Soochahn Lee

791 citations

30 papers · 477 indexed · h-index 10

Impact in

Ophthalmology top 5%
- Retinal and Optic Conditions
- Retinal Diseases and Treatments
- Glaucoma and retinal disorders
Radiology, Nuclear Medicine and Imaging top 5%
- Retinal Imaging and Analysis

Papers in ⓘ

Computer Vision and Pattern Recognition 18
- Medical Image Segmentation Techniques 8
- Advanced Vision and Imaging 6
- Video Surveillance and Tracking Methods 4
- Advanced Image and Video Retrieval Techniques 4
Ophthalmology 8
- Retinal Diseases and Treatments 5
- Glaucoma and retinal disorders 4

Co-authors: Il Dong Yun (10 shared papers)Kyoung Mu Lee (7 shared papers)Seung Yeon Shin (4 shared papers)Sang Jun Park (7 shared papers)Yong Seok Heo (5 shared papers)Ho Yub Jung (5 shared papers)Sang Uk Lee (3 shared papers)Kyu Hyung Park (3 shared papers)
Journals: IEEE Access (6 papers)Applied Sciences (3 papers)PLoS ONE (3 papers)Scientific Reports (2 papers)Medical Image Analysis (2 papers)
Partner nations: South Korea Puerto Rico Ethiopia

In The Last Decade

Soochahn Lee

25 papers receiving 461 citations

Peers

Countries citing papers authored by Soochahn Lee

Since Specialization

Citations

This map shows the geographic impact of Soochahn Lee's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Soochahn Lee with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Soochahn Lee more than expected).

Fields of papers citing papers by Soochahn Lee

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Soochahn Lee. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Soochahn Lee. The network helps show where Soochahn Lee may publish in the future.

Co-authors

The 25 scholars most cited alongside Soochahn Lee, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Soochahn Lee Line = papers co-authored together Soochahn Lee links everyone, so they are left out of the graph.

All Works

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20 of 20 papers shown

Showing the 20 most-cited of 30 papers — load more, or switch the sort, to bring in the rest.

