Research Library

OP Lamp at OR-X

Scientific Evidence for Surgical Innovation

Our Research Library lists the scientific publications resulting from our research initiatives at the OR-X, many of which have appeared in leading international journals. It highlights the breadth of interdisciplinary work at the intersection of surgery, technology and data science, while also demonstrating how new methods and innovations are developed and validated under realistic clinical conditions. The collection illustrates the continuity of our research efforts and their contribution to advancing surgical standards, strengthening evidence-based innovation and supporting improved patient care.

2025

  • A Modular Edge Device Network for Surgery Digitalization

    Schorp, V., Giraud, F., Pargatzi, G., Waspe, M., von Ritter-Zahony, L., Wegmann, M., Cavalcanti, N., Henao Garcia, J., Bünger, N., Cachin, D., Caprara, S., Fürnstahl, P. & Carrillo, F.

    arXiv (2025)

    A modular Data Hub (DH) network is introduced to enable real-time data integration in the operating room, bridging medical sensors, imaging systems, and robotic tools. Built on NVIDIA Jetson Orin NX and connected via optical fiber, each DH supports multiple interfaces and containerized drivers, with centralized configuration and monitoring. An ultrasound-based 3D reconstruction experiment demonstrates the system’s potential for advancing data-driven surgical care.

    Read more

  • A novel augmented reality-based simulator for enhancing orthopedic surgical training

    Wu, L., Seibold, M., Cavalcanti, N., Hein, J., Gerth, T., Lekar, R., Hoch, A., Vlachopoulos, L., Grabner, H., Zingg, P., Farshad, M. & Fürnstahl, P.

    Computers in Biology and Medicine (2025)

    This study presents an AR-based simulator for Total Hip Arthroplasty (THA), reducing reliance on instructors. The simulator uses AR guidance and automated evaluation for self-paced training. Feasibility results showed mean deviation errors below 3 mm and 3 degrees, with no significant difference from manual assessment, demonstrating the potential of AR simulators to enhance orthopedic training efficiency and safety.

    Read more

  • Acquiring submillimeter-accurate multi-task vision datasets for computer-assisted orthopedic surgery

    Most, E., Hein, J., Giraud, F., Cavalcanti, N., Zingg, L., Brument, B., Louman, N., Carrillo, F., Fürnstahl, P. & Calvet, L.

    International Journal of Computer Assisted Radiology and Surgery (2025)

    This study presents an approach for generating realistic ex vivo datasets with 3D ground truth, tailored to optical image-based reconstruction and feature matching in open orthopedic surgery. By addressing the current lack of suitable data, it supports the development of applications such as marker-less surgical navigation and surgical digitization.

    Read more

  • ArthroPhase: a novel dataset and method for phase recognition inarthroscopic video

    Bahari Malayeri, A., Seibold, M., Cavalcanti, N., Hein, J., Jecklin, S., Vlachopoulos, L., Fucentese, S., Hodel, S. & Fürnstahl, P.

    Computer Assisted Surgery (2025)

    Surgical phase recognition in arthroscopy is advanced through the introduction of the first dedicated dataset (ACL27) and a transformer-based model. By leveraging spatio-temporal features, the method addresses challenges such as limited field of view, occlusions, and visual distortions, while a surgical progress index (sPi) enables procedure progression estimation. Results on ACL27 and Cholec80 confirm strong performance and generalizability, underlining the potential for improved training, real-time assistance, and efficiency in orthopedic surgery.

    Read more

  • Automatic Calibration of a Multi-Camera System with Limited Overlapping Fields of View for 3D Surgical Scene Reconstruction

    Flückiger, T., Hein, J., Fischer, V., Fürnstahl, P. & Calvet, L.

    International Journal of Computer Assisted Radiology and Surgery (2025)

    A novel automated calibration method is introduced for multi-camera systems in 3D surgical scene reconstruction, eliminating the need for manual intervention or specialized expertise. Using a ceiling-mounted projector to display multi-scale markers, the approach achieves accuracy comparable to manual methods while offering greater robustness under varying zoom levels. Validation on synthetic and real OR data highlights its potential to enable fully automated 3D-SSR.

