publications

Publications by categories in reversed chronological order. For detail, please check the CV.

2026

  1. JMI
    Contrastive learning and advanced bundle metrics outperform fractional anisotropy for Alzheimer’s disease diffusion MRI prediction: findings from the Beyond FA challenge
    Elyssa McMaster, Nancy Newlin, Trent Schwartz, Adam Saunders, Gaurav Rudravaram, Jiheng Li, André Hucke, Yehyun Suh,  ..., Yihao Liu, Lianrui Zuo, Eleftherios Garyfallidis, Talia Nir, Neda Jahanshad, Kurt Schilling, Daniel Moyer, and Bennett A. Landman
    Journal of Medical Imaging, 2026
  2. MIDL
    Landmark Detection Uncertainty as a Reliability Weight for Robust Landmark-based 2D/3D Pelvic Pose Estimation
    Yehyun Suh, Brayden Schott, Chou Mo, J. Ryan Martin, and Daniel Moyer
    In Medical Imaging with Deep Learning, 2026
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  3. SPIE MI
    Enhanced landmark detection model in pelvic fluoroscopy using 2D/3D registration loss
    Chou Mo, Yehyun Suh, J Ryan Martin, and Daniel Moyer
    In Medical Imaging 2026: Clinical and Biomedical Imaging, 2026
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  4. SPIE MI
    Predicting 2D and 3D leg motion from short-leg films in total knee arthroplasty
    Zheye Caroline Yao, Yehyun Suh, Anoop Chandrashekar, J Ryan Martin, and Daniel Moyer
    In Medical Imaging 2026: Clinical and Biomedical Imaging, 2026
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  5. SPIE MI
    Pedicle screw pairing and registration for screw pose estimation from dual C-arm images using CAD models
    Yehyun Suh, Lin Li, Aric Plumley, Chaochao Zhou, Daniel Moyer, and Kongbin Kang
    In Medical Imaging 2026: Image-Guided Procedures, Robotic Interventions, and Modeling, 2026
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2025

  1. MICCAI CLIP
    2D/3D Registration of Acetabular Hip Implants Under Perspective Projection and Fully Differentiable Ellipse Fitting
    Yehyun Suh, J Ryan Martin, and Daniel Moyer
    In Workshop on Clinical Image-Based Procedures, 2025
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  2. JoA
    Development of a Machine Learning Model for Determining Alignment in Knees Following Total Knee Arthroplasty
    Anoop S. Chandrashekar, Yehyun Suh, Jacob A. Fox, Aleksander P. Mika, Daniel C. Moyer, Gregory G. Polkowski, Martin Faschingbauer, and J. Ryan Martin
    The Journal of Arthroplasty, 2025
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  3. MIDL
    Introducing Beyond FA: Crowdsourcing Imaging Biomarkers for Alzheimer’s Disease
    Elyssa M. McMaster, Nancy Newlin, Trent Schwartz, Adam M. Saunders, Gaurav Rudravaram, Yehyun Suh,  ..., Yihao Liu, Lianrui Zuo, Eleftherios Garyfallidis, Talia M. Nir, Neda Jahanshad, Kurt Schilling, Daniel Moyer, and Bennett Allan Landman
    In Medical Imaging with Deep Learning - Short Papers, 2025
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  4. SPIE MI
    Landmark prediction in large radiographs using RoI-based label augmentation
    Mahd Mohsin, Yehyun Suh, Anoop Chandrashekar, J Ryan Martin, and Daniel Moyer
    In Medical Imaging 2025: Clinical and Biomedical Imaging, 2025
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  5. arXiv
    Better Pose Initialization for Fast and Robust 2D/3D Pelvis Registration
    Yehyun Suh, J. Ryan Martin, and Daniel Moyer
    2025
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  6. JoA
    Development of a Deep Learning Model for Automating Implant Position in Total Hip Arthroplasty
    Peter YW. Chan, Courtney E. Baker, Yehyun Suh, Daniel Moyer, and J. Ryan Martin
    The Journal of Arthroplasty, 2025
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  7. CIBM
    Novel dilation-erosion labeling technique allows for rapid, accurate and adjustable alignment measurements in primary TKA
    Aleksander P Mika, Yehyun Suh, Robert W Elrod, Martin Faschingbauer, Daniel C Moyer, and J Ryan Martin
    Computers in Biology and Medicine, 2025
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2024

  1. Ped Rad
    Deep learning-based fully automatic Risser stage assessment model using abdominal radiographs
    Jae-Yeon Hwang, Yisak Kim, Jisun Hwang, Yehyun Suh, Sook Min Hwang, Hyeyun Lee, and Minsu Park
    Pediatric Radiology, 2024
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2023

  1. MedNeurIPS
    Label Augmentation Method for Medical Landmark Detection in Hip Radiograph Images
    Yehyun Suh, Peter Chan, J. Ryan Martin, and Daniel Moyer
    2023
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  2. MIDL
    Dilation-Erosion Methods for Radiograph Annotation in Total Knee Replacement
    Yehyun Suh, Aleksander Mika, J. Ryan Martin, and Daniel Moyer
    In Medical Imaging with Deep Learning, short paper track, 2023
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