Jisoo and Hong, Wonjae and others},
journal={Medical Image Analysis},
pages={101854},
year={2020},
publisher={Elsevier}
}
[Paper]
Hyeonsoo Lee and Won-Ki Jeong. International conference on Medical image computing and computer-assisted intervention (MICCAI), 2020. [Bibtex]
@article{hslee_miccai_2020,
title={Scribble2Label: Scribble-Supervised Cell Segmentation via Self-Generating Pseudo-Labels with Consistency},
author={Lee, Hyeonsoo and Jeong, Won-Ki},
journal={International conference on Medical image computing and computer-assisted intervention ({MICCAI})},
volume={},
number={},
pages={},
year={2020},
publisher={}
}
[Paper]
Sumin Hong, Junyoung Choi, and Won-Ki Jeong. IEEE Transactions on Visualization and Computer Graphics, 2020. [Bibtex]
@article{smhong_tvcg_2020,
title={Distributed Interactive Visualization using GPU-Optimized Spark},
author={Hong, Sumin and Choi, Junyoung and Jeong, Won-Ki},
journal={IEEE Transactions on Visualization and Computer Graphics},
year={2020},
publisher={IEEE}
}
2019
Tran Minh Quan, David Grant Colburn Hildebrand, Kanggeun Lee, Logan A. Thomas, Aaron T. Kuan, Wei-Chung Allen Lee, and Won-Ki Jeong. In Proceedings of the IEEE International Conference on Computer Vision Workshops, page 0–0, 2019. [Bibtex]
@inproceedings{quantm_lci_2019,
title={Removing Imaging Artifacts in Electron Microscopy using an Asymmetrically Cyclic Adversarial Network without Paired Training Data},
author={Minh Quan, Tran and Grant Colburn Hildebrand, David and Lee, Kanggeun and Thomas, Logan A and Kuan, Aaron T and Allen Lee, Wei-Chung and Jeong, Won-Ki},
booktitle={Proceedings of the IEEE International Conference on Computer Vision Workshops},
pages={0--0},
year={2019}
}
@article{kglee_2019,
title={CPEM: Accurate cancer type classification based on somatic alterations using an ensemble of a random forest and a deep neural network},
author={Lee, Kanggeun and Jeong, Hyoung-oh and Lee, Semin and Jeong, Won-Ki},
journal={Scientific Reports},
volume={9},
number={1},
year={2019}
}
@article{jychoi_vis_2019,
title={Interactive Dendritic Spine Analysis Based on 3D Morphological Features},
author={Choi, Junyoung and Lee, Sang-Eun and Cho, Eunji and Kashiwagi, Yutaro and Okabe, Shigeo and Chang, Sunghoe and Jeong, Won-Ki},
journal={IEEE VIS},
number={},
pages={},
year={2019}
}
최준영, 정해진, and 정원기. 컴퓨터그래픽스학회논문지, {25}:31-41, 2019. [Bibtex]
@article{jun_cgkorea_2019,
author={최준영 and 정해진 and 정원기},
title={{가젯암: 확장현실을 위한 손 제스처 기반 대화형 데이터 시각화 시스템}},
booltitle={{컴퓨터그래픽스학회논문지 제25권 제2호}},
journal={{컴퓨터그래픽스학회논문지}},
volume={{25}},
issue={{2}},
publisher={한국컴퓨터그래픽스학회},
year={2019},
ISSN={{1975-7883}},
abstract={{가상 및 증강현실과 같은 확장현실(XR: Extended Reality)은 몰입형 데이터 시각화 및 분석을 위한 거대한 잠재력을 가지고 있다. 확장현실에서 사용자는 3차원 가상 공간을 활용하여 데이터 및 여러 사용자와 사실적으로 상호 작용할 수 있으므로 보다 직관적인 데이터 분석이 가능하다. 그러나 확장현실의 장점을 제대로 활용하기 위한 시각화를 생성하는 것은 복잡한 프로그래밍이 필요하기 때문에 상당히 어려운 일이다. 본 논문에서는 손 제스처만으로 XR을 위한 시각화 전 과정을 수행하고, 모든 3차원 공간을 활용할 수 있는 가젯암(Gadget Arms) 시스템을 제안한다. 이 시스템에서 분석가는 데스크탑 기반 환경이나 복잡한 프로그래밍을 사용할 필요 없이 XR 기기를 착용한 상태에서 직관적으로 전체 시각화 공간을 디자인할 수 있으며, 가상의 손을 임의의 3차원 공간에 자유자재로 위치시킬 수 있는 인터랙션을 통해 거대한 3차원 공간을 효과적으로 활용할 수 있다. 우리는 사용자 연구를 통해 제안된 시스템이 시각화 제작과 공간 활용의 사용성을 크게 향상시시키는 것을 확인하였다.}},
pages={31-41},
url="http://www.dbpia.co.kr/journal/articleDetail?nodeId=NODE08735119"}
Thanh Nguyen-Duc, Tran Minh Quan, and Won-Ki Jeong. Medical Image Analysis, 2019. [Bibtex]
@article{thanh_mia_2019,
title = "Frequency-splitting Dynamic MRI Reconstruction using Multi-scale 3D Convolutional Sparse Coding and Automatic Parameter Selection",
journal = "Medical Image Analysis",
year = "2019",
issn = "1361-8415",
doi = "10.1016/j.media.2019.02.001",
url = "https://www.sciencedirect.com/science/article/pii/S1361841519300155",
author = "Thanh Nguyen-Duc and Tran Minh Quan and Won-Ki Jeong",
keywords = "Compressed Sensing, Dynamic MRI, Parallel MRI, Image Reconstruction, Frequency Filter, Multi-scale 3D Convolutional Sparse Coding, Elastic Net Regularization, Total Variation, Genetic Algorithm, GPU",
abstract = "In this paper, we propose a novel image reconstruction algorithm using multi-scale 3D convolutional sparse coding and a spectral decomposition technique for highly undersampled dynamic Magnetic Resonance Imaging (MRI) data. The proposed method recovers high-frequency information using a shared 3D convolution-based dictionary built progressively during the reconstruction process in an unsupervised manner, while low-frequency information is recovered using a total variation-based energy minimization method that leverages temporal coherence in dynamic MRI. Additionally, the proposed 3D dictionary is built across three different scales to more efficiently adapt to various feature sizes, and elastic net regularization is employed to promote a better approximation to the sparse input data. We also propose an automatic parameter selection technique based on a genetic algorithm to find optimal parameters for our numerical solver which is a variant of the alternating direction method of multipliers (ADMM). We demonstrate the performance of our method by comparing it with state-of-the-art methods on 15 single-coil cardiac, 7 single-coil DCE, and a multi-coil brain MRI datasets at different sampling rates (12.5%, 25% and 50%). The results show that our method significantly outperforms the other state-of-the-art methods in reconstruction quality with a comparable running time and is resilient to noise."
