Dynamic Structural Recovery Parameters Enhance Prediction of Visual Outcomes After Macular Hole Surgery
[40] Y. Zhao, Z. Zhao, R. Jiang, L. Sackewitz, Q. Liang, M. Maier, D. Zapp, P. C. Issa, and M. A. Nasseri, “Dynamic structural recovery parameters enhance prediction of visual outcomes after macular hole surgery,” Transl. Vis. Sci. Technol., vol. 14, no. 12, p. 29, 2025, doi: 10.1167/tvst.14.12.29.
Decoding the Surgical Scene: A Scoping Review of Scene Graphs in Surgery
[39] A. Henriques, K. Hoxha, D. Zapp, P. C. Issa, N. Navab, and M. A. Nasseri, “Decoding the surgical scene: A scoping review of scene graphs in surgery,” arXiv, Sept. 2025, arXiv:2509.20941.
UOPSL: Unpaired OCT Predilection Sites Learning for Fundus Image Diagnosis Augmentation
[38] Z. Zhao et al., “UOPSL: Unpaired OCT predilection sites learning for fundus image diagnosis augmentation,” arXiv, cs.CV, 2025.
CLAPS: A CLIP-Unified Auto-Prompt Segmentation for Multi-Modal Retinal Imaging
[37] Z. Zhao et al., “CLAPS: A CLIP-unified auto-prompt segmentation for multi-modal retinal imaging,” arXiv, Sept. 2025, arXiv:2509.08618.
Artificial Intelligence in Intraocular Robotic Microsurgery
[36] I. I. Iordachita, N. Navab, P. L. Gehlbach, M. Kobilarov, and M. A. Nasseri, “Artificial intelligence in intraocular robotic microsurgery,” in Artificial Intelligence in Surgery: Recent Advances and Future, Singapore: Springer Nature, 2025, pp. 127–149.
Needle Detection and Localisation for Robot-Assisted Subretinal Injection Using Deep Learning
[35] M. Zhou et al., “Needle detection and localisation for robot-assisted subretinal injection using deep learning,” CAAI Trans. Intell. Technol., vol. 10, no. 3, pp. 703–715, 2025, doi: 10.1049/cit2.12242.
Intraoperative Trocar-Based Eyeball Rotation Estimation Using Only 2D Microscope Images
[34] J. Yang et al., “Intraoperative trocar-based eyeball rotation estimation using only 2D microscope images,” in Proc. IEEE ICRA, Atlanta, GA, USA, 2025, pp. 4063–4069, doi: 10.1109/ICRA55743.2025.11127673.
Autonomous Continuous Capsulorhexis Based on a Force-Vision-Guided Robot System
[33] H. Liang, J. Liu, M. A. Nasseri, H. Lin, and K. Huang, “Autonomous continuous capsulorhexis based on a force-vision-guided robot system,” in Proc. IEEE ICRA, Atlanta, GA, USA, 2025, pp. 10474–10480, doi: 10.1109/ICRA55743.2025.11127235.
Real-Time Deformation-Aware Control for Autonomous Robotic Subretinal Injection Under iOCT Guidance
[32] D. Arikan et al., “Real-time deformation-aware control for autonomous robotic subretinal injection under iOCT guidance,” in Proc. IEEE ICRA, Atlanta, GA, USA, 2025, pp. 10531–10537, doi: 10.1109/ICRA55743.2025.11128595.
PAROS: Multi-Component Robotic System and an Image-Guided Patient Alignment for Robot-Assisted Ophthalmic Surgery
[31] A. Alikhani et al., “PAROS: Multi-component robotic system and an image-guided patient alignment for robot-assisted ophthalmic surgery,” IEEE Access, vol. 13, pp. 85056–85071, 2025, doi: 10.1109/ACCESS.2025.3564944.
Towards Motion Compensation in Autonomous Robotic Subretinal Injections
[30] D. Arikan et al., “Towards motion compensation in autonomous robotic subretinal injections,” in Proc. ISMR, Atlanta, GA, USA, 2025, pp. 66–72, doi: 10.1109/ISMR67322.2025.11025990.
