이화여자대학교

Taehoon Shin Professor

Department of Mechanical & Biomedical Engineering/ Graduate Program in System Health and Engineering

신태훈 프로필 사진 
Prof. Shin obtained interdisciplinary academic and research experiences through undergrad study in mechanical engineering, PhD research in electrical engineering, and faculty career in radiology at University of Maryland. His research focus is on machine learning and deep learning algorithms for disease diagnosis, leison detection, disease prognosis, image processing and quality improvement. Related clinical applications include MRI-based brain disease diagnosis, X-ray-based muscularskeleton disease grading, and CT-based body tissue composition analysis.  
Research Lab URL: https://mil.ewha.ac.kr
  • Research Cooperation Building #356
  • 02-3277-6534
  • Research Interests
    • Deep learning, Machine learning, Image processing, MRI, Medical imaging
Research Record
  • Three-Dimensional Variable Slab-Selective Projection Acquisition Imaging IEEE TRANSACTIONS ON MEDICAL IMAGING, 2025, v.44 no.2, 728-737
    SCIE Scopus dColl.
  • Brain Age Prediction Using Multi-Hop Graph Attention Combined with Convolutional Neural Network Bioengineering, 2024, v.11 no.3, 265
    SCIE Scopus dColl.
  • Enhancement of artery visualization in contrast-enhanced cerebral MR angiography using generative neural networks Biomedical Signal Processing and Control, 2024, v.96, 106652
    SCIE Scopus dColl.
  • Variable-density velocity-selective magnetization preparation for non-contrast-enhanced peripheral MR angiography PHYSICAL AND ENGINEERING SCIENCES IN MEDICINE, 2024, v.47 no.4, 1763-1771
    SCIE Scopus dColl.
  • Whole-Neck Non-Contrast-Enhanced MR Angiography Using Velocity Selective Magnetization Preparation TOMOGRAPHY, 2023, v.9 no.1, 60-69
    SCIE Scopus dColl.
  • Generalized self-calibrating simultaneous multi-slice MR image reconstruction from 3D Fourier encoding perspective Medical Image Analysis, 2022, v.82, 102621
    SCIE Scopus dColl.
  • Brain MRI radiomics analysis may predict poor psychomotor outcome in preterm neonates European Radiology, 2021, v.31 no.8, 6147-6155
    SCIE Scopus dColl.
  • Improved acceleration of phase-contrast flow imaging with magnitude difference regularization Magnetic Resonance Imaging, 2020, v.67, 1-6
    SCIE Scopus dColl.
  • [학술지논문] Three-Dimensional Variable Slab-Selective Projection Acquisition Imaging IEEE TRANSACTIONS ON MEDICAL IMAGING, 2025, v.44 no.2 , 728-737
    SCIE
  • [학술지논문] Enhancement of artery visualization in contrast-enhanced cerebral MR angiography using generative neural networks BIOMEDICAL SIGNAL PROCESSING AND CONTROL, 2024, v.96 no.0 , 106652-106652
    SCIE
  • [학술지논문] Generalized self-calibrating simultaneous multi-slice MR image reconstruction from 3D Fourier encoding perspective MEDICAL IMAGE ANALYSIS, 2022, v.82 no.0 , 102621-102621
    SCI
  • [학술지논문] Brain MRI radiomics analysis may predict poor psychomotor outcome in preterm neonates EUROPEAN RADIOLOGY, 2021, v.31 no.8 , 6147-6155
    SCI
  • [학술발표] Semi-supervised bone marrow lesion detection from knee MRI segmentation using mask inpainting models SPIE Medical Imaging, 미국, 샌디에고, 2025-02-17 SPIE Medical Imaging, 2025
  • [학술발표] 경동맥 MRA 이미지를 이용한 딥러닝 모델 기반 뇌백질변성 질병 분류 대한전자공학회 하계학술대회, 대한민국, 2024-06-27 대한전자공학회 2024년 하계학술대회논문집, 2024
  • [학술발표] 3D body composition segmentation in abdomen and pelvis CT using subdivided labels and random patch Medical Imaging with Deep Learning (MIDL), 미국, Nashville, 2023-07-12 Proceedings of MIDL2023, 2023
  • [학술발표] Brain age prediction using multi-hop graph attention module (MGA) with convolutional neural network Medical Imaging with Deep Learning (MIDL) Annual Meeting, 미국, 2023-07-12 Proceedings of MIDL2023, 2023
  • [학술발표] 자기 지도 사전 학습 Swin UNETR 모델을 이용한 3차원 체성분 분할 대한전자공학회하계종합학술대회, 대한민국, 2023-06-29 2023년 대학전자공학회하계학술대회논문집, 2023
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Courses

