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Seung-Koo Lee

Seung-Koo Lee

Yonsei University
Korea

D-Index & Metrics

Discipline name D-Index World Ranking Current World Ranking National Ranking Current National Ranking Publications Citations
Neuroscience 49 5949 5475 30 30 235 9691

Seung-Koo Lee publications per year

The chart shows the history of publications by Seung-Koo Lee between 1992 and 2025, highlighting the no. of papers published in each year and offering an overview of the publication velocity of this scholar. Seung-Koo Lee published across 34 years, from 1992 to 2025, averaging 11.5 papers a year. Output peaked at 41 publications in 2022. 52 of the 392 publications appeared in the last two years.

No. of publications
10 20 30 40
Bar chart. Horizontal axis: year, 1992 to 2025. Vertical axis: number of publications, 0 to 41. Peak 41 publications in 2022. 1992: 1 publication 1993: 0 publications 1994: 0 publications 1995: 0 publications 1996: 0 publications 1997: 1 publication 1998: 2 publications 1999: 2 publications 2000: 1 publication 2001: 1 publication 2002: 7 publications 2003: 8 publications 2004: 9 publications 2005: 8 publications 2006: 6 publications 2007: 10 publications 2008: 11 publications 2009: 6 publications 2010: 8 publications 2011: 6 publications 2012: 10 publications 2013: 8 publications 2014: 11 publications 2015: 9 publications 2016: 24 publications 2017: 16 publications 2018: 22 publications 2019: 11 publications 2020: 34 publications 2021: 34 publications 2022: 41 publications 2023: 33 publications 2024: 33 publications 2025: 19 publications
1992 2025

392 publications in total across all disciplines

View publications per year as a table
Seung-Koo Lee: publications per year, 1992 to 2025
Year Publications
1992 1
1993 0
1994 0
1995 0
1996 0
1997 1
1998 2
1999 2
2000 1
2001 1
2002 7
2003 8
2004 9
2005 8
2006 6
2007 10
2008 11
2009 6
2010 8
2011 6
2012 10
2013 8
2014 11
2015 9
2016 24
2017 16
2018 22
2019 11
2020 34
2021 34
2022 41
2023 33
2024 33
2025 19
Total 392
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Seung-Koo Lee publication distribution in Neuroscience in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Neuroscience in 2026. The highlighted bar marks where Seung-Koo Lee sits on this spectrum.

No. of scientists
100 200 300 400 500
Bar chart with 86 bars. Horizontal axis: publications, 38–47 to 887+. Vertical axis: number of scientists, 0 to 539. Most scientists, 539, have 98–107 publications. The last bar groups every scientist with 887 publications or more. The highlighted bar, 228–237 publications, is where this scientist sits. 38–47 publications: 18 scientists 48–57 publications: 79 scientists 58–67 publications: 193 scientists 68–77 publications: 323 scientists 78–87 publications: 406 scientists 88–97 publications: 452 scientists 98–107 publications: 539 scientists 108–117 publications: 505 scientists 118–127 publications: 522 scientists 128–137 publications: 469 scientists 138–147 publications: 456 scientists 148–157 publications: 459 scientists 158–167 publications: 397 scientists 168–177 publications: 383 scientists 178–187 publications: 350 scientists 188–197 publications: 302 scientists 198–207 publications: 306 scientists 208–217 publications: 262 scientists 218–227 publications: 242 scientists 228–237 publications: 220 scientists 238–247 publications: 203 scientists 248–257 publications: 174 scientists 258–267 publications: 176 scientists 268–277 publications: 175 scientists 278–287 publications: 125 scientists 288–297 publications: 116 scientists 298–307 publications: 127 scientists 308–317 publications: 128 scientists 318–327 publications: 99 scientists 328–337 publications: 89 scientists 338–347 publications: 78 scientists 348–357 publications: 96 scientists 358–367 publications: 66 scientists 368–377 publications: 59 scientists 378–387 publications: 65 scientists 388–397 publications: 54 scientists 398–407 publications: 48 scientists 408–417 publications: 49 scientists 418–427 publications: 34 scientists 428–437 publications: 31 scientists 438–447 publications: 30 scientists 448–457 publications: 31 scientists 458–467 publications: 36 scientists 468–477 publications: 40 scientists 478–487 publications: 35 scientists 488–497 publications: 30 scientists 498–507 publications: 23 scientists 508–517 publications: 26 scientists 518–527 publications: 20 scientists 528–537 publications: 23 scientists 538–547 publications: 20 scientists 548–557 publications: 20 scientists 558–567 publications: 17 scientists 568–577 publications: 14 scientists 578–587 publications: 20 scientists 588–597 publications: 20 scientists 598–607 publications: 19 scientists 608–617 publications: 18 scientists 618–627 publications: 17 scientists 628–637 publications: 11 scientists 638–647 publications: 11 scientists 648–657 publications: 11 scientists 658–667 publications: 8 scientists 668–677 publications: 7 scientists 678–687 publications: 11 scientists 688–697 publications: 10 scientists 698–707 publications: 4 scientists 708–717 publications: 6 scientists 718–727 publications: 5 scientists 728–737 publications: 5 scientists 738–747 publications: 9 scientists 748–757 publications: 9 scientists 758–767 publications: 3 scientists 768–777 publications: 7 scientists 778–787 publications: 7 scientists 788–797 publications: 6 scientists 798–807 publications: 2 scientists 808–817 publications: 2 scientists 818–827 publications: 7 scientists 828–837 publications: 0 scientists 838–847 publications: 9 scientists 848–857 publications: 3 scientists 858–867 publications: 1 scientist 868–877 publications: 3 scientists 878–886 publications: 6 scientists 887+ publications: 100 scientists
38–47 publications 887+