Pre-Surgical Planner for Robot-Assisted Vitreoretinal Surgery: Integrating Eye Posture, Robot Position and Insertion Point
[29] S. Inagaki, A. Alikhani, N. Navab, P. C. Issa, and M. A. Nasseri, “Pre-surgical planner for robot-assisted vitreoretinal surgery: Integrating eye posture, robot position and insertion point,” arXiv, cs.RO, 2025.
Development of Teleoperated Robotic System for Remote Intraocular Microsurgery
[28] A. Xu et al., “Development of teleoperated robotic system for remote intraocular microsurgery,” Adv. Sci., 2025, Art. no. e09849, doi: 10.1002/advs.202509849.
KLDD: Kalman Filter Based Linear Deformable Diffusion Model in Retinal Image Segmentation
[27] Z. Zhao et al., “KLDD: Kalman filter based linear deformable diffusion model in retinal image segmentation,” in Proc. IEEE BIBM, Lisbon, Portugal, 2024, pp. 1763–1766, doi: 10.1109/BIBM62325.2024.10822342.
Extrapolating Prospective Glaucoma Fundus Images through Diffusion in Irregular Longitudinal Sequences
[26] Z. Zhao et al., "Extrapolating Prospective Glaucoma Fundus Images through Diffusion in Irregular Longitudinal Sequences," 2024 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), Lisbon, Portugal, 2024, pp. 4032-4035, doi: 10.1109/BIBM62325.2024.10822368.
KaLDeX: Kalman Filter Based Linear Deformable Cross Attention for Retina Vessel Segmentation
[25] Z. Zhao et al., “KaLDeX: Kalman filter based linear deformable cross attention for retina vessel segmentation,” arXiv, eess.IV, 2024.
An Online Rcm Adjusting System for Robot-Assisted Retinal Surgeries
[24] J. Xia et al., "An Online Rcm Adjusting System for Robot-Assisted Retinal Surgeries," 2024 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Abu Dhabi, United Arab Emirates, 2024, pp. 8385-8392, doi: 10.1109/IROS58592.2024.10802804.
Shadow Maintenance for Automatic Light-Probe Control in Ophthalmic Surgeries Using Only 2D information
[23] J. Yang et al., "Shadow Maintenance for Automatic Light-Probe Control in Ophthalmic Surgeries Using Only 2D information," 2024 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Abu Dhabi, United Arab Emirates, 2024, pp. 7220-7226, doi: 10.1109/IROS58592.2024.10802617.
Intraocular Reflection Modeling and Avoidance Planning in Image-Guided Ophthalmic Surgeries
[22] J. Yang et al., "Intraocular Reflection Modeling and Avoidance Planning in Image-Guided Ophthalmic Surgeries," 2024 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Abu Dhabi, United Arab Emirates, 2024, pp. 13183-13189, doi: 10.1109/IROS58592.2024.10801530.
AI-Based Fully Automatic Analysis of Retinal Vascular Morphology in Pediatric High Myopia
[21] Y. Zhao et al., “AI-based fully automatic analysis of retinal vascular morphology in pediatric high myopia,” BMC Ophthalmol., vol. 24, p. 415, 2024, doi: 10.1186/s12886-024-03682-5.
Nonlinear Swimming Magnetically Driven Microrobot Influenced by Pulsatile Blood Flow
[20] A. Parvareh, F. Ibrahimi, and M. A. Nasseri, “Nonlinear swimming magnetically driven microrobot influenced by a pulsatile blood flow through adaptive backstepping control,” Int. J. Dyn. Control, vol. 12, pp. 1839–1850, 2024, doi: 10.1007/s40435-023-01310-6.
Exploring the Needle Tip Interaction Force with Retinal Tissue Deformation in Vitreoretinal Surgery
[19] S. Pannek et al., "Exploring the Needle Tip Interaction Force with Retinal Tissue Deformation in Vitreoretinal Surgery," 2024 IEEE International Conference on Robotics and Automation (ICRA), Yokohama, Japan, 2024, pp. 16999-17005, doi: 10.1109/ICRA57147.2024.10610807.