}
Thanh Nguyen-Duc, Inwan Yoo, Logan Thomas, Aaron Kuan, Wei-chung Lee, and Won-Ki Jeong. In Biomedical Imaging (ISBI 2019), 2019 IEEE 16th International Symposium on. IEEE,, 2019. [Bibtex]
@inproceedings{thanh_isbi_2019,
title={Weakly Supervised Learning in Deformable EM Image Registration using Slice Interpolation},
author={Thanh Nguyen-Duc and Inwan Yoo and Logan Thomas and Aaron Kuan and Wei-chung Lee and Won-Ki Jeong},
booktitle={{Biomedical Imaging (ISBI 2019), 2019 IEEE 16th International Symposium on}},
pages={},
year={2019},
organization={IEEE}
}
Ronell Sicat, Jiabao Li, JunYoung Choi, Maxime Cordeil, Won-Ki Jeong, Benjamin Bach, and Hanspeter Pfister. IEEE Transactions on Visualization & Computer Graphics, (1), 2019. [Bibtex]
@article{jychoi_dxr_2019,
title={DXR: A Toolkit for Building Immersive Data Visualizations},
author={Ronell Sicat and Jiabao Li and JunYoung Choi and Maxime Cordeil and Won-Ki Jeong and Benjamin Bach, and Hanspeter Pfister},
journal={IEEE Transactions on Visualization \& Computer Graphics},
number={1},
pages={},
year={2019},
publisher={IEEE}
}
2018
Tran Minh Quan, Thanh Nguyen-Duc, and Won-Ki Jeong. In in Proceedings 26th of Annual Meeting International Society for Magnetic Resonance in Medicine (ISMRM), volume 26, page 3370, Paris, France, 2018. [Bibtex]
@inproceedings{quan_ismrm_2018_3370,
address = {Paris, France},
author = {Tran Minh Quan and Thanh Nguyen-Duc and Won-Ki Jeong},
booktitle = {in Proceedings 26th of {Annual Meeting International Society for Magnetic Resonance in Medicine (ISMRM)}} ,
pages = {3370},
url = {http://archive.ismrm.org/2018/3370.html},
howpublished = "\url{http://archive.ismrm.org/2018/3370.html}",
title = {{Compressed Sensing MRI Reconstruction using Generative Adversarial Networks with Cyclic Loss.}},
volume = {26},
year = {2018}
}
최준영, 정해진, and 정원기. 컴퓨터그래픽스학회논문지, 24(2):29–40, 2018. [Bibtex]
@article{jychoi_graphics_2018,
title={가상현실을 통한 볼륨렌더링 깊이인식 향상},
author={최준영 and 정해진 and 정원기},
journal={컴퓨터그래픽스학회논문지},
volume={24},
number={2},
pages={29--40},
year={2018}
}
Lee Gyuhyun, Oh Jeong-Woo, Kang Mi-Sun, Her Nam-Gu, Kim Myoung-Hee, and Jeong Won-Ki. In International Conference on Medical Image Computing and Computer-Assisted Intervention, page 335–343. Springer,, 2018. [Bibtex]
@inproceedings{ghlee_deephcs_2018,
title={DeepHCS: Bright-Field to Fluorescence Microscopy Image Conversion Using Deep Learning for Label-Free High-Content Screening},
author={Lee Gyuhyun and Oh Jeong-Woo and Kang Mi-Sun and Her Nam-Gu and Kim Myoung-Hee and Jeong Won-Ki},
booktitle={International Conference on Medical Image Computing and Computer-Assisted Intervention},
pages={335--343},
year={2018},
organization={Springer}
}
T. M. Quan, T. Nguyen-Duc, and W. Jeong. IEEE Transactions on Medical Imaging, 37(6):1488-1497, June 2018. [Bibtex]
@ARTICLE{quan_2018_refinegan,
author={T. M. Quan and T. Nguyen-Duc and W. Jeong},
journal={IEEE Transactions on Medical Imaging},
title={Compressed Sensing MRI Reconstruction Using a Generative Adversarial Network With a Cyclic Loss},
year={2018},
volume={37},
number={6},
pages={1488-1497},
doi={10.1109/TMI.2018.2820120},
ISSN={0278-0062},
month={June},
}
Thanh Nguyen-Duc and Won-Ki Jeong. In Biomedical Imaging (ISBI 2018), 2018 IEEE 15th International Symposium on, page 332–335. IEEE,, 2018. [Bibtex]
@inproceedings{thanh_compressed_2018,
title={Compressed sensing dynamic MRI reconstruction using multi-scale 3D convolutional sparse coding with elastic net regularization},
author={Nguyen-Duc, Thanh and Jeong, Won-Ki},
booktitle={{Biomedical Imaging (ISBI 2018), 2018 IEEE 15th International Symposium on}},
pages={332--335},
year={2018},
organization={IEEE}
}
2017
JunYoung Choi, Tran Minh Quan, HaeJin Jeong, and Won-Ki Jeong. In 한국컴퓨터그래픽스학회 2017년 KCGS 학술대회 논문집. Korea Computer Graphics Society, 2017. [Bibtex]
@inproceedings{jychoi_probablisticgraphics_2017,
author={JunYoung Choi and Tran Minh Quan and HaeJin Jeong and Won-Ki Jeong},
title={{Probabilistic Volume Rendering using Hierarchical 3D Convolutional Sparse Coding}},
booktitle={{한국컴퓨터그래픽스학회 2017년 KCGS 학술대회 논문집}},
journal={{한국컴퓨터그래픽스학회 학술대회}},
publisher={Korea Computer Graphics Society},
year={2017}
}
Inwan Yoo, David G. C. Hildebrand, Willie F. Tobin, Wei-Chung Allen Lee, and Won-Ki Jeong. In Deep Learning in Medical Image Analysis and Multimodal Learning for Clinical Decision Support – Third International Workshop, DLMIA 2017, and 7th International Workshop, ML-CDS 2017, Held in Conjunction with MICCAI 2017, Québec City, QC, Canada, September 14, 2017, Proceedings, page 249–257, 2017. [Bibtex]
@inproceedings{iwyoo_2017_ssemnet,
author = {Inwan Yoo and
David G. C. Hildebrand and
Willie F. Tobin and
Wei-Chung Allen Lee and
Won-Ki Jeong},
title = {{ssEMnet}: Serial-Section Electron Microscopy Image Registration Using
a Spatial Transformer Network with Learned Features},
booktitle = {Deep Learning in Medical Image Analysis and Multimodal Learning for
Clinical Decision Support - Third International Workshop, {DLMIA}
2017, and 7th International Workshop, {ML-CDS} 2017, Held in Conjunction
with {MICCAI} 2017, Qu{\'{e}}bec City, QC, Canada, September
14, 2017, Proceedings},
pages = {249--257},
year = {2017},
crossref = {DBLP:conf/miccai/2017dlmia},
url = {https://doi.org/10.1007/978-3-319-67558-9_29},
doi = {10.1007/978-3-319-67558-9_29},
timestamp = {Mon, 11 Sep 2017 12:53:14 +0200},
biburl = {http://dblp.org/rec/bib/conf/miccai/YooHTLJ17},
bibsource = {dblp computer science bibliography, http://dblp.org}
}
이성민, 최민석, 이장호, 이규현, 정원기, and 윤성로. Korean Institute of Information Scientists and Engineers, to appear., 2017. [Bibtex]
@article{ghlee_2017_kcc,
title = {t-{SNE} 기반 군집화 분석을 통한 교모세포종 환자의 항암 후보 약물의 반응성 측정},
year = {2017},
author = {이성민 and 최민석 and 이장호 and 이규현 and 정원기 and 윤성로},
journal = {Korean Institute of Information Scientists and Engineers, to appear.}
}
Tran Minh Quan, JunYoung Choi, Haejin Jeong, and Won-Ki Jeong. IEEE transactions on visualization and computer graphics (TVCG), 24(1):964-973, 2017. [Bibtex]
@article{quan_jun_haejin_vis_2017,
title = {An Intelligent System Approach for Robust Volume Rendering using Hierarchical 3D Convolutional Sparse Coding},
year={2017},
volume={24},
number={1},
pages={964-973},
author = {Tran Minh Quan and JunYoung Choi and Haejin Jeong and Won-Ki Jeong},
journal = {{IEEE} transactions on visualization and computer graphics ({TVCG})},