    Read more

  • Automatic multi-view X-ray/CT registration using bone substructure contours

    Flepp, R., Nissen, L., Sigrist, B., Nieuwland, A., Cavalcanti, N., Fürnstahl, P., Dreher, T. & Calvet, L.

    International Journal of Computer Assisted Radiology and Surgery (2025)

    A novel multi-view X-ray/CT registration method is presented to improve intraoperative bone registration in orthopedic surgery. Unlike existing techniques, it is designed to achieve high accuracy and robustness without relying on manual key-point annotations, addressing key limitations in current surgical navigation approaches.

    Read more

  • Intra-, Epidural And Intracranial Pressure Changes During Interlaminar Endoscopy, With and Without Dural Tear

    Farshad, M., Schader, J., Stauffer, A., Zipser, C., Kheram, N., Spirig, J., Fasser, M., Widmer, J. & Hagel, V.

    Neurospine (2025)

    This study investigated the effect of irrigation fluid pressure during interlaminar endoscopic lumbar discectomy (IELD) on spinal intra-/epidural and intracranial pressures. Experiments on human cadavers showed a linear correlation between irrigation settings and pressure increases across spinal and intracranial levels. While pressures remained within safe ranges under normal conditions, outflow occlusion and the presence of a dural tear led to significantly higher values, highlighting important safety considerations for endoscopic spine surgery.

    Read more

  • IXGS—Intraoperative 3D Reconstruction from Sparse, Arbitrarily Posed Real X-rays

    Jecklin, S., Massalimova, A., Zha, R., Calvet, L., Laux, C., Farshad, M. & Fürnstahl, P.

    arXiv (2025)

    This work adapts Gaussian splatting to enable 3D spinal reconstruction from sparse and arbitrarily posed intraoperative X-rays. By introducing an anatomy-guided radiographic standardization step, the method improves visual consistency and reconstruction quality while requiring no pretraining, making it adaptable to new patients. Expert evaluation confirmed its clinical value for navigation, demonstrating the feasibility of instance-based volumetric reconstruction under real surgical conditions.

    Read more

  • UltraBoneUDF: Self-supervised Bone Surface Reconstruction from Ultrasound Based on Neural Unsigned Distance Functions

    Wu, L., Seibold, M., Cavalcanti, N., Loggia, G., Reissner, L., Sigirst, B., Hein., J., Calvet, L., Viehöfer, A. & Fürnstahl, P.

    arXiv (2025)

    UltraBoneUDF introduces a self-supervised framework for reconstructing open bone surfaces from ultrasound using neural unsigned distance functions. By fusing ultrasound-specific features and optimizing local surface geometry, the method overcomes limitations of partial bone capture in B-mode ultrasound. Extensive evaluation on multiple datasets shows substantial improvements over existing techniques, highlighting the potential of ultrasound-based 3D reconstruction for safer and more accessible orthopedic surgery.

    Read more

2024

  • Creating a Digital Twin of Spinal Surgery: A Proof of Concept

    Hein, J., Giraud, F., Calvet, L., Schwarz, A., Cavalcanti, N., Prokudin, S., Farshad, M., Tang, S., Pollefeys, M., Carrillo, F. & Fürnstahl, P.

    IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (2024)

    Surgical Digital Twins (SDTs) open new possibilities for training, surgical planning, and automation. This study presents a proof of concept for digitizing ex-vivo spinal surgery using advanced 3D reconstruction and tracking technologies. The high-quality results highlight the potential for future automated SDT generation.

    Read more

  • Domain adaptation strategies for 3D reconstruction of the lumbar spine using real fluoroscopy data

    Jecklin, S., Shen, Y., Gout, A, Suter, D., Calvet, L., Zingg, L., Straub, J., Cavalcanti, N., Farshad, M., Fürnstahl, P., Esfandiari, H.

    Medical Image Analysis (2024)

    Generating 3D spinal models from only a few intraoperative X-ray images can eliminate the need for conventional navigation systems. By bridging synthetic and real data with advanced deep learning, this approach moves toward accurate, real-time 3D reconstruction with promising implications for surgical planning, navigation, and robotics.

