2024

H. Peng, A. Lewis, Y.H. Su, S. Lin, D.T. Chiang, W. Jiang, H. Lai, B. Hannaford, “Efficient Data-Driven Joint-Level Calibration of Cable-Driven Surgical Robots,“ accepted by npj Robotics, 2024. [paper]

S. Saha, S. Liu, S. Lin, J. Lu, & M.C. Yip, “BASED: Bundle-Adjusting Surgical Endoscopic Dynamic Video Reconstruction using Neural Radiance Fields,” accepted by arXiv IEEE/CVF Winter Conference on Applications of Computer Vision (WACV), 2024. [paper]

S. Lin, A.J. Miao, A. Alabiad, F. Liu, K. Wang, J. Lu, F. Richter, & M.C. Yip, “SuPerPM: A Surgical Perception Framework Based on Deep Point Matching Learned from Physical Constrained Simulation Data,” accepted by IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2024. [paper]

H. Peng, S. Lin, D. King, Y.H. Su, R.A. Bly, K.S. Moe, & B. Hannaford, “Reducing Annotating Load: Active Learning with Synthetic Images in Surgical Instrument Segmentation,” accepted by Medical Image Analysis, 2024. [paper][github]

Coauthor of “DROID: A Large-Scale In-The-Wild Robot Manipulation Dataset,” in Robotics: Science and Systems (RSS), 2024. [paper]

A.J. Miao, S. Lin, J. Lu, F. Richter, B. Ostrander, E.K. Funk, R.K. Orosco, & M.C. Yip, “HemoSet: The First Blood Segmentation Dataset for Automation of Hemostasis Management,” in International Symposium on Medical Robotics, 2024. [paper] 🏆 Best Student Paper Award

J.E. Katz, J. Finnegan, J. Lu, S. Lin, M.C. Yip, & R. Sur, “3D Rendering of Cystoscopy Video Footage: A Novel Method Utilizing Neural Radiance Field Processing,” in The Journal of Urology, 211(5S), p.e552, 2024. [paper]

S. Liu*, S. Lin*, J. Lu, A. Supikov, & M.C. Yip, “BAA-NGP: Bundle-Adjusting Accelerated Neural Graphics Primitives,” in Workshop on Visual Odometry and Computer Vision Applications Based on Location Clues @ CVPR, pp. 850-857, 2024. [paper][github]

J. Lu, F. Richter, S. Lin, & M.C. Yip, “Tracking Snake-like Robots in the Wild Using Only a Single Camera,” in IEEE International Conference on Robotics and Automation (ICRA), 2024. [paper]

X. Liang, F. Liu, Y. Zhang, Y. Li, S. Lin, & M.C. Yip, “Real-to-Sim Deformable Object Manipulation: Optimizing Physics Models with Residual Mappings for Robotic Surgery,” in IEEE International Conference on Robotics and Automation (ICRA), 2024. [paper]

F. Qin, T. Hou, S. Lin, Kaiyuan Wang, Michael C. Yip, & Shan Yu, “AnyOKP: One-Shot and Instance-Aware Object Keypoint Extraction with Pretrained ViT,” in IEEE International Conference on Robotics and Automation (ICRA), 2024. [paper][github]

Coauthor of “Open X-Embodiment: Robotic Learning Datasets and RT-X Models,” in IEEE International Conference on Robotics and Automation (ICRA), 2024. [paper] 🏆 Best Conference Paper Award

2023

S. Lin, Y. Zhi, & M.C. Yip, “SemHint-MD: Learning from Noisy Semantic Labels for Self-Supervised Monocular Depth Estimation,” arXiv preprint arXiv:2303.18219, 2023. [paper]

S. Lin, J. Lu, F. Richter, & M.C. Yip, “Semantic-SuPer: Employing Semantic Perception for Endoscopic Tissue Identification, Reconstruction, and Tracking,” in Workshop on Integrated Perception, Planning, and Control for Physically and Contextually-Aware Robot Autonomy @ IROS, 2023. [paper]