doi={10.1109/TVCG.2017.2744078},
ISSN={1077-2626},
}
[Video]
Sumin Hong, Woohyuk Choi, and Won-Ki Jeong. 2017 17th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGrid), 2017. [Bibtex]
@article{hong_ccgrid_2017,
title = "{GPU} in-memory processing using Spark for iterative computation",
year = "2017",
author = "Sumin Hong and Woohyuk Choi and Won-Ki Jeong",
journal = {2017 17th {IEEE}/{ACM} International Symposium on Cluster, Cloud and Grid Computing ({CCG}rid)}
}
David Grant Colburn Hildebrand, Marcelo Cicconet, Russel Miguel Torres, Woohyuk Choi, Tran Minh Quan, Jungmin Moon, Arthur Willis Wetzel, Andrew Scott Champion, Brett Jesse Graham, Owen Randlett, George Scott Plummer, Ruben Portugues, Isaac Henry Bianco, Stephan Saalfeld, Alexander David Baden, Kunal Lillaney, Randal Burns, Joshua Tzvi Vogelstein, Alexander Franz Schier, Wei-Chung Allen Lee, Won-Ki Jeong, Jeff William Lichtman, and Florian Engert. Nature, 545(7654):345-349, May 2017. Letter [Bibtex]
@Article{hildebrand_nature_2017,
author={Hildebrand, David Grant Colburn
and Cicconet, Marcelo
and Torres, Russel Miguel
and Choi, Woohyuk
and Quan, Tran Minh
and Moon, Jungmin
and Wetzel, Arthur Willis
and Scott Champion, Andrew
and Graham, Brett Jesse
and Randlett, Owen
and Plummer, George Scott
and Portugues, Ruben
and Bianco, Isaac Henry
and Saalfeld, Stephan
and Baden, Alexander David
and Lillaney, Kunal
and Burns, Randal
and Vogelstein, Joshua Tzvi
and Schier, Alexander Franz
and Lee, Wei-Chung Allen
and Jeong, Won-Ki
and Lichtman, Jeff William
and Engert, Florian},
title={Whole-brain serial-section electron microscopy in larval zebrafish},
journal={Nature},
year={2017},
month={May},
day={18},
publisher={Macmillan Publishers Limited, part of Springer Nature. All rights reserved.},
volume={545},
number={7654},
pages={345-349},
note={Letter},
issn={0028-0836},
url={http://dx.doi.org/10.1038/nature22356},
doi = {10.1038/nature22356}
}
[Link]
S. Hong and W. K. Jeong. IEEE Transactions on Parallel and Distributed Systems, 28(2):318-331, Feb 2017. [Bibtex]
@ARTICLE{hong_group_2016,
author={S. Hong and W. K. Jeong},
journal={{IEEE} Transactions on Parallel and Distributed Systems},
title={A Group-Ordered Fast Iterative Method for Eikonal Equations},
year={2017},
volume={28},
number={2},
pages={318-331},
keywords={iterative methods;multiprocessing systems;parallel algorithms;parallel architectures;pattern clustering;GO-FIM;blocks clustering;eikonal equations;grid blocks;group-ordered fast iterative method;lock-free local queue approach;multicore parallel architectures;numerical algorithms;parallel algorithm;Algorithm design and analysis;Data structures;Graphics processing units;Iterative methods;Parallel algorithms;Parallel architectures;Eikonal equation;{GPU};parallel computing},
doi={10.1109/TPDS.2016.2567397},
ISSN={1045-9219},
month={Feb},}
2016
Woohyuk Choi, Sumin Hong, and Won-Ki Jeong. SIAM Journal on Scientific Computing (SISC), 38(5):S700-S719, 2016. [Bibtex]
@article{woohyuk_2016_vispark,
author={Woohyuk Choi and Sumin Hong and Won-Ki Jeong},
title={{Vispark: {GPU}-Accelerated Distributed Visual Computing Using Spark}},
journal={{SIAM Journal on Scientific Computing (SISC)}},
publisher={Society for Industrial and Applied Mathematics},
volume = {38},
number = {5},
pages = {S700-S719},
year = {2016},
doi = {10.1137/15M1026407},
URL = {
http://dx.doi.org/10.1137/15M1026407
},
eprint = {
http://dx.doi.org/10.1137/15M1026407
}
}
Gyuhyun Lee, Tran Minh Quan, and Won-Ki Jeong. Journal of the Korea Computer Graphics Society, 22:21-29, 2016. [Bibtex]
@article{ghlee_2016_dualdictionary,
author={Gyuhyun Lee and Tran Minh Quan and Won-Ki Jeong},
title={{명시야 현미경 영상에서의 세포 분할을위한 이중 사전 학습 기법}},
booltitle={{Vol.22 No.3}},
journal={{Journal of the Korea Computer Graphics Society}},
volume={22},
issur={3},
publisher={Korea Computer Graphics Society},
year={2016},
pages={21-29},
url={http://www.dbpia.co.kr/Article/NODE06716016
}
}
Tran Minh Quan and Won-Ki Jeong. In Proceedings of the 19th international conference on Medical image computing and computer-assisted intervention (MICCAI), number 9351 in Lecture {Notes} in {Computer} {Science}, page 484–492. Springer International Publishing, 2016. [Bibtex]
Sumin Hong and Won-Ki Jeong. Procedia Computer Science, 80:190-200, 2016. International Conference on Computational Science 2016, \{ICCS\} 2016, 6-8 June 2016, San Diego, California, \{USA\} [Bibtex]
@article{hong_multifim_2016,
title = "A Multi-{GPU} Fast Iterative Method for Eikonal Equations Using On-the-fly Adaptive Domain Decomposition ",
journal = "Procedia Computer Science ",
volume = "80",
number = "",
pages = "190 - 200",
year = "2016",
note = "International Conference on Computational Science 2016, \{ICCS\} 2016, 6-8 June 2016, San Diego, California, \{USA\} ",
issn = "1877-0509",
doi = "http://dx.doi.org/10.1016/j.procs.2016.05.309",
url = "http://www.sciencedirect.com/science/article/pii/S1877050916306676",
author = "Sumin Hong and Won-Ki Jeong",
keywords = "Eikonal equation",
keywords = "fast iterative method",
keywords = "{GPU}",
keywords = "parallel algorithms",
keywords = "domain decomposition ",
abstract = "Abstract The recent research trend of Eikonal solver focuses on employing state-of-the-art parallel computing technology, such as {GPU}s. Even though there exists previous work on {GPU}-based parallel Eikonal solvers, only little research literature exists on the multi-{GPU} Eikonal solver due to its complication in data and work management. In this paper, we propose a novel on-the-fly, adaptive domain decomposition method for efficient implementation of the Block-based Fast Iterative Method on a multi-{GPU} system. The proposed method is based on dynamic domain decomposition so that the region to be processed by each \{{GPU}\} is determined on-the-fly when the solver is running. In addition, we propose an efficient domain assignment algorithm that minimizes communication overhead while maximizing load balancing between {GPU}s. The proposed method scales well, up to 6.17x for eight {GPU}s, and can handle large computing problems that do not fit to limited \{{GPU}\} memory. We assess the parallel efficiency and runtime performance of the proposed method on various distance computation examples using up to eight {GPU}s. "
}
