Research on real-time physics-based deformation for haptic-enabled medical simulation

This study developed a multiple effective visuo-haptic surgical engine to handle a variety of surgical manipulations in real-time. Soft tissue models are based on biomechanical experiment and continuum mechanics for greater accuracy. Such models will increase the realism of future training systems and the VR/AR/MR implementations for the operating room

A high-immersive medical training platform using direct intraoperative data

The virtual training of primitive surgical procedures has been widely recognized as immersive and effective to medical education. Virtual basic surgical training framework integrated with multi-sensations rendering has been recognized as one of the most immersive implementations in medical education. Yet, compared with the original intraoperative data, there has always been an argument on the lower fidelity these data are represented in virtual surgical training. In this paper, a solution is proposed to achieve better training immersion by incorporating multiple higher-fidelity factors toward a trainee\u27s sensations (vision, touch, and hearing) during virtual training sessions. This was based on the proposal of a three-tier model to classify reasons leading to fidelity issues. This include: haptic factors, such as high-quality fitting of force models based on surgical data acquisition, the use of actual surgical instrument linked to desktop haptic devices; visual factors, such as patient-specific CT images segmentation and reconstruction from the original medical data; and hearing factors, such as variations of the sound of monitoring systems in the theatre under different surgical conditions. Twenty seven urologists comprising 18 novices and 9 professors were invited to test a virtual training system based on the proposed solution. Post-test values from both professors\u27 and novices\u27 groups demonstrated obvious improvements in comparison with pre-test values under both the subjective and objective criteria, the fitting rate of the whole puncture processing is 99.93%. Both the subjective and objective results demonstrated a higher performance than the existing benchmark training platform. Combining these in a systematic approach, tuned with specific fidelity requirements, haptically enabled training simulation systems would be able to provide a more immersive and effective training environment

Development and validation of a hybrid surgical simulator for ultrasound guided laparoscopic common bile duct exploration

This thesis investigates using 3D printing for developing a low-cost, quick, and simple fabrication method for the surgical simulation of the basic skills needed in a laparoscopic common bile duct exploration using ultrasound. This is achieved through a human-centred design methodology where each step of the development is guided by interactions or evaluations with the end users. The specifications are defined by using interviews to understand the needs of surgeons in a simulation practice and to characterise the experience of performing surgery, including the embodied knowledge of surgeons when they manipulate soft tissues. Using an action research methodology combining qualitative and quantitative evaluations in an iterative process, commonly used materials in simulation are thoroughly investigated to identify the most suitable synthetic materials for each type of soft tissue. The synthetic materials identified are silicones because of their tactile properties; moreover, two augmented reality techniques are implemented in addition to the physical model. The first one is style transfer, which aims to improve the appearance of the physical simulator when it is viewed through the laparoscopic camera. The style transfer algorithm used during this research can successfully modify the appearance of the simulator to replicate the diversity of real life. The second technique is marker tracking, which is used to simulate the laparoscopic ultrasound step by overlaying pre-recorded ultrasound images onto the physical model. This technique allows surgeons to practice reading laparoscopic ultrasound images and identifying key anatomical features during the surgery. Through consultations with the surgeons, the outcomes of this research are evaluated using face, content, and construct validations. Throughout this thesis, the research methods and results are explained and discussed to provide a basis for further research. These findings can be used as a framework for future development of surgical simulators