This scientist: 235 publications — 71st percentile

71% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 887 publications or more.

View publications distribution as a table
Number of Neuroscience scientists by publication count, Research.com 2026 ranking edition. Based on 9,597 ranked scientists.
Publications Scientists This scientist
38–47 18
48–57 79
58–67 193
68–77 323
78–87 406
88–97 452
98–107 539
108–117 505
118–127 522
128–137 469
138–147 456
148–157 459
158–167 397
168–177 383
178–187 350
188–197 302
198–207 306
208–217 262
218–227 242
228–237 220 235
238–247 203
248–257 174
258–267 176
268–277 175
278–287 125
288–297 116
298–307 127
308–317 128
318–327 99
328–337 89
338–347 78
348–357 96
358–367 66
368–377 59
378–387 65
388–397 54
398–407 48
408–417 49
418–427 34
428–437 31
438–447 30
448–457 31
458–467 36
468–477 40
478–487 35
488–497 30
498–507 23
508–517 26
518–527 20
528–537 23
538–547 20
548–557 20
558–567 17
568–577 14
578–587 20
588–597 20
598–607 19
608–617 18
618–627 17
628–637 11
638–647 11
648–657 11
658–667 8
668–677 7
678–687 11
688–697 10
698–707 4
708–717 6
718–727 5
728–737 5
738–747 9
748–757 9
758–767 3
768–777 7
778–787 7
788–797 6
798–807 2
808–817 2
818–827 7
828–837 0
838–847 9
848–857 3
858–867 1
868–877 3
878–886 6
887+ 100
Download as CSV

Seung-Koo Lee D-index placement in Neuroscience in 2026

The chart shows the D-index (discipline H-index) distribution of Neuroscience scientists ranked by Research.com in 2026. The highlighted bar marks where Seung-Koo Lee sits on this spectrum.