T. M. Quan and W. K. Jeong. IEEE Transactions on Parallel and Distributed Systems, 27(11):3088-3100, Nov 2016. [Bibtex]
@ARTICLE{quan_fast_2016,
author={T. M. Quan and W. K. Jeong},
journal={{IEEE} Transactions on Parallel and Distributed Systems},
title={A Fast Discrete Wavelet Transform Using Hybrid Parallelism on {GPU}s},
year={2016},
volume={27},
number={11},
pages={3088-3100},
keywords={discrete wavelet transforms;graphics processing units;optimisation;parallel processing;CPU;{GPU} DWT methods;{GPU} optimization strategies;{GPU}-based discrete wavelet transform;Haar DWT;ILP maximization;acceleration techniques;computationally-intensive problem acceleration;fast discrete wavelet transform;graphics processing unit;hybrid parallelism;mixed-band memory layout;multilevel transform;single fused kernel launch;time-critical applications;Acceleration;Discrete wavelet transforms;Graphics processing units;Parallel processing;Registers;{GPU} computing;Wavelet transform;bit rotation;hybrid parallelism;lifting scheme},
doi={10.1109/TPDS.2016.2536028},
ISSN={1045-9219},
month={Nov},}
T. M. Quan and W. K. Jeong. In 2016 IEEE 13th International Symposium on Biomedical Imaging (ISBI), pages 518-521, April 2016. [Bibtex]
@INPROCEEDINGS{quan_compressed_2016,
author={T. M. Quan and W. K. Jeong},
booktitle={2016 {IEEE} 13th International Symposium on Biomedical Imaging ({ISBI})},
title={Compressed sensing reconstruction of dynamic contrast enhanced {MRI} using {GPU}-accelerated convolutional sparse coding},
year={2016},
pages={518-521},
keywords={Convolution;Convolutional codes;Dictionaries;Encoding;Fourier transforms;Image reconstruction;Magnetic resonance imaging;Compressed Sensing;Convolutional Sparse Coding;{GPU};{MRI}},
doi={10.1109/ISBI.2016.7493321},
month={April},}
2015
Jinwoong Kim, Won-Ki Jeong, and Beomseok Nam. IEEE Transactions on Parallel and Distributed Systems, 26(8):2258–2271, 2015. [Bibtex]
@article{kim2015exploiting,
title={Exploiting Massive Parallelism for IndexingMulti-Dimensional Datasets on the {GPU}},
author={Kim, Jinwoong and Jeong, Won-Ki and Nam, Beomseok},
journal={{IEEE} Transactions on Parallel and Distributed Systems},
volume={26},
number={8},
pages={2258--2271},
year={2015},
publisher={IEEE}
}
Tran Minh Quan, Sohyun Han, Hyungjoon Cho, and Won-Ki Jeong. In Proceedings of the 18th international conference on Medical image computing and computer-assisted intervention (MICCAI), number 9351 in Lecture {Notes} in {Computer} {Science}, page 484–492. Springer International Publishing, 2015. [Bibtex]
H. Choi, W. Choi, T. M. Quan, D. G. C. Hildebrand, H. Pfister, and W. Jeong. IEEE Transactions on Visualization and Computer Graphics, 20(12):2407–2416, 2014. [Bibtex]
@article{choi_vivaldi_2014,
title = {Vivaldi: A Domain-Specific Language for Volume Processing and Visualization on Distributed Heterogeneous Systems},
volume = {20},
issn = {1077-2626},
shorttitle = {Vivaldi},
doi = {10.1109/TVCG.2014.2346322},
abstract = {As the size of image data from microscopes and telescopes increases, the need for high-throughput processing and visualization of large volumetric data has become more pressing. At the same time, many-core processors and {GPU} accelerators are commonplace, making high-performance distributed heterogeneous computing systems affordable. However, effectively utilizing {GPU} clusters is difficult for novice programmers, and even experienced programmers often fail to fully leverage the computing power of new parallel architectures due to their steep learning curve and programming complexity. In this paper, we propose Vivaldi, a new domain-specific language for volume processing and visualization on distributed heterogeneous computing systems. Vivaldi's Python-like grammar and parallel processing abstractions provide flexible programming tools for non-experts to easily write high-performance parallel computing code. Vivaldi provides commonly used functions and numerical operators for customized visualization and high-throughput image processing applications. We demonstrate the performance and usability of Vivaldi on several examples ranging from volume rendering to image segmentation.},
number = {12},
journal = {{IEEE} Transactions on Visualization and Computer Graphics},
author = {Choi, H. and Choi, W. and Quan, T.M. and Hildebrand, D.G.C. and Pfister, H. and Jeong, W.},
month = dec,
year = {2014},
keywords = {computational modeling, Data models, Data visualization, distributed heterogeneous systems, Domain-specific language, {GPU} computing, graphics processing units, image classification, parallel processing, rendering (computer graphics), volume rendering},
pages = {2407--2416},
file = {{IEEE} Xplore Abstract Record:H\:\\Zotero\\storage\\ED5RN7ME\\articleDetails.html:text/html;{IEEE} Xplore Full Text PDF:H\:\\Zotero\\storage\\XKKZSRWV\\Choi et al. - 2014 - Vivaldi A Domain-Specific Language for Volume Pro.pdf:application/pdf}
}
Tran Minh Quan and Won-Ki Jeong. In IEEE International Conference on Image Processing, pages 1238-1242, 2014. [Bibtex]
@INPROCEEDINGS{quan_fast_2013,
AUTHOR="Tran Minh Quan and Won-Ki Jeong",
TITLE="A Fast {Mixed-Band} Lifting Wavelet Transform on the {GPU}",
BOOKTITLE="{{IEEE} International Conference on Image Processing}",
PAGES="1238-1242",
DAYS=27,
MONTH=oct,
YEAR=2014,
KEYWORDS="Mixed-band, Wavelet, Denoising, {GPU}, Parallel Computing, Compressive
Sensing, MRI",
DOI = {10.1109/ICIP.2014.7025247},
ABSTRACT="Discrete wavelet transform (DWT) has been widely used in many image
compression applications, such as JPEG2000 and compressive sensing MRI.
Even though a lifting scheme has been widely adopted to accelerate DWT,
only a handful of research has been done on its efficient implementation on
many-core accelerators, such as graphics processing units ({GPU}s). Moreover,
we observe that rearranging the spatial locations of wavelet coefficients
at every level of DWT significantly impairs the performance of memory
transaction on the {GPU}. To address these problems, we propose a mixed-band
lifting wavelet transform that reduces uncoalesced global memory access on
the {GPU} and maximizes on-chip memory bandwidth by implementing in-place
operations using registers. We assess the performance of the proposed
method by comparing with the state-of-the-art DWT libraries, and show its
usability in a compressive sensing (CS) MRI application."