Colibri5: Real-Time Monocular 5-DoF Trocar Pose Tracking for Robot-Assisted Vitreoretinal Surgery
[18] S. Dehghani et al., "Colibri5: Real-Time Monocular 5-DoF Trocar Pose Tracking for Robot-Assisted Vitreoretinal Surgery," 2024 IEEE International Conference on Robotics and Automation (ICRA), Yokohama, Japan, 2024, pp. 4547-4554, doi: 10.1109/ICRA57147.2024.10610576.
Analyzing Accessibility in Robot-Assisted Vitreoretinal Surgery: Integrating Eye Posture and Robot Position
[17] S. Inagaki, A. Alikhani, N. Navab, M. Maier and M. A. Nasseri, "Analyzing Accessibility in Robot-Assisted Vitreoretinal Surgery: Integrating Eye Posture and Robot Position," 2024 IEEE International Conference on Robotics and Automation (ICRA), Yokohama, Japan, 2024, pp. 9894-9900, doi: 10.1109/ICRA57147.2024.10611482.
Envibroscope: Real-Time Monitoring and Prediction of Environmental Motion for Enhancing Safety in Robot-Assisted Microsurgery
[16] A. Alikhani, S. Inagaki, S. Dehghani, M. Maier, N. Navab and M. A. Nasseri, "Envibroscope: Real-Time Monitoring and Prediction of Environmental Motion for Enhancing Safety in Robot-Assisted Microsurgery," 2024 IEEE International Conference on Robotics and Automation (ICRA), Yokohama, Japan, 2024, pp. 8202-8208, doi: 10.1109/ICRA57147.2024.10611207.
Shadow-Based 3D Pose Estimation of Intraocular Instrument Using Only 2D Images
[15] J. Yang, Z. Zhao, M. Maier, K. Huang, N. Navab and M. Ali Nasseri, "Shadow-Based 3D Pose Estimation of Intraocular Instrument Using Only 2D Images," 2024 IEEE International Conference on Robotics and Automation (ICRA), Yokohama, Japan, 2024, pp. 1323-1329, doi: 10.1109/ICRA57147.2024.10611011.
IC-RCM: Intraoperative real-time detection of 5D RCM-misalignment in robot-assisted ophthalmic surgeries with a single-camera system
[14] A. Alikhani, N. Fareghzadeh, S. Inagaki, M. Maier, N. Navab, and M. A. Nasseri, “IC-RCM: Intraoperative real-time detection of 5D RCM-misalignment in robot-assisted ophthalmic surgeries with a single-camera system,” in Proc. 10th Int. Conf. Electrical Engineering, Control and Robotics (EECR), Guangzhou, China, 2024, pp. 111–117, doi: 10.1109/EECR60807.2024.10607316.
Accelerated corneal cross-linking (18 mW/cm² for 5 min) with HPMC-riboflavin in progressive keratoconus—5 years follow-up
[13] J. Friedrich, A. Sandner, A. Nasseri, et al., “Accelerated corneal cross-linking (18 mW/cm² for 5 min) with HPMC-riboflavin in progressive keratoconus—5 years follow-up,” Graefes Arch. Clin. Exp. Ophthalmol., vol. 262, pp. 871–877, 2024, doi: 10.1007/s00417-023-06225-8.
EyeLS: Shadow-Guided Instrument Landing System for Target Approaching in Robotic Eye Surgery
[12] J. Yang et al., “EyeLS: Shadow-guided instrument landing system for target approaching in robotic eye surgery,” IEEE Robot. Autom. Lett., vol. 9, no. 4, pp. 3664–3671, Apr. 2024, doi: 10.1109/LRA.2024.3370000.
iOCT-Guided Simulated Subretinal Injections: A Comparison Between Manual and Robot-Assisted Techniques
[11] N. A. Maierhofer et al., “iOCT-guided simulated subretinal injections: A comparison between manual and robot-assisted techniques in an ex-vivo porcine model,” J. Robotic Surg., vol. 17, pp. 2735–2742, 2023, doi: 10.1007/s11701-023-01699-4.