X. Liang, S. Lin, F. Liu, D. Schreiber, & M.C. Yip, “ORRN: An ODE-based Recursive Registration Network for Deformable Respiratory Motion Estimation With Lung 4DCT Images,” in IEEE Transactions on Biomedical Engineering, pp. 1-12, 2023. [paper][github]

S. Lin, A.J. Miao, J. Lu, S. Yu, Z.Y. Chiu, F. Richter, & M.C. Yip, “Semantic-SuPer: A Semantic-aware Surgical Perception Framework for Endoscopic Tissue Identification, Reconstruction, and Tracking,” in IEEE International Conference on Robotics and Automation (ICRA), pp. 4739-4746, 2023. [paper][github]

2022

F. Qin, S. Lin, & D. Xu, “Contour Primitive of Interest Extraction Network Based on Dual-Metric One-Shot Learning for Vision Measurement,” in IEEE Transactions on Industrial Informatics, vol. 19, no. 4, pp. 5839-5848, 2022. [paper]

Z. Yang, S. Lin, R. Simon, and C.A. Linte, “Endoscope Localization and Dense Surgical Scene Reconstruction for Stereo Endoscopy by Unsupervised Optical Flow and Kanade-Lucas-Tomasi Tracking,” in Annual International Conference of the IEEE Engineering in Medicine & Biology Society, pp. 4839-4842, 2022. [paper][github]

2021

S. Lin, “Vision-based Surgical Instrument Segmentation and Endoscopic Sinus Surgery Skill Assessment,” University of Washington Ph.D. Dissertation, 2021. [paper]

S. Lin, F. Qin, H. Peng, R.A. Bly, K.S. Moe, & B. Hannaford, “Multi-frame Feature Aggregation for Real-time Instrument Segmentation in Endoscopic Video,” in IEEE Robotics and Automation Letters, vol. 6, no. 4, pp. 6773-6780, 2021. [paper]

2020

S. Lin, F. Qin, Y. Li, R.A. Bly, K.S. Moe, & B. Hannaford, “LC-GAN: Image-to-Image Translation Based on Generative Adversarial Network for Endoscopic Images,” in International Conference on Intelligent Robots and Systems (IROS), pp. 2914-2920, 2020. [paper]

F. Qin, S. Lin, Y. Li, R.A. Bly, K.S. Moe, & B. Hannaford, “Towards Better Surgical Instrument Segmentation in Endoscopic Vision: Multi-angle Feature Aggregation and Contour Supervision,” in IEEE Robotics and Automation Letters, vol. 5, no. 4, pp. 6639-6646, 2020. [paper]

S. Lin, X. Gu, R.A. Bly, K.S. Moe, & B. Hannaford, “Video-based Automatic and Objective Endoscopic Sinus Surgery Skill Assessment,” in SPIE Medical Imaging 2020: Image-Guided Procedures, Robotic Interventions, and Modeling, vol. 11315, pp. 663-670, 2020. [paper]

2019

S. Lin, F. Qin, R.A. Bly, K.S. Moe, & B. Hannaford, “Automatic Sinus Surgery Skill Assessment Based on Instrument Segmentation and Tracking in Endoscopic Video,” in Workshop on Multiscale Multimodal Medical Imaging @ MICCAI, pp. 93-100, 2019. [paper]

2017

S. Lin, “Monitoring of Thermal Processes for Medical Applications Using Infrared Thermography,” Vanderbilt University M.S. Thesis, 2017. [paper]

S. Lin, L. Fichera, M.J. Fulton, & R.J. Webster III, “Don't Get Burned: Thermal Monitoring of Vessel Sealing Using a Miniature Infrared Camera,” in SPIE Medical Imaging 2017: Image-Guided Procedures, Robotic Interventions, and Modeling, vol. 10135, pp. 263-269, 2017. [paper]