}
2013
J. Beyer, M. Hadwiger, A. Al-Awami, Won-Ki Jeong, N. Kasthuri, J. W. Lichtman, and H. Pfister. IEEE Computer Graphics and Applications, 33(4):50–61, 2013. [Bibtex]
@article{beyer_exploring_2013,
title = {Exploring the Connectome: Petascale Volume Visualization of Microscopy Data Streams},
volume = {33},
issn = {0272-1716},
shorttitle = {Exploring the Connectome},
doi = {10.1109/MCG.2013.55},
abstract = {Recent advances in high-resolution microscopy let neuroscientists acquire neural-tissue volume data of extremely large sizes. However, the tremendous resolution and the high complexity of neural structures present big challenges to storage, processing, and visualization at interactive rates. A proposed system provides interactive exploration of petascale (petavoxel) volumes resulting from high-throughput electron microscopy data streams. The system can concurrently handle multiple volumes and can support the simultaneous visualization of high-resolution voxel segmentation data. Its visualization-driven design restricts most computations to a small subset of the data. It employs a multiresolution virtual-memory architecture for better scalability than previous approaches and for handling incomplete data. Researchers have employed it for a 1-teravoxel mouse cortex volume, of which several hundred axons and dendrites as well as synapses have been segmented and labeled.},
number = {4},
journal = {{IEEE} Computer Graphics and Applications},
author = {Beyer, J. and Hadwiger, M. and Al-Awami, A. and Jeong, Won-Ki and Kasthuri, N. and Lichtman, J.W. and Pfister, H.},
month = jul,
year = {2013},
keywords = {1-teravoxel mouse cortex volume, axon, computer graphics, data processing, data storage, data visualisation, Data visualization, dendrite, high-resolution microscopy, high-resolution voxel segmentation, high-throughput electron microscopy, high-throughput imaging, image resolution, incomplete data handling, medical computing, medical image processing, microscopy, microscopy data stream, multiresolution virtual-memory architecture, neural structure, neural-tissue volume data, neurophysiology, neuroscience, neuroscientist, petascale volume visualization, petascale-volume exploration, petavoxel volume, rendering (computer graphics), segmented volume data, Streaming media, visualization-driven design},
pages = {50--61},
file = {{IEEE} Xplore Abstract Record:E:\Zotero\storage\EQHG5J25\articleDetails.html:text/html}
}
W. Jeong, J. Schneider, A. Hansen, M. Lee, S. G. Turney, B. E. Faulkner-Jones, J. L. Hecht, R. Najarian, E. Yee, J. W. Lichtman, and H. Pfister. Computer Graphics Forum, 32(6):227–242, 2013. [Bibtex]
Markus Hadwiger, Johanna Beyer, Won-Ki Jeong, and Hanspeter Pfister. IEEE Transactions on Visualization and Computer Graphics, 18(12):2285–2294, 2012. [Bibtex]
@article{hadwiger_interactive_2012,
title = {Interactive Volume Exploration of Petascale Microscopy Data Streams Using a Visualization-Driven Virtual Memory Approach},
volume = {18},
issn = {1077-2626},
doi = {10.1109/TVCG.2012.240},
number = {12},
journal = {{IEEE} Transactions on Visualization and Computer Graphics},
author = {Hadwiger, Markus and Beyer, Johanna and Jeong, Won-Ki and Pfister, Hanspeter},
year = {2012},
keywords = {{2D} microscope image tiles, {3D} blocks, {3D} multiresolution representation, anisotropic petascale volume, best-of-breed system, cache misses, continuous stream, data acquisition, data visualisation, Data visualization, decouples construction, electron microscopes, Graphics processing unit, high resolution electron microscopy image, high-resolution microscopy, high-throughput imaging, Image resolution, interactive volume exploration, microscopes, microscopy, multiresolution hierarchy, multiresolution virtual memory architecture, neuroscience, octree, Octrees, petascale microscopy data streams, Petascale volume exploration, petascale volumes, ray-casting, real microscopy data, rendering (computer graphics), system design, virtual storage, visible volume data, visualization-driven virtual memory, volume ray casting, volume visualization system},
pages = {2285--2294}
}
2011
Zhisong Fu, Won-Ki Jeong, Yongsheng Pan, Robert M. Kirby, and Ross T. Whitaker. SIAM J. Sci. Comput., 33(5):2468–2488, 2011. [Bibtex]
@article{fu_fast_2011,
title = {A Fast Iterative Method for Solving the Eikonal Equation on Triangulated Surfaces},
volume = {33},
issn = {1064-8275},
url = {http://dx.doi.org/10.1137/100788951},
doi = {10.1137/100788951},
number = {5},
urldate = {2013-04-20},
journal = {{SIAM} J. Sci. Comput.},
author = {Fu, Zhisong and Jeong, Won-Ki and Pan, Yongsheng and Kirby, Robert M. and Whitaker, Ross T.},
month = oct,
year = {2011},
keywords = {Eikonal equation, Graphics processing unit, Hamilton-Jacobi equation, parallel algorithm, shared memory multiple-processor computer system, triangular mesh},
pages = {2468–2488}
}
Yongsheng Pan, Won-Ki Jeong, and Ross Whitaker. Computer Vision and Image Understanding, 115(10):1375–1383, 2011. [Bibtex]
@article{pan_markov_2011,
title = {Markov surfaces: A probabilistic framework for user-assisted three-dimensional image segmentation},
volume = {115},
issn = {1077-3142},
shorttitle = {Markov surfaces},
url = {http://www.sciencedirect.com/science/article/pii/S1077314211001408},
doi = {10.1016/j.cviu.2011.06.003},
number = {10},
urldate = {2013-04-20},
journal = {Computer Vision and Image Understanding},
author = {Pan, Yongsheng and Jeong, Won-Ki and Whitaker, Ross},
month = oct,
year = {2011},
keywords = {{GPU}, Image segmentation, Markov chain, Probabilistic framework},
pages = {1375--1383},
}
Won-Ki Jeong, Micah K. Johnson, Insu Yu, J. Kautz, H. Pfister, and S. Paris. In 2011 IEEE International Conference on Computational Photography (ICCP), page 1–8, 2011. [Bibtex]
@inproceedings{jeong_display-aware_2011,
title = {Display-aware image editing},
doi = {10.1109/ICCPHOT.2011.5753125},
abstract = {We describe a set of image editing and viewing tools that explicitly take into account the resolution of the display on which the image is viewed. Our approach is twofold. First, we design editing tools that process only the visible data, which is useful for images larger than the display. This encompasses cases such as multi-image panoramas and high-resolution medical data. Second, we propose an adaptive way to set viewing parameters such brightness and contrast. Because we deal with very large images, different locations and scales often require different viewing parameters. We let users set these parameters at a few places and interpolate satisfying values everywhere else. We demonstrate the efficiency of our approach on different display and image sizes. Since the computational complexity to render a view depends on the display resolution and not the actual input image resolution, we achieve interactive image editing even on a 16 gigapixel image.},