    Read more

  • Spatial context awareness in surgery through sound source localization

    Seibold, M., Bahari Malayeri, A., Fürnstahl, P.

    International Conference on Medical Image Computing and Computer Assisted Intervention – MICCAI (2024)

    In this study, the novel concept of Sound Source Localization (SSL) is introduced for surgery, enabling not only the detection but also the spatial mapping of acoustic activity in the operating field. Proof-of-concept experiments with an acoustic camera demonstrated the feasibility of using sound for object and keypoint detection in surgical tasks. These findings highlight SSL’s potential to advance surgical scene understanding and pave the way for multimodal sensing in future operating rooms.

    Read more

  • Spinal navigation with AI-driven 3D-reconstruction of fluoroscopy images: an ex-vivo feasibility study

    Luchmann, D., Jecklin, S., Cavalcanti, N.A., Laux, C., Massalimova, A., Esfandiari, H., Farshad, M., Fürnstahl, P.

    BMC Musculoskeletal Disorders (2024)

    With the increasing number of spinal instrumentation surgeries, 3D navigation seeks to improve implant accuracy. Yet, adoption has been limited by radiation exposure, costs, and workflow disruption. In this study, a new approach generates 3D spinal models from only a few intraoperative X-ray images, moving toward accurate, real-time reconstruction with potential benefits for surgical planning, navigation, and robotics.

    Read more

  • The journey of FAROS from technical design to in-vivo animal validation

    Cavalcanti, N., Carrillo, F., Li, R., van Assche, K., Davoodi, A., Tummers, M., Huber, M., Teyssere, F., Perez Velásquez, J., Massalimova, A., Laux, C., Sutter, R., Farshad, M., Borghesan, G., Denis, K., Morel, G., Chandanson, T., Vercauteren, T., Vander Poorten, E. & Fürnstahl P.

    MICCAI Conference on Medical Image Computing and Computer Assisted Invervention (2024)

    This study investigates the FAROS robotic system's ability to autonomously execute pedicle screw trajectories using 3D reconstructed ultrasound navigation. Results show that the system can achieve clinically acceptable accuracy, highlighting its potential for future robotic applications in surgery.

    Read more

  • Virtual reality for immersive education in orthopedic surgery digital twins

    Hein, J., Grunder, J., Calvet, L., Giraud, F., Cavalcanti, N., Carrillo, F., and Fürnstahl, P.

    IEEE International Symposium on Mixed and Augmented Reality Adjunct (2024)

    SurgTwinVR introduces a Virtual Reality application that immerses users in a Surgical Digital Twin, creating a high-fidelity replica of the entire operating room. Unlike existing VR or AR systems, it dynamically reproduces the surgical scene while optimized for real-time rendering. This approach highlights the potential of VR-based digital twins for surgical training and education.

    Read more

2023

  • Marker-less Multi-view 6DoF Pose Estimation of Surgical Instruments

    Hein, J., Cavalcanti, N., Suter, D., Zingg, L., Carrillo, F., Calvet, L., Farshad, M., Navab, N., Pollefeys, M. & Fürnstahl, P.

    Medical Image Analysis (2023)

    Deep learning-based image processing is transforming surgical navigation by enabling markerless tracking of instruments. This study explores the benefits of multi-view camera setups for highly accurate and occlusion-robust 6DoF pose estimation in surgery. The results demonstrate that markerless tracking is becoming a viable alternative to traditional marker-based systems, paving the way for improved surgical navigation.

  • Translation of medical AR research into clinical practice

    Seibold, M., Spirig, J., Esfandiari, H., Farshad, M., Fürnstahl, P.

    Journal of Imaging (2023)

    Medical Augmented Reality (AR) is beginning to make its way into patient care after decades of research. This concept paper details the translational pathway from clinical need to validation and approval, highlighting why many innovations remain prototypes. It also introduces the first guideline designed to support the successful transfer of medical AR research into clinical practice.