  • 2025-1st

    • Introduction to Mechanical and Biomedical Engineering

      • Subject No 38559Class No 01
      • 1Year ( 2Credit , 2Hour) Mon 4~4 (ESEA) , Thu 5~5 (CH)
        • Syllabus(File)

    • Introduction to Mechanical and Biomedical Engineering

      • Subject No 38559Class No 02
      • 1Year ( 2Credit , 2Hour) Mon 2~2 (ENG ) , Thu 3~3 (161)
        • Syllabus(File)

    • Biomedical Signal Processing

      • Subject No 38659Class No 01
      • 3Year ( 3Credit , 3Hour) Mon 7~7 (POSCO) , Thu 7~7 (152)
      • Exchange students are not allowed
        • 영문계획안 Syllabus(File)

    • Pattern Recognition and Deep Learning 강의 계획서 상세보기

      • Subject No 38660Class No 01
      • 4Year ( 3Credit , 3Hour) Mon 5~5 (ENG ) , Wed 4~4 (159)
        • Syllabus(File)

    • Smart Factory Capstone Design

  • 2023-2nd

    • Electrical Engineering for Mechanical Engineers

    • Smart Factory Capstone Design

    • Big data analysis using deep learning

      • Subject No G18167Class No 01
      • Year ( 3Credit , 3Hour) Fri 6~7 (ENG )
        • Syllabus(File)

  • 2023-1st

    • Pattern Recognition and Machine Learning

    • Computational Medicine; Translating Models to Medicine 강의 계획서 상세보기

      • Subject No 38920Class No 01
      • Year ( 3Credit , 3Hour) Mon 3~4
      • Major Requisite
        • Syllabus(File)

    • Smart Factory Capstone Design

    • Deep Learning

      • Subject No G18425Class No 01
      • Year ( 3Credit , 3Hour) Fri 5~6 (ENG )
        • Syllabus(File)

  • 2022-2nd

    • Electrical Engineering for Mechanical Engineers

    • Biomedical image reconstruction

      • Subject No G17565Class No 01
      • Year ( 3Credit , 3Hour) Thu 5~6 (ENG )
        • Syllabus(File)

  • 2022-1st

    • HOKMA Seminar

    • Mechanical and Biomedical Engineering Experiment I

      • Subject No 38571Class No 02
      • 3Year ( 3Credit , 4.5Hour) Fri 5~7 (ENG )
        • Syllabus(File)

    • Capstone Project in Content Convergence

      • Subject No 38588Class No 01
      • 4Year ( 3Credit , 4.5Hour) Mon 2~2 (ENG A) , Thu 2~3 (101)
        • Syllabus(File)

    • Biomedical Signal Processing

      • Subject No 38659Class No 01
      • 3Year ( 3Credit , 3Hour) Mon 5~5 , Wed 4~4
        • Syllabus(File)

    • Pattern Recognition and Machine Learning

      • Subject No 38660Class No 01
      • 4Year ( 3Credit , 3Hour) Tue 6~6 (ESEA) , Thu 4~4 (CH)
        • Syllabus(File)

    • Computational Medicine; Translating Models to Medicine

      • Subject No 38920Class No 01
      • Year ( 3Credit , 3Hour) Mon 3~4
      • Major Requisite
        • Syllabus(File)
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Academic Background

University of Southern California Ph.D.(Electrical Engineering)

University of Southern California M.S.(Electrical Engineering)

Seoul Nat'l Univ. 공학사(기계설계학과)

Work Experience

Division Chair, Mechanical and Biomedical Engineering 2018-03-01 ~ 2019-02-28

University of Maryland 2013-04-17 ~ 2017-02-28

Stanford University 2010-02-01 ~ 2013-04-15