booktitle = {2011 {IEEE} International Conference on Computational Photography ({ICCP)}},
author = { Jeong, Won-Ki and Johnson, Micah K. and Yu, Insu and Kautz, J. and Pfister, H. and Paris, S.},
month = apr,
year = {2011},
keywords = {Brightness, Cloning, Computational complexity, data visualisation, display resolution, display sizes, display-aware image editing, Histograms, image render, image resolution, image sizes, image viewing tools, Interpolation, Pixel, rendering (computer graphics), Tiles, viewing parameters},
pages = {1--8},
file = {{IEEE} Xplore Abstract Record:E:\Zotero\storage\CZQ7GWEI\abs_all.html:text/html;{IEEE} Xplore Full Text PDF:E:\Zotero\storage\INNKVUSB\Jeong et al. - 2011 - Display-aware image editing.pdf:application/pdf}
}
Mike Roberts, Won-Ki Jeong, Amelio Vázquez-Reina, Markus Unger, Horst Bischof, Jeff Lichtman, and Hanspeter Pfister. In Proceedings of the 14th international conference on Medical image computing and computer-assisted intervention – Volume Part I, {MICCAI’11}, page 621–628, Berlin, Heidelberg, 2011. Springer-Verlag. [Bibtex]
@inproceedings{roberts_neural_2011,
address = {Berlin, Heidelberg},
series = {{MICCAI'11}},
title = {Neural process reconstruction from sparse user scribbles},
isbn = {978-3-642-23622-8},
url = {http://dl.acm.org/citation.cfm?id=2044656.2044742},
urldate = {2013-04-20},
booktitle = {Proceedings of the 14th international conference on Medical image computing and computer-assisted intervention - Volume Part I},
publisher = {Springer-Verlag},
author = {Roberts, Mike and Jeong, Won-Ki and Vázquez-Reina, Amelio and Unger, Markus and Bischof, Horst and Lichtman, Jeff and Pfister, Hanspeter},
year = {2011},
pages = {621–628}
}
Before 2011
Journal Papers
Won-Ki Jeong, Jens Schneider, Stephen Turney, Beverly E. Faulkner-Jones, Dominik Meyer, Rudiger Westermann, Clay R. Reid, Jeff Lichtman, and Hanspeter Pfister. Interactive Histology of Large-Scale Biomedical Image Stacks. IEEE Transactions on Visualization and Computer Graphics, 16(6):1386–1395, 2010. [Bibtex]
@article{jeong_interactive_2010,
title = {Interactive Histology of Large-Scale Biomedical Image Stacks},
volume = {16},
issn = {1077-2626},
url = {http://dx.doi.org/10.1109/TVCG.2010.168},
doi = {10.1109/TVCG.2010.168},
abstract = {Histology is the study of the structure of biological tissue using microscopy techniques. As digital imaging technology advances, high resolution microscopy of large tissue volumes is becoming feasible; however, new interactive tools are needed to explore and analyze the enormous datasets. In this paper we present a visualization framework that specifically targets interactive examination of arbitrarily large image stacks. Our framework is built upon two core techniques: display-aware processing and {{GPU}-accelerated} texture compression. With display-aware processing, only the currently visible image tiles are fetched and aligned on-the-fly, reducing memory bandwidth and minimizing the need for time-consuming global pre-processing. Our novel texture compression scheme for {{GPU}s} is tailored for quick browsing of image stacks. We evaluate the usability of our viewer for two histology applications: digital pathology and visualization of neural structure at nanoscale-resolution in serial electron micrographs.},
number = {6},
urldate = {2013-04-20},
journal = {{IEEE} Transactions on Visualization and Computer Graphics},
author = {Jeong, Won-Ki and Schneider, Jens and Turney, Stephen and Faulkner-Jones, Beverly E and Meyer, Dominik and Westermann, Rudiger and Reid, R. Clay and Lichtman, Jeff and Pfister, Hanspeter},
month = nov,
year = {2010},
keywords = {biomedical image processing, Gigapixel viewer, {GPU}, texture compression},
pages = {1386–1395}
}
Won-Ki Jeong, Johanna Beyer, Markus Hadwiger, Rusty Blue, Charles Law, Amelio Vázquez-Reina, Clay R. Reid, Jeff Lichtman, and Hanspeter Pfister. Ssecrett and NeuroTrace: Interactive Visualization and Analysis Tools for Large-Scale Neuroscience Data Sets. IEEE Comput. Graph. Appl., 30(3):58–70, 2010. [Bibtex]
@article{jeong_ssecrett_2010,
title = {Ssecrett and {NeuroTrace:} Interactive Visualization and Analysis Tools for Large-Scale Neuroscience Data Sets},
volume = {30},
issn = {0272-1716},
shorttitle = {Ssecrett and {NeuroTrace}},
url = {http://dx.doi.org/10.1109/MCG.2010.56},
doi = {10.1109/MCG.2010.56},
number = {3},
urldate = {2013-04-20},
journal = {{IEEE} Comput. Graph. Appl.},
author = {Jeong, Won-Ki and Beyer, Johanna and Hadwiger, Markus and Blue, Rusty and Law, Charles and Vázquez-Reina, Amelio and Reid, R. Clay and Lichtman, Jeff and Pfister, Hanspeter},
month = may,
year = {2010},
keywords = {computer graphics, connectome, graphics and multimedia, graphics hardware, implicit surface rendering, neuroscience, Segmentation, volume rendering},
pages = {58–70}
}
Won-Ki Jeong, Johanna Beyer, Markus Hadwiger, Amelio Vazquez, Hanspeter Pfister, and Ross T. Whitaker. Scalable and Interactive Segmentation and Visualization of Neural Processes in EM Datasets. IEEE Transactions on Visualization and Computer Graphics, 15(6):1505–1514, 2009. [Bibtex]
@article{jeong_scalable_2009,
title = {Scalable and Interactive Segmentation and Visualization of Neural Processes in {EM} Datasets},
volume = {15},
issn = {1077-2626},
url = {http://dx.doi.org/10.1109/TVCG.2009.178},
doi = {10.1109/TVCG.2009.178},
number = {6},
urldate = {2013-04-20},
journal = {{IEEE} Transactions on Visualization and Computer Graphics},
author = {Jeong, Won-Ki and Beyer, Johanna and Hadwiger, Markus and Vazquez, Amelio and Pfister, Hanspeter and Whitaker, Ross T.},
month = nov,
year = {2009},
keywords = {connectome, graphics hardware, implicit surface rendering, neuroscience, Segmentation, volume rendering},
pages = {1505–1514}
}
Joon-Kyung Seong, Won-Ki Jeong, and Elaine Cohen. Curvature-based anisotropic geodesic distance computation for parametric and implicit surfaces. The Visual Computer, 25(8):743–755, 2009. [Bibtex]
@article{seong_curvature-based_2009,
title = {Curvature-based anisotropic geodesic distance computation for parametric and implicit surfaces},
volume = {25},
issn = {0178-2789, 1432-2315},
url = {http://link.springer.com/article/10.1007/s00371-009-0362-0},
doi = {10.1007/s00371-009-0362-0},
language = {en},
number = {8},
urldate = {2013-04-20},
journal = {The Visual Computer},
author = {Seong, Joon-Kyung and Jeong, Won-Ki and Cohen, Elaine},
month = aug,
year = {2009},
keywords = {Anisotropy, Artificial Intelligence (incl. Robotics), computer graphics, Geodesic, {H–J} equation, Image Processing and Computer Vision, Normal curvature, Parametric and implicit surface, Tensor},
pages = {743--755},