No. of scientists
100 200 300 400 500
Bar chart with 68 bars. Horizontal axis: D-Index, 30–31 to 163+. Vertical axis: number of scientists, 0 to 512. Most scientists, 512, have 46–47 D-Index. The last bar groups every scientist with 163 D-Index or more. The highlighted bar, 48–49 D-Index, is where this scientist sits. 30–31 D-Index: 42 scientists 32–33 D-Index: 172 scientists 34–35 D-Index: 296 scientists 36–37 D-Index: 435 scientists 38–39 D-Index: 459 scientists 40–41 D-Index: 456 scientists 42–43 D-Index: 467 scientists 44–45 D-Index: 478 scientists 46–47 D-Index: 512 scientists 48–49 D-Index: 435 scientists 50–51 D-Index: 425 scientists 52–53 D-Index: 418 scientists 54–55 D-Index: 392 scientists 56–57 D-Index: 357 scientists 58–59 D-Index: 334 scientists 60–61 D-Index: 328 scientists 62–63 D-Index: 260 scientists 64–65 D-Index: 278 scientists 66–67 D-Index: 239 scientists 68–69 D-Index: 250 scientists 70–71 D-Index: 210 scientists 72–73 D-Index: 200 scientists 74–75 D-Index: 189 scientists 76–77 D-Index: 170 scientists 78–79 D-Index: 146 scientists 80–81 D-Index: 113 scientists 82–83 D-Index: 126 scientists 84–85 D-Index: 100 scientists 86–87 D-Index: 84 scientists 88–89 D-Index: 99 scientists 90–91 D-Index: 84 scientists 92–93 D-Index: 85 scientists 94–95 D-Index: 72 scientists 96–97 D-Index: 76 scientists 98–99 D-Index: 45 scientists 100–101 D-Index: 49 scientists 102–103 D-Index: 43 scientists 104–105 D-Index: 32 scientists 106–107 D-Index: 45 scientists 108–109 D-Index: 50 scientists 110–111 D-Index: 32 scientists 112–113 D-Index: 39 scientists 114–115 D-Index: 32 scientists 116–117 D-Index: 29 scientists 118–119 D-Index: 27 scientists 120–121 D-Index: 19 scientists 122–123 D-Index: 23 scientists 124–125 D-Index: 27 scientists 126–127 D-Index: 16 scientists 128–129 D-Index: 24 scientists 130–131 D-Index: 13 scientists 132–133 D-Index: 21 scientists 134–135 D-Index: 17 scientists 136–137 D-Index: 14 scientists 138–139 D-Index: 15 scientists 140–141 D-Index: 10 scientists 142–143 D-Index: 10 scientists 144–145 D-Index: 13 scientists 146–147 D-Index: 9 scientists 148–149 D-Index: 8 scientists 150–151 D-Index: 6 scientists 152–153 D-Index: 6 scientists 154–155 D-Index: 7 scientists 156–157 D-Index: 7 scientists 158–159 D-Index: 10 scientists 160–161 D-Index: 4 scientists 162 D-Index: 8 scientists 163+ D-Index: 100 scientists
30–31 D-Index 163+

This scientist: 49 D-Index — 39th percentile

39% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 163 D-Index or more.

View D-Index distribution as a table
Number of Neuroscience scientists by D-index, Research.com 2026 ranking edition. Based on 9,597 ranked scientists.
D-Index Scientists This scientist
30–31 42
32–33 172
34–35 296
36–37 435
38–39 459
40–41 456
42–43 467
44–45 478
46–47 512
48–49 435 49
50–51 425
52–53 418
54–55 392
56–57 357
58–59 334
60–61 328
62–63 260
64–65 278
66–67 239
68–69 250
70–71 210
72–73 200
74–75 189
76–77 170
78–79 146
80–81 113
82–83 126
84–85 100
86–87 84
88–89 99
90–91 84
92–93 85
94–95 72
96–97 76
98–99 45
100–101 49
102–103 43
104–105 32
106–107 45
108–109 50
110–111 32
112–113 39
114–115 32
116–117 29
118–119 27
120–121 19
122–123 23
124–125 27
126–127 16
128–129 24
130–131 13
132–133 21
134–135 17
136–137 14
138–139 15
140–141 10
142–143 10
144–145 13
146–147 9
148–149 8
150–151 6
152–153 6
154–155 7
156–157 7
158–159 10
160–161 4
162 8
163+ 100
Download as CSV

Overview

Seung-Koo Lee is affiliated with Yonsei University in South Korea and has contributed extensively to the field of medical research, particularly in radiology and medical imaging. Their work emphasizes the application of radiomics and machine learning techniques to improve diagnostic and prognostic processes in neurological and oncological diseases.

