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Jin Keun Seo

Jin Keun Seo

D-Index & Metrics

Engineering and Technology

D-Index
57
Citations
9206
World Ranking
2730
National Ranking
54

Overview

Jin Keun Seo is affiliated with Yonsei University in South Korea and has contributed extensively to research in the intersecting fields of medicine, engineering, and dentistry. Their work primarily addresses medical imaging and analysis, with a focus on advanced techniques in radiography, X-ray, and computed tomography (CT).

The scientist's research outputs include studies in:

  • Dental Radiography and Imaging
  • Medical Imaging Techniques and Applications
  • Advanced X-ray and CT Imaging
  • Radiation Dose and Imaging
  • Medical Image Segmentation Techniques
  • Numerical methods in inverse problems
  • Medical Imaging and Analysis

Their main fields of study encompass Medicine, Engineering, and Dentistry, while subfields of emphasis include Biomedical Engineering, Radiology, Nuclear Medicine and Imaging, Oral Surgery, Computer Vision and Pattern Recognition, and Pediatrics, Perinatology and Child Health.

Jin Keun Seo's publication record features multiple recent papers, including:

  • "Automatic detection and segmentation of lumbar vertebrae from X-ray images for compression fracture evaluation," 2020, Computer Methods and Programs in Biomedicine
  • "Automated ultrasound assessment of amniotic fluid index using deep learning," 2021, Medical Image Analysis
  • "Learning-based local-to-global landmark annotation for automatic 3D cephalometry," 2020, Physics in Medicine and Biology
  • "Automation of Spine Curve Assessment in Frontal Radiographs Using Deep Learning of Vertebral-Tilt Vector," 2020, IEEE Access
  • "Deep learning method for reducing metal artifacts in dental cone-beam CT using supplementary information from intra-oral scan," 2022, Physics in Medicine and Biology

Frequent publication venues for Seo include arXiv (Cornell University), IEEE Access, Physics in Medicine and Biology, Medical Image Analysis, and Computer Methods and Programs in Biomedicine.

Coauthor collaborations are an important element of their research activity. Frequent coauthors include Chang Min Hyun, Tae Jun Jang, Hye Sun Yun, Hyoung Suk Park, and Sang-Hwy Lee.

Among their scholarly contributions is a book published with Springer Nature titled "Deep Learning and Medical Applications" released in 2023.

Best Publications

  • Deep learning for undersampled MRI reconstruction.

    Chang Min Hyun;Hwa Pyung Kim;Sung Min Lee;Sungchul Lee

  • Magnetic resonance electrical impedance tomography (MREIT): simulation study of J-substitution algorithm

    Ohin Kwon;Eung Je Woo;Jeong-Rock Yoon;Jin Keun Seo

  • Magnetic resonance electrical impedance tomography (MREIT) for high-resolution conductivity imaging

    Eung Je Woo;Jin Keun Seo

  • Reconstruction of conductivity and current density images using only one component of magnetic field measurements

    Jin Keun Seo;Jeong-Rock Yoon;Eung Je Woo;Ohin Kwon

  • Conductivity and current density image reconstruction using harmonic Bz algorithm in magnetic resonance electrical impedance tomography

    Suk Hoon Oh;Byung Il Lee;Eung Je Woo;Soo Yeol Lee

  • Magnetic Resonance Electrical Impedance Tomography (MREIT)

    Jin Keun Seo;Eung Je Woo

  • J-substitution algorithm in magnetic resonance electrical impedance tomography (MREIT): phantom experiments for static resistivity images

    Hyun Soo Khang;Byung Il Lee;Suk Hoon Oh;Eung Je Woo

  • The layer potential technique for the inverse conductivity problem

    Hyeonbae Kang;Jin Keun Seo

  • Nonlinear Inverse Problems in Imaging

    Jin Keun Seo;Eung Je Woo

  • A real time algorithm for the location search of discontinuous conductivities with one measurement

    Ohin Kwon;Jin Keun Seo;Jeong Rock Yoon

  • Level set-based bimodal segmentation with stationary global minimum

    Suk-Ho Lee;Jin Keun Seo

  • The inverse conductivity problem with one measurement: stability and estimation of size

    Hyeonbae Kang;Jin Keun Seo;Dongwoo Sheen

  • Frequency-difference electrical impedance tomography (fdEIT): algorithm development and feasibility study.

    Jin Keun Seo;Jeehyun Lee;Sung Wan Kim;Habib Zribi

  • On a Nonlinear Partial Differential Equation Arising in Magnetic Resonance Electrical Impedance Tomography

    Sungwhan Kim;Sungwhan Kim;Ohin Kwon;Jin Keun Seo;Jeong Rock Yoon;Jeong Rock Yoon

  • Noise removal with Gauss curvature-driven diffusion

    Suk-Ho Lee;Jin Keun Seo

  • In Vivo High-ResolutionConductivity Imaging of the Human Leg Using MREIT: The First Human Experiment

    Hyung Joong Kim;Young Tae Kim;A.S. Minhas;Woo Chul Jeong

  • Recent progress and future challenges in MR electric properties tomography.

    Ulrich Katscher;Dong Hyun Kim;Jin Keun Seo

  • Metal Artifact Reduction for Polychromatic X-ray CT Based on a Beam-Hardening Corrector

    Hyoung Suk Park;Dosik Hwang;Jin Keun Seo

  • Electrical conductivity images of biological tissue phantoms in MREIT

    Suk Hoon Oh;Byung Il Lee;Eung Je Woo;Soo Yeol Lee

  • Electrical conductivity imaging using gradient B/sub z/ decomposition algorithm in magnetic resonance electrical impedance tomography (MREIT)

    Chunjae Park;Ohin Kwon;Eung Je Woo;Jin Keun Seo

  • Noise analysis in magnetic resonance electrical impedance tomography at 3 and 11 T field strengths.

    Rosalind Sadleir;Samuel Grant;Sung Uk Zhang;Byung Il Lee

Frequent Co-Authors

Eung Je Woo
Eung Je Woo Kyung Hee University
Habib Ammari
Habib Ammari ETH Zurich
Hyeonbae Kang
Hyeonbae Kang Inha University
Yi Wang
Yi Wang Cornell University
William R B Lionheart
William R B Lionheart University of Manchester
Tae-Seong Kim
Tae-Seong Kim Kyung Hee University
Eugene B. Fabes
Eugene B. Fabes University of Minnesota
Manuchehr Soleimani
Manuchehr Soleimani University of Bath
David Holder
David Holder University College London
Jong Chul Ye
Jong Chul Ye Korea Advanced Institute of Science and Technology

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