file = {Seong et al. - 2009 - Curvature-based anisotropic geodesic distance comp.pdf:E:\Zotero\storage\FSZ6VKMT\Seong et al. - 2009 - Curvature-based anisotropic geodesic distance comp.pdf:application/pdf;Snapshot:E:\Zotero\storage\427GD4WC\10.html:text/html}
}
Won-Ki Jeong and Ross T. Whitaker. A Fast Iterative Method for Eikonal Equations. SIAM J. Sci. Comput., 30(5):2512–2534, 2008. [Bibtex]
@article{jeong_fast_2008,
title = {A Fast Iterative Method for Eikonal Equations},
volume = {30},
issn = {1064-8275},
url = {http://dx.doi.org/10.1137/060670298},
doi = {10.1137/060670298},
number = {5},
urldate = {2013-04-20},
journal = {{SIAM} J. Sci. Comput.},
author = {Jeong, Won-Ki and Whitaker, Ross T.},
month = jul,
year = {2008},
keywords = {Eikonal equation, graphics processing unit ({{GPU})}, Hamilton-Jacobi equation, label-correcting method, parallel algorithm, viscosity solution},
pages = {2512–2534}
}
Won-Ki Jeong, Thomas P. Fletcher, Ran Tao, and Ross Whitaker. Interactive Visualization of Volumetric White Matter Connectivity in DT-MRI Using a Parallel-Hardware Hamilton-Jacobi Solver. IEEE Transactions on Visualization and Computer Graphics, 13(6):1480–1487, 2007. [Bibtex]
@article{jeong_interactive_2007,
title = {Interactive Visualization of Volumetric White Matter Connectivity in {DT-MRI} Using a Parallel-Hardware Hamilton-Jacobi Solver},
volume = {13},
issn = {1077-2626},
url = {http://dx.doi.org/10.1109/TVCG.2007.70571},
doi = {10.1109/TVCG.2007.70571},
number = {6},
urldate = {2013-04-20},
journal = {{IEEE} Transactions on Visualization and Computer Graphics},
author = {Jeong, Won-Ki and Fletcher, P. Thomas and Tao, Ran and Whitaker, Ross},
month = nov,
year = {2007},
keywords = {Diffusion tensor visualization, graphics hardware, interactivity.},
pages = {1480–1487}
}
Won-Ki Jeong and Chang-Hun Kim. Direct Reconstruction of a Displaced Subdivision Surface from Unorganized Points. Graphical Models, 64(2):78–93, 2002. [Bibtex]
@article{jeong_direct_2002,
title = {Direct Reconstruction of a Displaced Subdivision Surface from Unorganized Points},
volume = {64},
issn = {1524-0703},
url = {http://www.sciencedirect.com/science/article/pii/S1524070302905722},
doi = {10.1006/gmod.2002.0572},
number = {2},
urldate = {2013-04-20},
journal = {Graphical Models},
author = {Jeong, Won-Ki and Kim, Chang-Hun},
month = mar,
year = {2002},
pages = {78--93},
file = {Jeong and Kim - 2002 - Direct Reconstruction of a Displaced Subdivision S.pdf:E:\Zotero\storage\JR6NZB5M\Jeong and Kim - 2002 - Direct Reconstruction of a Displaced Subdivision S.pdf:application/pdf;ScienceDirect Snapshot:E:\Zotero\storage\3D8MKH94\S1524070302905722.html:text/html}
}
Peer Reviewed Conference Papers
Yongsheng Pan, Won-Ki Jeong, and Ross T. Whitaker. Markov Surfaces: A Probabilistic Framework for User-Assisted Three-Dimensional Image Segmentation. In Proceedings of Medical image computing and computer-assisted intervention Workshop on Probabilistic Models for Medical Image Analysis, {MICCAI’09}, page 57–68, 2009. [Bibtex]
@inproceedings{pan_probabilistic_2009,
address = {},
series = {{MICCAI'09}},
title = {Markov Surfaces: A Probabilistic Framework for User-Assisted Three-Dimensional Image Segmentation},
isbn = {},
url = {},
urldate = {2013-04-20},
booktitle = {Proceedings of Medical image computing and computer-assisted intervention Workshop on Probabilistic Models for Medical Image Analysis},
publisher = {},
author = {Pan, Yongsheng and Jeong, Won-Ki and Whitaker, Ross T.},
year = {2009},
pages = {57–68}
}
Joon-Kyung Seong, Won-Ki Jeong, and Elaine Cohen. Anisotropic geodesic distance computation for parametric surfaces. In IEEE International Conference on Shape Modeling and Applications, 2008. SMI 2008, page 179–186, 2008. [Bibtex]
@inproceedings{seong_anisotropic_2008,
title = {Anisotropic geodesic distance computation for parametric surfaces},
doi = {10.1109/SMI.2008.4547968},
booktitle = {{IEEE} International Conference on Shape Modeling and Applications, 2008. {SMI} 2008},
author = {Seong, Joon-Kyung and Jeong, Won-Ki and Cohen, Elaine},
year = {2008},
keywords = {{AG} distance map, anisotropic geodesic distance computation, Anisotropic magnetoresistance, Application software, computational geometry, computer graphics, convex Hamilton-Jacobi equation solver, curve fitting, difference curvature tensor, differential geometry, Distributed computing, Equations, Euclidean distance, geometric feature distribution, Geophysics computing, local distance function, minimisation, parametric surface, Shape, surface fitting, Tensile stress, tensor speed function, tensors, total distance minimization, Vehicles, wave propagation control},
pages = {179--186},
}
Thomas P. Fletcher, Ran Tao, Won-Ki Jeong, and Ross T. Whitaker. A volumetric approach to quantifying region-to-region white matter connectivity in diffusion tensor MRI. In Proceedings of the 20th international conference on Information processing in medical imaging, {IPMI’07}, page 346–358, Berlin, Heidelberg, 2007. Springer-Verlag. [Bibtex]
@inproceedings{fletcher_volumetric_2007,
address = {Berlin, Heidelberg},
series = {{IPMI'07}},
title = {A volumetric approach to quantifying region-to-region white matter connectivity in diffusion tensor {MRI}},
isbn = {978-3-540-73272-3},
url = {http://dl.acm.org/citation.cfm?id=1770424.1770457},
urldate = {2013-04-20},
booktitle = {Proceedings of the 20th international conference on Information processing in medical imaging},
publisher = {Springer-Verlag},
author = {Fletcher, P. Thomas and Tao, Ran and Jeong, Won-Ki and Whitaker, Ross T.},
year = {2007},
pages = {346–358}
}
Won-Ki Jeong, Ross Whitaker, and Mark Dobin. Interactive 3D seismic fault detection on the Graphics Hardware. In Proceedings of International Workshop on Volume Graphics, page 111–118, 2006. [Bibtex]
@inproceedings{jeong_interactive_2006,
title = {Interactive {3D} seismic fault detection on the Graphics Hardware},
url = {},
author = {Jeong, Won-Ki and Whitaker, Ross and Dobin, Mark},
booktitle = {Proceedings of International Workshop on Volume Graphics},
year = {2006},
pages = {111--118}
}
Ioannis Ivrissimtzis, Won-Ki Jeong, Ross Whitaker, and Mark Dobin. SURFACE RECONSTRUCTION BASED ON NEURAL MESHES. In Proceedings of Mathematical Methods for Curves and Surfaces, page 223–242, 2005. [Bibtex]
@inproceedings{ivrissimtzis_surface_2005,
title = {SURFACE RECONSTRUCTION BASED ON NEURAL MESHES},
url = {},
author = {Ivrissimtzis, Ioannis and Jeong, Won-Ki and Whitaker, Ross and Dobin, Mark},
booktitle = {Proceedings of Mathematical Methods for Curves and Surfaces},
year = {2005},
pages = {223--242}
}
Ioannis Ivrissimtzis, Yunjin Lee, Seungyong Lee, Won-Ki Jeong, and Hans-Peter Seidel. Neural Mesh Ensembles. In Proceedings of the 3D Data Processing, Visualization, and Transmission, 2nd International Symposium, {3DPVT} ’04, page 308–315, Washington, {DC}, {USA}, 2004. IEEE Computer Society. [Bibtex]
