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Soochahn Lee
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- affiliation: Soonchunhyang University, Korea
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2020 – today
- 2024
- [i7]Gun Lee, Subin An, Sungyong Baik, Soochahn Lee:
CoAPT: Context Attribute words for Prompt Tuning. CoRR abs/2407.13808 (2024) - 2023
- [j18]Euyoung Kim
, Soochahn Lee
, Kyoung Mu Lee
:
Abnormality Detection in Chest X-Ray via Residual-Saliency From Normal Generation. IEEE Access 11: 21799-21810 (2023) - [j17]Gun Lee
, Subin An
, Byung-Jun Jang
, Soochahn Lee
:
Deep Learning for Counting People from UWB Channel Impulse Response Signals. Sensors 23(16): 7093 (2023) - [i6]Sojung Go, Younghoon Ji, Sang Jun Park, Soochahn Lee:
Generation of Structurally Realistic Retinal Fundus Images with Diffusion Models. CoRR abs/2305.06813 (2023) - 2022
- [j16]Sojung Go
, Jooyoung Kim
, Kyoung Jin Noh
, Sang Jun Park
, Soochahn Lee
:
Combined Deep Learning of Fundus Images and Fluorescein Angiography for Retinal Artery/Vein Classification. IEEE Access 10: 70688-70698 (2022) - [i5]Seung Yeon Shin, Soochahn Lee, Kyoung Jin Noh, Il Dong Yun, Kyoung Mu Lee:
Extraction of Coronary Vessels in Fluoroscopic X-Ray Sequences Using Vessel Correspondence Optimization. CoRR abs/2207.13837 (2022) - 2021
- [j15]Yongseok Mun
, Jooyoung Kim, Kyoung Jin Noh, Soochahn Lee, Seok Kim, Soyoung Yi, Kyu Hyung Park, Sooyoung Yoo, Dong-Jin Chang
, Sang Jun Park
:
An innovative strategy for standardized, structured, and interoperable results in ophthalmic examinations. BMC Medical Informatics Decis. Mak. 21(1): 9 (2021) - [i4]Euyoung Kim, Soochahn Lee, Kyoung Mu Lee:
Generative Residual Attention Network for Disease Detection. CoRR abs/2110.12984 (2021) - 2020
- [j14]Kyoung Jin Noh
, Jooyoung Kim
, Sang Jun Park
, Soochahn Lee
:
Multimodal Registration of Fundus Images With Fluorescein Angiography for Fine-Scale Vessel Segmentation. IEEE Access 8: 63757-63769 (2020) - [j13]Sunghee Jung
, Soochahn Lee
, Byunghwan Jeon
, Yeonggul Jang
, Hyuk-Jae Chang
:
Deep Learning Cross-Phase Style Transfer for Motion Artifact Correction in Coronary Computed Tomography Angiography. IEEE Access 8: 81849-81863 (2020) - [j12]Euyoung Kim, Seung Yeon Shin, Soochahn Lee, Kyong Joon Lee, Kyoung Ho Lee, Kyoung Mu Lee:
Triplanar convolution with shared 2D kernels for 3D classification and shape retrieval. Comput. Vis. Image Underst. 193: 102901 (2020) - [c14]Kyoung Jin Noh, Sang Jun Park, Soochahn Lee:
Combining Fundus Images and Fluorescein Angiography for Artery/Vein Classification Using the Hierarchical Vessel Graph Network. MICCAI (5) 2020: 595-605
2010 – 2019
- 2019
- [j11]Soochahn Lee, Changho Jeon
, Leonard Sunwoo
, Dong Yul Oh
, Kyong Joon Lee
:
Phase-Based Nonrigid Deformation for Digital Subtraction Angiography. IEEE Access 7: 32256-32265 (2019) - [j10]Ho Yub Jung
, Yong Seok Heo
, Soochahn Lee
:
Fingerprint Liveness Detection by a Template-Probe Convolutional Neural Network. IEEE Access 7: 118986-118993 (2019) - [j9]Kyoung Jin Noh, Sang Jun Park, Soochahn Lee:
Scale-space approximated convolutional neural networks for retinal vessel segmentation. Comput. Methods Programs Biomed. 178: 237-246 (2019) - [j8]Seung Yeon Shin
, Soochahn Lee
, Il Dong Yun
, Kyoung Mu Lee:
Deep vessel segmentation by learning graphical connectivity. Medical Image Anal. 58 (2019) - [j7]Seung Yeon Shin
, Soochahn Lee
, Il Dong Yun
, Sun Mi Kim
, Kyoung Mu Lee
:
Joint Weakly and Semi-Supervised Deep Learning for Localization and Classification of Masses in Breast Ultrasound Images. IEEE Trans. Medical Imaging 38(3): 762-774 (2019) - [c13]Kyoung Jin Noh, Sang Jun Park, Soochahn Lee:
Fine-Scale Vessel Extraction in Fundus Images by Registration with Fluorescein Angiography. MICCAI (1) 2019: 779-787 - 2018
- [c12]Taewoo Park, Soochahn Lee, Il Dong Yun:
Nonrigid 2D registration of coronary artery angiograms with periodic displacement field. Medical Imaging: Biomedical Applications in Molecular, Structural, and Functional Imaging 2018: 105781N - [c11]Sunghee Jung, Soochahn Lee, Byunghwan Jeon, Yeonggul Jang, Hyuk-Jae Chang:
