System integration of a fluoroscopic image calibration using robot assisted surgical guidance for distal locking process in closed intramedullary nailing of femur

Distal locking procedure is one of the most complex tasks in close intramedullary nailing operation which requires fluoroscopic image to interpret 2-D distal locking position on image related to 3-D distal locking position on the patient site. Hence the surgeon has to perform the distal locking process by using multiple fluoroscopic images which causes a lot of x-ray exposure to the patient and surgeon and is a time consuming task. This paper presents the system integration of a fluoroscopic image calibration using robot assisted surgical guidance. The system integration consists of three parts; distal locking recovery, fluoroscopic calibration and tracking, and robot assisted surgical guidance. The distal locking-hole recovery algorithm is based on characteristic information of the major and minor axes of distal locking hole. The fluoroscopic calibration and tracking is modeled as pin-hole projection model to estimate a projection equation based on optical tracking system. The robot-assisted surgical guidance is developed to overlay a trajectory path using a laser beam for reducing the problem of hand – eye coordination on most surgical navigation system. We integrate each part to complete a surgical navigation system for distal locking process. The experiment of system integration is conducted to validate the accuracy of distal locking axis position and orientation. The results of the system integration shows a mean angular error of 1.10 and mean Euclidean distance in X-Y plane error of 3.65 mm

Digitally reconstructed wall radiographs

Master'sMASTER OF SCIENC

Visual Perception and Cognition in Image-Guided Intervention

Surgical image visualization and interaction systems can dramatically affect the efficacy and efficiency of surgical training, planning, and interventions. This is even more profound in the case of minimally-invasive surgery where restricted access to the operative field in conjunction with limited field of view necessitate a visualization medium to provide patient-specific information at any given moment. Unfortunately, little research has been devoted to studying human factors associated with medical image displays and the need for a robust, intuitive visualization and interaction interfaces has remained largely unfulfilled to this day. Failure to engineer efficient medical solutions and design intuitive visualization interfaces is argued to be one of the major barriers to the meaningful transfer of innovative technology to the operating room. This thesis was, therefore, motivated by the need to study various cognitive and perceptual aspects of human factors in surgical image visualization systems, to increase the efficiency and effectiveness of medical interfaces, and ultimately to improve patient outcomes. To this end, we chose four different minimally-invasive interventions in the realm of surgical training, planning, training for planning, and navigation: The first chapter involves the use of stereoendoscopes to reduce morbidity in endoscopic third ventriculostomy. The results of this study suggest that, compared with conventional endoscopes, the detection of the basilar artery on the surface of the third ventricle can be facilitated with the use of stereoendoscopes, increasing the safety of targeting in third ventriculostomy procedures. In the second chapter, a contour enhancement technique is described to improve preoperative planning of arteriovenous malformation interventions. The proposed method, particularly when combined with stereopsis, is shown to increase the speed and accuracy of understanding the spatial relationship between vascular structures. In the third chapter, an augmented-reality system is proposed to facilitate the training of planning brain tumour resection. The results of our user study indicate that the proposed system improves subjects\u27 performance, particularly novices\u27, in formulating the optimal point of entry and surgical path independent of the sensorimotor tasks performed. In the last chapter, the role of fully-immersive simulation environments on the surgeons\u27 non-technical skills to perform vertebroplasty procedure is investigated. Our results suggest that while training surgeons may increase their technical skills, the introduction of crisis scenarios significantly disturbs the performance, emphasizing the need of realistic simulation environments as part of training curriculum

Medical Image Analysis: Progress over two decades and the challenges ahead

International audienceThe analysis of medical images has been woven into the fabric of the pattern analysis and machine intelligence (PAMI) community since the earliest days of these Transactions. Initially, the efforts in this area were seen as applying pattern analysis and computer vision techniques to another interesting dataset. However, over the last two to three decades, the unique nature of the problems presented within this area of study have led to the development of a new discipline in its own right. Examples of these include: the types of image information that are acquired, the fully three-dimensional image data, the nonrigid nature of object motion and deformation, and the statistical variation of both the underlying normal and abnormal ground truth. In this paper, we look at progress in the field over the last 20 years and suggest some of the challenges that remain for the years to come

Development of a Rigid Body Forward Solution Physiological Model of the Lower Leg to Predict Non Implanted and Implanted Knee Kinematics and Kinetics

This dissertation describes the development and results of a physiological rigid body forward solution mathematical model that can be used to predict normal knee and total knee arthroplasty (TKA) kinematics and kinetics. The simulated activities include active extension and weight-bearing deep knee bend. The model includes both the patellofemoral and tibiofemoral joints. Geometry of the normal or implanted knee is represented by multivariate polynomials and modeled by constraining the velocity of lateral and medial tibiofemoral and patellofemoral contact points in a direction normal to the geometry surface. Center of mass, ligament and muscle attachment points and normal knee geometry were found using computer aided design (CAD) models built from computer tomography (CT) scans of a single subject. Quadriceps forces were the input for this model and were adjusted using a unique controller to control the rate of flexion, embedded with a controller which stabilizes the patellofemoral joint. The model was developed first using normal knee parameters. Once the normal knee model was validated, different total knee arthroplasty (TKA) designs were virtually implanted. The model was validated using in vivo data obtained through fluoroscopic analysis. In vivo data of the extension and deep knee bend activities from five non-implanted knees were used to validate the normal model kinematics. In vivo kinematic and kinetic data from a telemetric TKA with a tibia component instrumented with strain gauges was used to validate the kinematic and kinetic results of the model implanted with the TKA geometry. The tibiofemoral contact movement matched the trend seen in the in vivo data from the one patient available with this implant. The maximum axial tibiofemoral force calculated with the model was in 3.1% error with the maximum force seen in the in vivo data, and the trend of the contact forces matched well. Several other TKA designs were virtually implanted and analyzed to determine kinematics and bearing surface kinetics. The comparison between the model results and those previously assessed under in vivo conditions validates the effectiveness of the model and proves that it can be used to predict the in vivo kinematic and kinetic behavior of a TKA