Simultaneous State and Parameter Estimation for Physics-Based Tracking of Heart Surface Motion

Most existing approaches for tracking of the beating heart motion assume known cardiac kinematics and material parameters. However, these assumptions are not realistic for application in beating heart surgery. In this paper, a novel probabilistic tracking approach based on a physical model of the heart surface is presented. In contrast to existing approaches, the physical information about heart kinematics and material properties is incorporated and considered in an estimation of the heart behavior. An additional advantage is that the time-dependencies and uncertainties of the heart parameters are efficiently handled by exploiting simultaneous state and parameter estimation. Furthermore, by decomposing the state into linear and nonlinear substructures, the computational complexity of the estimation problem is reduced. The experimental results demonstrate the high performance of the method proposed in this paper. The solution of the parameter identification problem allows a personalized physical model and opens up possibilities to apply the physics-based tracking of the heart surface motion in a clinical environment

Physics-Based Probabilistic Motion Compensation of Elastically Deformable Objects

A predictive tracking approach and a novel method for visual motion compensation are introduced, which accurately reconstruct and compensate the deformation of the elastic object, even in the case of complete measurement information loss. The core of the methods involves a probabilistic physical model of the object, from which all other mathematical models are systematically derived. Due to flexible adaptation of the models, the balance between their complexity and their accuracy is achieved

Efficient Physics-Based Tracking of Heart Surface Motion for Beating Heart Surgery Robotic Systems

Purpose: Tracking of beating heart motion in a robotic surgery system is required for complex cardiovascular interventions. Methods: A heart surface motion tracking method is developed, including a stochastic physics-based heart surface model and an efficient reconstruction algorithm. The algorithm uses the constraints provided by the model that exploits the physical characteristics of the heart. The main advantage of the model is that it is more realistic than most standard heartmodels. Additionally, no explicit matching between the measurements and the model is required. The application of meshless methods significantly reduces the complexity of physics-based tracking. Results: Based on the stochastic physical model of the heart surface, this approach considers the motion of the intervention area and is robust to occlusions and reflections. The tracking algorithm is evaluated in simulations and experiments on an artificial heart. Providing higher accuracy than the standardmodel-based methods, it successfully copes with occlusions and provides high performance even when all measurements are not available. Conclusions: Combining the physical and stochastic description of the heart surface motion ensures physically correct and accurate prediction. Automatic initialization of the physics-based cardiac motion tracking enables system evaluation in a clinical environment

Aerospace medicine and biology: A continuing bibliography with indexes, supplement 204

This bibliography lists 140 reports, articles, and other documents introduced into the NASA scientific and technical information system in February 1980

Adaptive Model-Based Visual Stabilization of Image Sequences Using Feedback

Visual stabilization proposed in this paper compensates changes of the scene caused by motion and deformation of an observed object. This is of high importance in computer-assisted beating heart surgery, where the views of the beating heart should be stabilized. The proposed model-based method defines visual stabilization as a transformation of the current image sequence to a stabilized image sequence. This transformation incorporates physical model of the observed object and model of the measurement process. In contrast to standard approaches, the quality of the visual stabilization is continuously evaluated and improved in two aspects. On the one hand, discretization errors are reduced. On the other hand, the parameters of the underlying models are adjusted. The performance of the proposed method is evaluated in an experiment with a pressure-regulated artificial heart. Compared with standard methods, the model-based method provides higher accuracy, which is additionally improved by a feedback mechanism

Coronary Artery Segmentation and Motion Modelling

Conventional coronary artery bypass surgery requires invasive sternotomy and the use of a cardiopulmonary bypass, which leads to long recovery period and has high infectious potential. Totally endoscopic coronary artery bypass (TECAB) surgery based on image guided robotic surgical approaches have been developed to allow the clinicians to conduct the bypass surgery off-pump with only three pin holes incisions in the chest cavity, through which two robotic arms and one stereo endoscopic camera are inserted. However, the restricted field of view of the stereo endoscopic images leads to possible vessel misidentification and coronary artery mis-localization. This results in 20-30% conversion rates from TECAB surgery to the conventional approach. We have constructed patient-specific 3D + time coronary artery and left ventricle motion models from preoperative 4D Computed Tomography Angiography (CTA) scans. Through temporally and spatially aligning this model with the intraoperative endoscopic views of the patient's beating heart, this work assists the surgeon to identify and locate the correct coronaries during the TECAB precedures. Thus this work has the prospect of reducing the conversion rate from TECAB to conventional coronary bypass procedures. This thesis mainly focus on designing segmentation and motion tracking methods of the coronary arteries in order to build pre-operative patient-specific motion models. Various vessel centreline extraction and lumen segmentation algorithms are presented, including intensity based approaches, geometric model matching method and morphology-based method. A probabilistic atlas of the coronary arteries is formed from a group of subjects to facilitate the vascular segmentation and registration procedures. Non-rigid registration framework based on a free-form deformation model and multi-level multi-channel large deformation diffeomorphic metric mapping are proposed to track the coronary motion. The methods are applied to 4D CTA images acquired from various groups of patients and quantitatively evaluated

Aerospace Medicine and Biology: A continuing supplement 180, May 1978

This special bibliography lists 201 reports, articles, and other documents introduced into the NASA scientific and technical information system in April 1978

Characterization and Compensation of Hysteretic Cardiac Respiratory Motion in Myocardial Perfusion Studies Through MRI Investigations

Respiratory motion causes artifacts and blurring of cardiac structures in reconstructed images of SPECT and PET cardiac studies. Hysteresis in respiratory motion causes the organs to move in distinct paths during inspiration and expiration. Current respiratory motion correction methods use a signal generated by tracking the motion of the abdomen during respiration to bin list- mode data as a function of the magnitude of this respiratory signal. They thereby fail to account for hysteretic motion. The goal of this research was to demonstrate the effects of hysteretic respiratory motion and the importance of its correction for different medical imaging techniques particularly SPECT and PET. This study describes a novel approach for detecting and correcting hysteresis in clinical SPECT and PET studies. From the combined use of MRI and a synchronized Visual Tracking System (VTS) in volunteers we developed hysteretic modeling using the Bouc-Wen model with inputs from measurements of both chest and abdomen respiratory motion. With the MRI determined heart motion as the truth in the volunteer studies we determined the Bouc Wen model could match the behavior over a range of hysteretic cycles. The proposed approach was validated through phantom simulations and applied to clinical SPECT studies