Showing papers by "Miguel Ángel González Ballester published in 2008"

Augmented reality endoscopic system (ARES): preliminary results

Abstract: During endoscopic surgery, it is difficult to ascertain the anatomical landmarks once the anatomy is fiddled with or if the operating area is filled with blood. An augmented reality system will enhance the endoscopic view and further enable surgeons to view hidden critical structures or the results of preoperative planning.

Calibration of a surgical microscope with automated zoom lenses using an active optical tracker.

Abstract: Background In this paper, we present a new method for the calibration of a microscope and its registration using an active optical tracker.

A method for frame-by-frame us to CT registration in a joint calibration and registration framework

Abstract: A method is presented for achieving robust joint calibration and registration in ultrasound (US) to CT registration for computer assisted orthopedic surgery. We propose using an effectively real-time frame- by-frame registration algorithm during US image acquisition. This approach provides more control to the surgeon, is more robust to initial conditions, and is computationally efficient. We then use the estimated registration of the frame-by-frame method to initialize a joint calibration and registration algorithm, and this is shown to produce over all more accurate and repeatable results. Experiments are performed using simulated US images of the lumbar vertebra and the distal femur as potential areas of interest for surgical applications.

A feasibility study of computer-assisted bone graft implantation for tissue-engineered replacement of the human ankle joint.

Abstract: Objective: Computer-assisted graft implantation may contribute to achieving biological joint replacement in the future. The purpose of this experimental study was to evaluate the feasibility and accuracy of a series of computer-assisted graft implantations into human cadaver ankle joints.Methods: Three-dimensional graft models of virtually planned corresponding tibial and talar defects were created from bovine cancellous bone. A platform for computer-assisted surgery (CAS) was set up to implant the grafts. Registration was performed by pair-point matching with anatomical landmarks. In the case of insufficient registration accuracy, artificial landmarks were used for registration. Eight grafts (four tibial, four talar) were implanted in four human cadaver ankle joints. Postoperative CT was used for outcome analysis. The following criteria of accuracy were defined: macroscopic quality of implant fit; quality of the sagittal and coronar joint surface; and quality of the undersurface of the graft in relation ...

Statistical Shape Space Analysis Based on Level Sets

Abstract: A framework for optimisation of specific criteria across the shape variability found in a population is proposed. The method is based on level set segmentation in the parametric space defined by Principal Component Analysis (PCA). The efficient narrow band evolution of the level set allows to search for the instances only in the neighborhood of the zero level set and not in the whole shape space. We are able to optimise any given criterion not to provide a single best fitting instance in the shape space, but rather to provide a group of instances that meet the criterion. This effectively defines a partition in the shape space, which can have any topology. The method works for data of any dimension, determined by the number of principal components retained. Results are shown on the application to shape analysis of human femora.

Evidence-based implant design using statistical bone model and automated implant fitting

Abstract: Introduction: A key in the development of better bone implant design is to consider the natural shape variability found in a certain population. Being able to characterize such shape variability, and how this variability can be injected in the process of implant design has become an important issue within implant manufacturers. Ultimately, the aim is to design an implant that can be used across a population ensuring a good fit. While it is clear that no unique implant will fit as well in every bone, it is possible however to tailor the implant design to be as generic a possible. Thus, an important aspect of the design is to evaluate how well the current bone implant fitting is performing before any further analysis. To asses the quality of the fitting one can search for the distances errors produced when placing the implant on the bone surface. However, current rigid registration strategies as the classical Iterative Closest Point (ICP) do not consider aspects like collision detection between objects nor include more specific constraints which can come from anatomical or manufacturer specific criteria. In this paper, a modified Iterative Closest Point (ICP) technique, tailored to the specific task of bone implant fitting was developed. Collision constraint was incorporated to ensure that no points in the implant mesh model fall inside the bone model. In addition, fitting guidelines provided by the implant manufacturer were included as fitting constraints, this in order to find plausible implant fitting. These specific constraints favors fittings of the implant that are collinear as much as possible with the bone main axis, and do not go above the bone plateau.

Sincerity in Simple and Complex Voting Mechanisms

Abstract: We discuss sincere voting when voters have cardinal preferences over alternatives. We interpret sincerity as opposed to strategic voting, and thus define sincerity as the optimal behavior when conditions to vote strategically diminish. When voting mechanisms allow for only one message type (simple voting mechanisms) we show that eliminating some conditions for strategic voting, individuals' optimal behavior coincides with an intuitive and common definition of sincerity. In order to obtain a precise definition of sincerity in voting mechanisms allowing for multiple message types (complex voting mechanisms) further restrictions on strategic voting are required. We illustrate our methodological approach using approval voting (AV) as a prime example of complex voting mechanisms for which no conclusive definition of sincerity exists in the literature.

Kalman Filtering for Frame-by-Frame CT to Ultrasound Rigid Registration

Abstract: This paper presents a method for CT-US rigid registration in minimally-invasive computer-assisted orthopaedic surgery, whereby the registration procedure is reformulated to enable effectively real-time registrations. A linear Kalman filter based algorithm is compared to an Unscented Kalman filter based method in simulated and experimental scenarios. The validation schemes demonstrate that the linear Kalman filter is more accurate, more robust, and converges quicker than the UKF, yielding an effectively real-time method for rigid registration applications, circumventing surgeons' waiting times.

Interpretability of anatomical variability analysis of abdominal organs via clusterization of decomposition modes

Abstract: Extensive recent work has taken place on the construction of probabilistic atlases of anatomical organs, especially the brain, and their application in medical image analysis. These techniques are leading the way into similar studies of other organs and more comprehensively of groups of organs. In this paper we report results on the analysis of anatomical variability obtained from probabilistic atlases of abdominal organs. Two factor analysis techniques, namely principal component analysis (PCA) and principal factor analysis (PFA), were used to decompose and study shape variability within the abdomen. To assess and ease the interpretability of the resulting deformation modes, a clustering technique of the deformation vectors is proposed. The analysis of deformation fields obtained using these two factor analysis techniques showed strong correlation with anatomical landmarks and known mechanical deformations in the abdomen, allowing us to conclude that PFA is a complementary decomposition technique that offers easy-to-interpret additional information to PCA in a clinical setting. The analysis of organ anatomical variability will represent a potentially important research tool for abdominal diagnosis and modeling.

An Integrated Approach for Reconstructing a Surface Model of the Proximal Femur from Sparse Input Data and a Multi-Level Point Distribution Model

Abstract: In this paper, we present an integrated approach using a multi-level point distribution model (ML-PDM) to reconstruct a patient-specific surface model of the proximal femur from intra-operatively available sparse data, which may consist of sparse point data or a limited number of calibrated fluoroscopic images. We conducted experiments on clinical datasets as well as on datasets from cadaveric bones. Our experimental results demonstrate promising accuracy of the present approach. Further extension to reconstructing a surface model from pre-operative biplanar X-ray radiographs is discussed.