#	Work
1	Deep vessel segmentation by learning graphical connectivity Medical Image Analysis ·Seung Yeon Shin, Soochahn Lee, Il Dong Yun, Kyoung Mu Lee	2019	158
2	Random tree walk toward instantaneous 3D human pose estimation Ho Yub Jung, Soochahn Lee, Yong Seok Heo, Il Dong Yun	2015	58
3	Scale-space approximated convolutional neural networks for retinal vessel segmentation Computer Methods and Programs in Biomedicine ·Kyoung Jin Noh, Sang Jun Park, Soochahn Lee	2019	53
4	Effects of Hypertension, Diabetes, and Smoking on Age and Sex Prediction from Retinal Fundus Images Scientific Reports ·Yong Dae Kim, Kyoung Jin Noh, Seong Jun Byun, Soochahn Lee, Tackeun Kim, Leonard Sunwoo, Kyong Joon Lee, Si‐Hyuck Kang, Kyu Hyung Park, Sang Jun Park	2020	47
5	Optimization of local shape and appearance probabilities for segmentation of knee cartilage in 3-D MR images Computer Vision and Image Understanding ·Soochahn Lee, (unknown), Sang Hyun Park, Hackjoon Shim, Il Dong Yun, Sang‐Uk Lee	2011	29
6	Fingerprint Liveness Detection by a Template-Probe Convolutional Neural Network IEEE Access ·Ho Yub Jung, Yong Seok Heo, Soochahn Lee	2019	22
7	Deep Learning Cross-Phase Style Transfer for Motion Artifact Correction in Coronary Computed Tomography Angiography IEEE Access ·Sung‐Hee Jung, Soochahn Lee, Byunghwan Jeon, Yeonggul Jang, Hyuk‐Jae Chang	2020	14
8	A deep learning-based framework for retinal fundus image enhancement PLoS ONE ·Kang Geon Lee, Su Jeong Song, Soochahn Lee, Hyeong Gon Yu, Dong Ik Kim, Kyoung Mu Lee	2023	12
9	Hierarchical MRF of globally consistent localized classifiers for 3D medical image segmentation Pattern Recognition ·Sang Hyun Park, Soochahn Lee, Il Dong Yun, Sang Uk Lee	2013	12
10	Robust bilayer video segmentation by adaptive propagation of global shape and local appearance Journal of Visual Communication and Image Representation ·Soochahn Lee, Il Dong Yun, Sang Uk Lee	2010	9
11	Multimodal Registration of Fundus Images With Fluorescein Angiography for Fine-Scale Vessel Segmentation IEEE Access ·Kyoung Jin Noh, Joo‐Young Kim, Sang Jun Park, Soochahn Lee	2020	9
12	An innovative strategy for standardized, structured, and interoperable results in ophthalmic examinations BMC Medical Informatics and Decision Making ·Yongseok Mun, Joo‐Young Kim, Kyoung Jin Noh, Soochahn Lee, Seok Kim, Soyoung Yi, Kyu Hyung Park, Sooyoung Yoo, Dong Jin Chang, Sang Jun Park	2021	8
13	Triplanar convolution with shared 2D kernels for 3D classification and shape retrieval Computer Vision and Image Understanding ·Eu Young Kim, Seung Yeon Shin, Soochahn Lee, Kyong Joon Lee, Kyoung Ho Lee, Kyoung Mu Lee, (unknown), (unknown), (unknown)	2020	7
14	Abnormality Detection in Chest X-Ray via Residual-Saliency From Normal Generation IEEE Access ·Euyoung Kim, Soochahn Lee, Kyoung Mu Lee	2023	7
15	A Novel Cascade Classifier for Automatic Microcalcification Detection PLoS ONE ·Seung Yeon Shin, Soochahn Lee, Il Dong Yun, Ho Yub Jung, Yong Seok Heo, Sun Mi Kim, Kyoung Mu Lee	2015	6
16	Structured patch model for a unified automatic and interactive segmentation framework Medical Image Analysis ·Sang Hyun Park, Soochahn Lee, Il Dong Yun, Sang Uk Lee	2015	4
17	Fully automatic 3-D segmentation of knee bone compartments by iterative local branch-and-mincut on MR images from osteoarthritis initiative (OAI) Sang Hyun Park, Soochahn Lee, Hackjoon Shim, Il Dong Yun, Sang Uk Lee, Kyoung Ho Lee, Heung Sik Kang, Joon Koo Han	2009	4
18	Topology-Aware Retinal Artery–Vein Classification via Deep Vascular Connectivity Prediction Applied Sciences ·Seung Yeon Shin, Soochahn Lee, Il Dong Yun, Kyoung Mu Lee	2020	4
19	Deep Learning for Counting People from UWB Channel Impulse Response Signals Sensors ·Gun Jik Lee, Subin An, Byung‐Jun Jang, Soochahn Lee	2023	3
20	Forest Walk Methods for Localizing Body Joints from Single Depth Image PLoS ONE ·Ho Yub Jung, Soochahn Lee, Yong Seok Heo, Il Dong Yun	2015	3

About Soochahn Lee

Soochahn Lee is a scholar working on Computer Vision and Pattern Recognition, Ophthalmology, Radiology, Nuclear Medicine and Imaging, Software and Geology, having authored 30 papers that have together received 477 indexed citations. Recurring topics across this work include Retinal Imaging and Analysis (10 papers), Medical Image Segmentation Techniques (8 papers), Advanced Vision and Imaging (6 papers), Retinal Diseases and Treatments (5 papers), Medical Imaging Techniques and Applications (4 papers), Glaucoma and retinal disorders (4 papers), Video Surveillance and Tracking Methods (4 papers) and Advanced Image and Video Retrieval Techniques (4 papers). The work is most often cited by research in Ophthalmology (153 citations), Radiology, Nuclear Medicine and Imaging (293 citations), Computer Vision and Pattern Recognition (255 citations), Health Informatics (7 citations) and Human-Computer Interaction (20 citations). Soochahn Lee has collaborated with scholars based in South Korea, Puerto Rico and Ethiopia. Frequent co-authors include Il Dong Yun, Kyoung Mu Lee, Seung Yeon Shin, Sang Jun Park, Yong Seok Heo, Ho Yub Jung, Sang Uk Lee, Kyu Hyung Park, Kyong Joon Lee and Hackjoon Shim. Their work appears in journals such as IEEE Access, Applied Sciences, PLoS ONE, Scientific Reports and Medical Image Analysis.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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