Deep Learning Based Coronary Artery Motion Artifact Compensation Using Style-Transfer Synthesis in CT Images. SASHIMI@MICCAI 2018: 100-110 - [i3]Seung Yeon Shin, Soochahn Lee, Il Dong Yun, Kyoung Mu Lee:
Deep Vessel Segmentation By Learning Graphical Connectivity. CoRR abs/1806.02279 (2018) - [i2]Kyoung Jin Noh, Sang Jun Park, Soochahn Lee:
Scale Space Approximation in Convolutional Neural Networks for Retinal Vessel Segmentation. CoRR abs/1806.09230 (2018) - 2017
- [j6]Yong Seok Heo, Soochahn Lee, Ho Yub Jung:
Dual Exposure Fusion with Entropy-based Residual Filtering. KSII Trans. Internet Inf. Syst. 11(5): 2555-2575 (2017) - [c10]Taewoo Park, Seung Yeon Shin, Youngtaek Hong, Soochahn Lee, Hyuk-Jae Chang, Il Dong Yun:
Nonrigid 2D registration of fluoroscopic coronary artery image sequence with propagated deformation field. Medical Imaging: Biomedical Applications in Molecular, Structural, and Functional Imaging 2017: 101371W - [c9]Soochahn Lee, Se-Hoon Kim, Woo-Sung Shim:
Adaptive Combination of Local Motion, Appearance, and Shape for Video Segmentation. Visual Information Processing and Communication 2017: 44-50 - [i1]Seung Yeon Shin, Soochahn Lee, Il Dong Yun, Kyoung Mu Lee:
Joint Weakly and Semi-Supervised Deep Learning for Localization and Classification of Masses in Breast Ultrasound Images. CoRR abs/1710.03778 (2017) - 2016
- [j5]Yong Seok Heo, Soochahn Lee, Ho Yub Jung:
Consistent color and detail transfer from multiple source images for video and images. Vis. Comput. 32(10): 1273-1289 (2016) - [c8]Seung Yeon Shin, Soochahn Lee, Kyoung Jin Noh, Il Dong Yun, Kyoung Mu Lee:
Extraction of Coronary Vessels in Fluoroscopic X-Ray Sequences Using Vessel Correspondence Optimization. MICCAI (3) 2016: 308-316 - 2015
- [j4]Sang Hyun Park, Soochahn Lee, Il Dong Yun, Sang Uk Lee:
Structured patch model for a unified automatic and interactive segmentation framework. Medical Image Anal. 24(1): 297-312 (2015) - [c7]Ho Yub Jung, Soochahn Lee, Yong Seok Heo, Il Dong Yun:
Random tree walk toward instantaneous 3D human pose estimation. CVPR 2015: 2467-2474 - 2014
- [c6]Seung Yeon Shin, Soochahn Lee, Il Dong Yun:
Classification based micro-calcification detection using discriminative restricted Boltzmann machine in digitized mammograms. Medical Imaging: Computer-Aided Diagnosis 2014: 90351L - 2013
- [j3]Sang Hyun Park, Soochahn Lee, Il Dong Yun, Sang Uk Lee:
Hierarchical MRF of globally consistent localized classifiers for 3D medical image segmentation. Pattern Recognit. 46(9): 2408-2419 (2013) - 2012
- [c5]Sang Hyun Park, Soochahn Lee, Il Dong Yun, Sang Uk Lee:
Automatic bone segmentation in knee MR images using a coarse-to-fine strategy. Medical Imaging: Image Processing 2012: 831405 - 2011
- [j2]Soochahn Lee, Sang Hyun Park, Hackjoon Shim, Il Dong Yun, Sang Uk Lee:
Optimization of local shape and appearance probabilities for segmentation of knee cartilage in 3-D MR images. Comput. Vis. Image Underst. 115(12): 1710-1720 (2011) - 2010
- [j1]Soochahn Lee, Il Dong Yun, Sang Uk Lee:
Robust bilayer video segmentation by adaptive propagation of global shape and local appearance. J. Vis. Commun. Image Represent. 21(7): 665-676 (2010)
2000 – 2009
- 2009
- [c4]Sang Hyun Park, Soochahn Lee, Hackjoon Shim, Il Dong Yun, Sang Uk Lee, Kyoung Ho Lee
, Heung Sik Kang, Joon Koo Han:
Fully automatic 3-D segmentation of knee bone compartments by iterative local branch-and-mincut on MR images from osteoarthritis initiative (OAI). ICIP 2009: 3381-3384 - 2008
- [c3]Hackjoon Shim, Soochahn Lee, Bohyeong Kim, Cheng Tao, Samuel Chang, Il Dong Yun, Sang Uk Lee, C. Kent Kwoh, Kyongtae Ty Bae:
3-D segmentation of articular cartilages by graph cuts using knee MR images from osteoarthritis initiative. Medical Imaging: Image Processing 2008: 691448 - 2006
- [c2]Soochahn Lee, Sehyuk Yoon, Il Dong Yun, Duck Hoon Kim, Kyoung Mu Lee, Sang Uk Lee:
A New 3-D Model Retrieval System Based on Aspect-Transition Descriptor. ECCV (4) 2006: 543-554 - 2005
- [c1]Soochahn Lee, Duck Hoon Kim, Sang Uk Lee, Il Dong Yun:
How CanWe Evaluate Object Recognition Algorithms Using a Public Object Image Database? CVPR Workshops 2005: 37
Coauthor Index
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last updated on 2024-08-23 18:35 CEST by the dblp team
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