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C. Lai

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Authored

Using a Guidance Virtual Fixture on a Soft Robot to Improve Ureteroscopy Procedures in a Phantom

Journal article (2024) - C. Lai, C. Lai, Elena De Momi, Giancarlo Ferrigno, J. Dankelman

Manipulating a flexible ureteroscope is difficult, due to its bendable body and hand–eye coordination problems, especially when exploring the lower pole of the kidney. Though robotic interventions have been adopted in various clinical scenarios, they are rarely used in ureterosco ...

Autonomous Intraluminal Navigation of a Soft Robot using Deep-Learning-based Visual Servoing

Conference paper (2022) - J. F. Lazo, J. F. Lazo, C. Lai, C. Lai, S. Moccia, S. Moccia, B. Rosa, M. Catellani, M. de Mathelin, G. Ferrigno, P. Breedveld, J. Dankelman, Elena De Momi

Navigation inside luminal organs is an arduous task that requires non-intuitive coordination between the movement of the operator's hand and the information obtained from the endoscopic video. The development of tools to automate certain tasks could alleviate the physical and men ...

Design of an Affordable, Modular Implant Device for Soft Tissue Tension Assessment and Range of Motion Tracking During Total Hip Arthroplasty

Journal article (2022) - J.C. Wei, Bryan Blaauw, D.G.M. van der Pol, M. Cruz Saldivar, C. Lai, J. Dankelman, T. Horeman

Background: In hip arthroplasties, surgeons rely on their experience to assess the stability and balance of hip tissues when fitting the implant to their patients. During the operation, surgeons use a modular, temporary set of implants to feel the tension in the surrounding soft tissues and adjust the implant configuration. This process is naturally subjective and therefore depends on the operator. Inexperienced surgeons undertaking hip arthroplasties are twice as likely to experience errors than their experienced colleagues, leading to dislocations, pain and discomfort for the patients. Methods: To address this issue, a new, 3DOF force measurement system was developed and integrated into the modular, trial implants that can quantify forces and movements intraoperatively in 3D. The prototypes were evaluated in three post-mortem human specimens (PMHSs), to provide surgeons with objective data to help determine the optimal implant fit and configuration. The devices comprise a deformable polymer material providing strain-based displacements measured with electromagnetic-based sensors and an inertial measurement unit (IMU) for motion data. Results: Device results show a relative accuracy of approx. 2% and a sensitivity of approx. 1%. PMHS results indicated that soft tissue forces on the hip joint peak in the order of ~100 N and trend with positions of the leg during range of motion (ROM) tests, although force patterns differ between each PMHS. Conclusion: By monitoring forces and force patterns of hip soft tissues, in combination with standardised ROM tests, the force patterns could shed a light on potential anomalies that can be addressed during surgery. Clinical and Translational Impact Statement: The development of an instrumented hip implant device for use during surgery knowledge will eventually allow us to develop a predictive model for soft tissue balancing, that can be used for pre- and intra-operative planning for each patient on a tailored and personalised basis. Ultimately, we hope that with this device, patients will benefit from a faster recovery, from a more-precisely fitted hip, and an improved quality of life.@en

Contact Localization of Continuum and Flexible Robot Using Data-driven Approach

Journal article (2022) - Xuan Thao Ha, Xuan Thao Ha, D. Wu, D. Wu, C. Lai, C. Lai, Mouloud Ourak, Gianni Borghesan, Arianna Menciassi, Emmanuel Vander Poorten

Continuum robots such as robotic catheters are increasingly being used in minimally invasive surgery. Compliance contributes to enhanced safety during e.g. catheter insertion, however, estimation of contact force and location may help clinicians avoiding exerting excessive for ...

Contributed

Image-matching based navigation system for robotic ureteroscopy in kidney exploration

Master thesis (2022) - Z. Huang, C. Lai, J. Dankelman, C. Della Santina

Kidney stone disease has become the most common disease of the urinary tract. Flexible ureteroscopy (fURS) is one of the methods to perform diagnosis or treatment for the stones inside the kidney. However, because of the complex structure inside the kidney with multiple calyxes and the limitation of the ureteroscope, surgeons find it difficult to know which calyx is being observed and where the ureteroscope tip actually reaches during the ureteroscopy procedure by only using the ureteroscope camera views. To solve this problem, this thesis proposed an image-matching-based navigation system for robotic ureteroscopy in kidney exploration. The system consists of two parts: pre-operation and post-operation. During pre-operation, the virtual ureteroscopy (VURS) environment is rendered from the 3D kidney model, which is generated from computed tomography (CT) scan data. The VURS images of calyxes inside the kidney are collected and then processed to perform edge feature extraction as the matching virtual image database (VID). In post-operation, real calyx images (RCIs) are collected. For each RCI, image processing is used, and its edge features are extracted as the matching input. By performing the matching algorithm between edge features of the RCI and the VID, the best matching result image in the VID can be found according to the RCI. Then the location of the ureteroscope can be shown in the virtual ureteroscopy environment. This thesis uses an open source kidney model to replace the data from CT scans due to resource limitations. Unity software is used to generate the VURS. The VID is collected manually. A robotic ureteroscope prototype and a 3D-printing kidney phantom based on the open source kidney model are used to simulate the fURS procedure to get RCIs. After applying image processing techniques to RCIs, the shape context (SC) matching method is used to find the best matching image from the VID. The results are validated by the EMT system. The whole system is validated through both simulation images and the experiment. The successful rate of matching the simulation images is 92%, while it reduces to 62.5% when matching the RCIs. This performance difference is caused by the poor image quality of RCIs, which can be improved by selecting a more suitable light source and a digital camera.