Their research covers a broad array of topics including:

  • Radiomics and Machine Learning in Medical Imaging
  • Glioma Diagnosis and Treatment
  • MRI in cancer diagnosis
  • Meningioma and schwannoma management
  • Brain Metastases and Treatment
  • Advanced Neuroimaging Techniques and Applications
  • Medical Imaging Techniques and Applications

Seung-Koo Lee's main field of study is Medicine, with 387 published works. Their subfields include:

  • Radiology, Nuclear Medicine and Imaging
  • Genetics
  • Neurology
  • Pulmonary and Respiratory Medicine
  • Epidemiology

Frequent publication venues for Lee's work are:

  • European Radiology
  • Neuro-Oncology
  • Korean Journal of Radiology
  • Neuroradiology
  • Yonsei Medical Journal

Selected notable papers include:

  • Fully automated hybrid approach to predict the IDH mutation status of gliomas via deep learning and radiomics (2020, Neuro-Oncology)
  • Robust performance of deep learning for distinguishing glioblastoma from single brain metastasis using radiomic features: model development and validation (2020, Scientific Reports)
  • A deep learning algorithm may automate intracranial aneurysm detection on MR angiography with high diagnostic performance (2020, European Radiology)
  • Machine learning and radiomic phenotyping of lower grade gliomas: improving survival prediction (2020, European Radiology)
  • Radiomics machine learning study with a small sample size: Single random training-test set split may lead to unreliable results (2021, PLoS ONE)

Frequent co-authors collaborating with Lee include:

  • Sung Soo Ahn
  • Yae Won Park
  • Jong Hee Chang
  • Se Hoon Kim
  • Kyunghwa Han

Best Publications

  • Pediatric diffusion tensor imaging: normal database and observation of the white matter maturation in early childhood.

    Laurent Hermoye;Christine Saint-Martin;Guy Cosnard;Seung Koo Lee

  • Diffusion-tensor MR imaging and tractography : Exploring brain microstructure and connectivity

    Paolo G. P. Nucifora;Ragini Verma;Seung-Koo Lee;Elias R. Melhem

  • Free radicals as triggers of brain edema formation after stroke.

    Ji Hoe Heo;Sang Won Han;Seung Koo Lee

  • Diffusion-Tensor MR Imaging and Fiber Tractography: A New Method of Describing Aberrant Fiber Connections in Developmental CNS Anomalies

    Seung-Koo Lee;Dong Ik Kim;Jinna Kim;Dong Joon Kim

  • Corpus callosal connection mapping using cortical gray matter parcellation and DT-MRI

    Hae-Jeong Park;Jae Jin Kim;Seung-Koo Lee;Jeong Ho Seok

  • Predictors of surgical outcome and pathologic considerations in focal cortical dysplasia.

    D. W. Kim;S. K. Lee;K. Chu;K. I. Park

  • White matter abnormalities associated with auditory hallucinations in schizophrenia: a combined study of voxel-based analyses of diffusion tensor imaging and structural magnetic resonance imaging.

    Jeong Ho Seok;Jeong Ho Seok;Hae Jeong Park;Ji Won Chun;Seung Koo Lee

  • Fully automated hybrid approach to predict the IDH mutation status of gliomas via deep learning and radiomics

    Yoon Seong Choi;Yoon Seong Choi;Yoon Seong Choi;Sohi Bae;Jong Hee Chang;Seok Gu Kang

  • Atlas-based analysis of neurodevelopment from infancy to adulthood using diffusion tensor imaging and applications for automated abnormality detection

    Andreia V. Faria;Jiangyang Zhang;Kenichi Oishi;Xin Li

  • Results of Transvenous Embolization of Cavernous Dural Arteriovenous Fistula: A Single-Center Experience with Emphasis on Complications and Management

    D J Kim;D I Kim;S H Suh;J Kim

  • Stent-assisted coil embolization of intracranial wide-necked aneurysms.