@inproceedings{ivrissimtzis_neural_2004,
address = {Washington, {DC}, {USA}},
series = {{3DPVT} '04},
title = {Neural Mesh Ensembles},
isbn = {0-7695-2223-8},
url = {http://dx.doi.org/10.1109/3DPVT.2004.87},
doi = {10.1109/3DPVT.2004.87},
urldate = {2013-04-20},
booktitle = {Proceedings of the {3D} Data Processing, Visualization, and Transmission, 2nd International Symposium},
publisher = {{IEEE} Computer Society},
author = {Ivrissimtzis, Ioannis and Lee, Yunjin and Lee, Seungyong and Jeong, Won-Ki and Seidel, Hans-Peter},
year = {2004},
pages = {308--315}
}
Won-Ki Jeong, Ioannis Ivrissimtzis, and Hans-Peter Seidel. Neural Meshes: Statistical Learning Based on Normals. In Proceedings of the 11th Pacific Conference on Computer Graphics and Applications, {PG} ’03, page 404, Washington, {DC}, {USA}, 2003. IEEE Computer Society. [Bibtex]
@inproceedings{jeong_neural_2003,
address = {Washington, {DC}, {USA}},
series = {{PG} '03},
title = {Neural Meshes: Statistical Learning Based on Normals},
isbn = {0-7695-2028-6},
shorttitle = {Neural Meshes},
url = {http://dl.acm.org/citation.cfm?id=946250.946985},
urldate = {2013-04-20},
booktitle = {Proceedings of the 11th Pacific Conference on Computer Graphics and Applications},
publisher = {{IEEE} Computer Society},
author = {Jeong, Won-Ki and Ivrissimtzis, Ioannis and Seidel, Hans-Peter},
year = {2003},
pages = {404}
}
Ioannis Ivrissimtzis, Won-Ki Jeong, and Hans-Peter Seidel. Using growing cell structures for surface reconstruction. In Shape Modeling International, 2003, page 78–86, 2003. [Bibtex]
@inproceedings{ivrissimtzis_using_2003,
title = {Using growing cell structures for surface reconstruction},
doi = {10.1109/SMI.2003.1199604},
booktitle = {Shape Modeling International, 2003},
author = {Ivrissimtzis, Ioannis and Jeong, Won-Ki and Seidel, Hans-Peter},
year = {2003},
keywords = {Application software, Biological neural networks, Clouds, Computer networks, concavity, evolutionary computation, growing cell structure, Humans, image reconstruction, mesh generation, network connectivity, neural nets, neural network algorithm, random sampling, Shape, shape modeling, sharp feature, signal processing, Signal processing algorithms, solid modelling, surface fitting, surface meshing, surface reconstruction, surface sampling, target space, unorganized point cloud},
pages = {78--86},
file = {{IEEE} Xplore Abstract Record:E:\Zotero\storage\KHMVTMGD\articleDetails.html:text/html;{IEEE} Xplore Full Text PDF:E:\Zotero\storage\CKUTIX23\Ivrissimtzis et al. - 2003 - Using growing cell structures for surface reconstr.pdf:application/pdf}
}
Won-Ki Jeong, Kolja Kahler, and Hans-Peter Seidel. Subdivision surface simplification. In 10th Pacific Conference on Computer Graphics and Applications, 2002. Proceedings, page 477–480, 2002. [Bibtex]
@inproceedings{jeong_subdivision_2002,
title = {Subdivision surface simplification},
doi = {10.1109/PCCGA.2002.1167907},
abstract = {A modified quadric error metric ({QEM)} for simplification of Loop subdivision surfaces is presented The suggested error metric not only measures the geometric difference but also controls the smoothness and well-shapedness of the triangles that result from the decimation process. Minimizing the error with respect to the original limit surface, our method allows for drastic simplification of Loop control meshes with convenient control over the reproduction of sharp features.},
booktitle = {10th Pacific Conference on Computer Graphics and Applications, 2002. Proceedings},
author = {Jeong, Won-Ki and Kahler, Kolja and Seidel, Hans-Peter},
year = {2002},
keywords = {Application software, Bridges, computer graphics, Control systems, decimation, Displays, Error correction, error metric, errors, Loop scheme, loop subdivision surfaces, mesh generation, mesh simplification, quadric error metric, smoothness, surface fitting, surface reconstruction, Tensile stress},
pages = {477--480},
file = {{IEEE} Xplore Abstract Record:E:\Zotero\storage\EQUKRR3U\abs_all.html:text/html;{IEEE} Xplore Full Text PDF:E:\Zotero\storage\GPHFTKG2\Jeong et al. - 2002 - Subdivision surface simplification.pdf:application/pdf}
}
Won-Ki Jeong, Kolja Kahler, Jörg Haber, and Hans-peter Seidel. Automatic Generation of Subdivision Surface Head Models from Point Cloud Data. In In Graphics Interface 2002 Conf. Proc, page 181–188, 2002. [Bibtex]
@inproceedings{jeong_automatic_2002,
title = {Automatic Generation of Subdivision Surface Head Models from Point Cloud Data},
booktitle = {In Graphics Interface 2002 Conf. Proc},
author = {Jeong, Won-Ki and Kahler, Kolja and Haber, Jörg and Seidel, Hans-peter},
year = {2002},
pages = {181–188},
}
Won-Ki Jeong and Chang-Hun Kim. Direct reconstruction of displaced subdivision surface from unorganized points. In Ninth Pacific Conference on Computer Graphics and Applications, 2001. Proceedings, page 160–168, 2001. [Bibtex]
@inproceedings{jeong_direct_2001,
title = {Direct reconstruction of displaced subdivision surface from unorganized points},
doi = {10.1109/PCCGA.2001.962869},
booktitle = {Ninth Pacific Conference on Computer Graphics and Applications, 2001. Proceedings},
author = {Jeong, Won-Ki and Kim, Chang-Hun},
year = {2001},
keywords = {Clouds, compact mesh size, computational geometry, computer graphics, Computer science, direct reconstruction, displaced subdivision surface, displacement map, explicit polygonal mesh, initial coarse control mesh, Laser modes, mesh generation, mesh reconstruction algorithm, multiresolution modeling, parametric domain surface, piecewise regular connectivity, Probes, Reconstruction algorithms, Sampling methods, smooth domain surface, surface detail sampling scheme, surface fitting, surface reconstruction, unorganized points, valid sampling triangle},
pages = {160--168},
}
Book Chapters
Won-Ki Jeong, Hanspeter Pfister, and Massimiliano Fatica. Chapter 46: Medical Image Processing using GPU-Accelerated ITK image filters. . [Bibtex]
@inbook{jeong_chap46_2011,
author = {Jeong, Won-Ki and Pfister, Hanspeter and Fatica, Massimiliano},
title = {Chapter 46: Medical Image Processing using {GPU}-Accelerated ITK image filters},
}
@book{{GPU}gem_2011,
editor = {Wen-mei W. Hwu},
title = {NVIDIA {GPU} Computing Gems Emerald Edition},
publisher = {Morgan-Kaufmann},
year = {2011}
}
Won-Ki Jeong, Hanspeter Pfister, Johanna Beyer, and Markus Hadwiger. Chapter49: GPU-accelerated Brain Connectivity Reconstruction and Visualization in Large-Scale Electron Micrographs. . [Bibtex]
@inbook{jeong_chap46_2011,
author = {Jeong, Won-Ki and Pfister, Hanspeter and Beyer, Johanna and Hadwiger, Markus},
title = {Chapter49: {GPU}-accelerated Brain Connectivity Reconstruction and Visualization in Large-Scale Electron Micrographs},
}
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[Bibtex] 