Autonomous Clear Corneal Incision Guided by Force–Vision Fusion
[10] H. Liang, T. Wang, J. Xia, M. A. Nasseri, H. Lin and K. Huang, "Autonomous Clear Corneal Incision Guided by Force–Vision Fusion," in IEEE Transactions on Industrial Electronics, vol. 71, no. 8, pp. 9319-9327, Aug. 2024, doi: 10.1109/TIE.2023.3325586.
Label-Preserving Data Augmentation in Latent Space for Diabetic Retinopathy Recognition
[9] Z. Zhao et al., “Label-preserving data augmentation in latent space for diabetic retinopathy recognition,” in Proc. MICCAI, LNCS vol. 14222, Springer, 2023.
Semantic Virtual Shadows (SVS) for Improved Perception in 4D OCT Guided Surgery
[8] M. Sommersperger et al., “Semantic virtual shadows (SVS) for improved perception in 4D OCT guided surgery,” in Proc. MICCAI, LNCS vol. 14228, Springer, 2023.
Unobtrusive Biometric Data De-Identification of Fundus Images Using Latent Space Disentanglement
[7] Z. Zhao et al., “Unobtrusive biometric data de-identification of fundus images using latent space disentanglement,” Biomed. Opt. Express, vol. 14, pp. 5466–5483, 2023.
PKC-RCM: Preoperative Kinematic Calibration for Enhancing RCM Accuracy in Automatic Vitreoretinal Robotic Surgery
[6] A. Alikhani et al., “PKC-RCM: Preoperative kinematic calibration for enhancing RCM accuracy in automatic vitreoretinal robotic surgery,” IEEE Access, vol. 11, pp. 103616–103627, 2023, doi: 10.1109/ACCESS.2023.3316708.
RCIT: A Robust Catadioptric-based Instrument 3D Tracking Method For Microsurgical Instruments In a Single-Camera System
[5] A. Alikhani et al., "RCIT: A Robust Catadioptric-based Instrument 3D Tracking Method For Microsurgical Instruments In a Single-Camera System," 2023 45th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC), Sydney, Australia, 2023, pp. 1-5, doi: 10.1109/EMBC40787.2023.10340955.
Modelling and development of a mechanical eye for the evaluation of robotic systems for surgery
[4] K. Hoxha, A. Alikhani, S. Inagaki, M. Ferle, M. Maier, and M. A. Nasseri, “Modelling and development of a mechanical eye for the evaluation of robotic systems for surgery,” in Proc. 45th Annu. Int. Conf. IEEE Eng. Med. Biol. Soc. (EMBC), Sydney, Australia, 2023, pp. 1–4, doi: 10.1109/EMBC40787.2023.10340226.
Robotic Navigation Autonomy for Subretinal Injection via Intelligent Real-Time Virtual iOCT Volume Slicing
[3] S. Dehghani et al., “Robotic navigation autonomy for subretinal injection via intelligent real-time virtual iOCT volume slicing,” in Proc. IEEE ICRA, London, UK, 2023, pp. 4724–4731, doi: 10.1109/ICRA48891.2023.10160372.
Comparison of Robot-Assisted and Manual Cannula Insertion in Simulated Big-Bubble Deep Anterior Lamellar Keratoplasty
[2] Y. Zhao et al., “Comparison of robot-assisted and manual cannula insertion in simulated big-bubble deep anterior lamellar keratoplasty,” Micromachines, vol. 14, no. 6, p. 1261, 2023, doi: 10.3390/mi14061261.
Theoretical Error Analysis of Spotlight-Based Instrument Localization for Retinal Surgery
[1] M. Zhou et al., “Theoretical error analysis of spotlight-based instrument localization for retinal surgery,” Robotica, vol. 41, no. 5, pp. 1536–1549, 2023, doi: 10.1017/S0263574722001862.