    Young-Jun Lee;Dong Joon Kim;Sang Hyun Suh;Seung-Koo Lee

  • Mitochondrial respiratory chain defects: Underlying etiology in various epileptic conditions

    Young Mock Lee;Hoon Chul Kang;Joon Soo Lee;Se Hoon Kim

  • Radiomics and machine learning may accurately predict the grade and histological subtype in meningiomas using conventional and diffusion tensor imaging

    Yae Won Park;Yae Won Park;Jongmin Oh;Seng Chan You;Kyunghwa Han

  • Multiparametric tissue characterization of brain neoplasms and their recurrence using pattern classification of MR images

    Raginia Verma;Evangelia I. Zacharaki;Yangming Ou;Hongmin Cai

  • Prediction of IDH1-Mutation and 1p/19q-Codeletion Status Using Preoperative MR Imaging Phenotypes in Lower Grade Gliomas.

    Y.W. Park;K. Han;S.S. Ahn;S. Bae

  • ORBIT: A Multiresolution Framework for Deformable Registration of Brain Tumor Images

    E.I. Zacharaki;Dinggang Shen;Seung-Koo Lee;C. Davatzikos

  • MR Imaging of Neoplastic Central Nervous System Lesions: Review and Recommendations for Current Practice

    Marco Essig;N. Anzalone;S. E. Combs;A. Dörfler

  • Primary central nervous system lymphoma and atypical glioblastoma: Differentiation using radiomics approach

    Hie Bum Suh;Yoon Seong Choi;Sohi Bae;Sung Soo Ahn

  • MR imaging in multiple sclerosis: review and recommendations for current practice.

    Karl Olof Lövblad;N. Anzalone;A. Dörfler;M. Essig

  • Amide proton transfer imaging to discriminate between low- and high-grade gliomas: added value to apparent diffusion coefficient and relative cerebral blood volume

    Yoon Seong Choi;Sung Soo Ahn;Seung Koo Lee;Jong Hee Chang

Frequent Co-Authors

Phil Hyu Lee
Phil Hyu Lee Yonsei University
Susumu Mori
Susumu Mori Johns Hopkins University School of Medicine
Byung In Lee
Byung In Lee Inje University
Christos Davatzikos
Christos Davatzikos University of Pennsylvania
Heung Dong Kim
Heung Dong Kim Yonsei University Health System
Young H. Sohn
Young H. Sohn Yonsei University
Hae-Jeong Park
Hae-Jeong Park Yonsei University
Peter C.M. van Zijl
Peter C.M. van Zijl Kennedy Krieger Institute
Sang Won Seo
Sang Won Seo Samsung Medical Center
Daniel S. Marcus
Daniel S. Marcus Washington University in St. Louis

External Links

Personal website of Seung-Koo Lee

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Best Scientists Citing Seung-Koo Lee

Susumu Mori

Susumu Mori

Johns Hopkins University School of Medicine

Publications: 60

Dinggang Shen

Dinggang Shen

ShanghaiTech University

Publications: 32

Phil Hyu Lee

Phil Hyu Lee

Yonsei University

Publications: 29

Catherine Lebel

Catherine Lebel

University of Calgary

Publications: 29

Young H. Sohn

Young H. Sohn

Yonsei University

Publications: 27

Peter C.M. van Zijl

Peter C.M. van Zijl

Kennedy Krieger Institute

Publications: 26

Andreia V. Faria

Andreia V. Faria

Johns Hopkins University School of Medicine

Publications: 26

Marek Kubicki

Marek Kubicki

Brigham and Women's Hospital

Publications: 25

Christos Davatzikos

Christos Davatzikos

University of Pennsylvania

Publications: 25

Martha E. Shenton

Martha E. Shenton

Harvard University

Publications: 23

Hao Huang

Hao Huang

University of Pennsylvania

Publications: 21

Heung Dong Kim

Heung Dong Kim

Yonsei University Health System

Publications: 18

Arthur W. Toga

Arthur W. Toga

University of Southern California

Publications: 17

Guido Gerig

Guido Gerig

New York University

Publications: 16

Argye E. Hillis

Argye E. Hillis

Johns Hopkins University School of Medicine

Publications: 15

André Aleman

André Aleman

University Medical Center Groningen

Publications: 15

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