[J10] Jihyeon Kim, Gyeongmin Lee, Seung Yeon Shin, Soopil Kim, and Sang Hyun Park, "MOSInversion: Knowledge distillation-based incremental learning in organ segmentation using DeepInversion," Computers in Biology and Medicine, 2025. [paper]

[J9] Seung Yeon Shin, Stephen A. Wank, and Ronald M. Summers, "Size-Controllable Tumor Synthesis for Improved Detection of Small Bowel Carcinoid Tumors in CT Scans," IEEE Access, 2025. [paper]

[J8] Seung Yeon Shin, Thomas C. Shen, and Ronald M. Summers, "Improving Segmentation and Detection of Lesions in CT Scans Using Intensity Distribution Supervision," Computerized Medical Imaging and Graphics, 2023. [paper] [code]

[J7] Seung Yeon Shin, Thomas C. Shen, Stephen A. Wank, and Ronald M. Summers, "Fully-Automated Detection of Small Bowel Carcinoid Tumors in CT Scans using Deep Learning," Medical Physics, 2023. [paper]

[C12] Manas K. Nag, Jianfei Liu, Seung Yeon Shin, Benjamin Hou, Liangchen Liu, Jung-Min Lee, and Ronald M. Summers, "Improved Ascites Segmentation with Bladder Identification using Anatomical Location Residual (ALR) U-Net," SPIE Medical Imaging, 2023. [paper]

[C11] Seung Yeon Shin, Thomas C. Shen, Stephen A. Wank, and Ronald M. Summers, "Improving Small Lesion Segmentation in CT Scans using Intensity Distribution Supervision: Application to Small Bowel Carcinoid Tumor," SPIE Medical Imaging, 2023. [paper]

[C10] Manas K. Nag, Jianfei Liu, Liangchen Liu, Seung Yeon Shin, Sungwon Lee, Jung-Min Lee, and Ronald M. Summers, "Body Location Embedded 3D U-Net (BLE-U-Net) for Ovarian Cancer Ascites Segmentation on CT Scans," International Symposium on Medical Information Processing and Analysis (SIPAIM), 2022. [paper]

[C9] Liangchen Liu, Jianfei Liu, Manas K. Nag, Navid Hasani, Seung Yeon Shin, Sriram Paravastu, Jing Xiao, Lingyun Huang, Babak saboury, and Ronald M. Summers, "Improve Multi-modal Patch Based Lymphoma Segmentation with Negative Sample Augmentation and Label Guidance on PET/CT Scans," Medical Image Computing and Computer Assisted Intervention (MICCAI) Multiscale Multimodal Medical Imaging (MMMI), 2022. [paper]

[C8] Seung Yeon Shin and Ronald M. Summers, "Deep Reinforcement Learning for Small Bowel Path Tracking using Different Types of Annotations," Medical Image Computing and Computer Assisted Intervention (MICCAI), 2022. (Early Accepted, Top 13%) [paper]

[C7] Seung Yeon Shin, Sungwon Lee, and Ronald M. Summers, "Graph-based Small Bowel Path Tracking with Cylindrical Constraints," IEEE International Symposium on Biomedical Imaging (ISBI), 2022. [paper]

[C6] Seung Yeon Shin, Sungwon Lee, and Ronald M. Summers, "A Graph-theoretic Algorithm for Small Bowel Path Tracking in CT Scans," SPIE Medical Imaging, 2022. [paper]

[C5] Seung Yeon Shin, Sungwon Lee, and Ronald M. Summers, "Unsupervised Domain Adaptation for Small Bowel Segmentation using Disentangled Representation," Medical Image Computing and Computer Assisted Intervention (MICCAI), 2021. [paper]

[J6] Hwaseong Ryu, Seung Yeon Shin, Jae Young Lee, Kyoung Mu Lee, Hyo-jin Kang, and Jonghyon Yi, "Joint Segmentation and Classification of Hepatic Lesions in Ultrasound Images using Deep Learning," European Radiology, 2021. (Co-first author) [paper]

[J5] Seung Yeon Shin, Soochahn Lee, Il Dong Yun, and Kyoung Mu Lee, "Topology-Aware Retinal Artery-Vein Classification via Deep Vascular Connectivity Prediction," Applied Sciences, 2021. [paper]

[C4] Seung Yeon Shin, Sungwon Lee, Daniel C. Elton, James L. Gulley, and Ronald M. Summers, "Deep Small Bowel Segmentation with Cylindrical Topological Constraints," Medical Image Computing and Computer Assisted Intervention (MICCAI), 2020. [paper]

[J4] Eu Young Kim, Seung Yeon Shin, Soochahn Lee, Kyong Joon Lee, Kyoung Ho Lee, and Kyoung Mu Lee, "Triplanar Convolution with Shared 2D Kernels for 3D Classification and Shape Retrieval," Computer Vision and Image Understanding (CVIU), 2020. [paper]

[J3] Seung Yeon Shin, Soochahn Lee, Il Dong Yun, and Kyoung Mu Lee, "Deep Vessel Segmentation by Learning Graphical Connectivity," Medical Image Analysis, 2019. [paper] [code]

[J2] Seung Yeon Shin, Soochahn Lee, Il Dong Yun, Sun Mi Kim, and Kyoung Mu Lee, "Joint Weakly and Semi-Supervised Deep Learning for Localization and Classification of Masses in Breast Ultrasound Images," IEEE Transactions on Medica Imaging (T-MI), 2019. [paper] [code]

[C3] Taewoo Park, Seung Yeon Shin, Youngtaek Hong, Soochahn Lee, Hyuk-Jae Chang, and Il Dong Yun, "Nonrigid 2D Registration of Fluoroscopic Coronary Artery Image Sequence with Propagated Deformation Field," SPIE Medical Imaging, 2017. [paper]

[C2] Seung Yeon Shin, Soochahn Lee, Kyoung Jin Noh, Il Dong Yun, and Kyoung Mu Lee, "Extraction of Coronary Vessels in Fluoroscopic X-Ray Sequences using Vessel Correspondence Optimization," Medical Image Computing and Computer Assisted Intervention (MICCAI), 2016. (Early Accepted) [paper] [code]

[J1] Seung Yeon Shin, Soochahn Lee, Il Dong Yun, Ho Yub Jung, Yong Seok Heo, Sun Mi Kim, and Kyoung Mu Lee, "A Novel Cascade Classifier for Automatic Microcalcification Detection," PLoS ONE, 2015. [paper] [data]

[C1] Seung Yeon Shin, Soochahn Lee, and Il Dong Yun, "Classification based Micro-Calcification Detection using Discriminative Restricted Boltzmann Machine in Digitized Mammograms," SPIE Medical Imaging, 2014. [paper]