Analysis of Image Sequence Data with Applications to Two-Dimensional Echocardiography

Digital two-dimensional echocardiography is an ultrasonic imaging technique that is used as an increasingly important noninvasive technique in the comprehensive characterization of the left ventricular structure and function. Quantitative analysis often uses heart wall motion and other shape attributes such as the heart wall thickness, heart chamber area, and the variation of these attributes throughout the cardiac cycle. These analyses require the complete determination of the heart wall boundaries. Poor image quality and large amount of noise makes computer detection of the boundaries difficult. An algorithm to detect both the inner and outer heart wall boundaries is presented. The algorithm was applied to images acquired from animal studies and from a tissue equivalent phantom to verify the performance. Different approaches to exploiting the temporal redundancy of the image data without making use of results from image segmentation and scene interpretation are explored. A new approach to perform image flow analysis is developed based on the Total Least Squares method. The result of this processing is an estimate of the velocities in the image plane. In an image understanding system, information acquired from related domains by other sensors are often useful to the analysis of images. Electrocardiogram signals measure the change of electrical potential changes in the heart muscle an d provide important information such as the timing data for image sequence analysis. These signals are frequently plagued by impulsive muscle noise and background drift due to patient movement. A new approach to solving these problems is presented using mathematical morphology. Experiments addressing various aspects of the problem, such as algorithm performance, choice of operator parameters, and response to sinusoidal inputs, are reported

Tree-Structured Nonlinear Adaptive Signal Processing

In communication systems, nonlinear adaptive filtering has become increasingly popular in a variety of applications such as channel equalization, echo cancellation and speech coding. However, existing nonlinear adaptive filters such as polynomial (truncated Volterra series) filters and multilayer perceptrons suffer from a number of problems. First, although high Order polynomials can approximate complex nonlinearities, they also train very slowly. Second, there is no systematic and efficient way to select their structure. As for multilayer perceptrons, they have a very complicated structure and train extremely slowly Motivated by the success of classification and regression trees on difficult nonlinear and nonparametfic problems, we propose the idea of a tree-structured piecewise linear adaptive filter. In the proposed method each node in a tree is associated with a linear filter restricted to a polygonal domain, and this is done in such a way that each pruned subtree is associated with a piecewise linear filter. A training sequence is used to adaptively update the filter coefficients and domains at each node, and to select the best pruned subtree and the corresponding piecewise linear filter. The tree structured approach offers several advantages. First, it makes use of standard linear adaptive filtering techniques at each node to find the corresponding Conditional linear filter. Second, it allows for efficient selection of the subtree and the corresponding piecewise linear filter of appropriate complexity. Overall, the approach is computationally efficient and conceptually simple. The tree-structured piecewise linear adaptive filter bears some similarity to classification and regression trees. But it is actually quite different from a classification and regression tree. Here the terminal nodes are not just assigned a region and a class label or a regression value, but rather represent: a linear filter with restricted domain, It is also different in that classification and regression trees are determined in a batch mode offline, whereas the tree-structured adaptive filter is determined recursively in real-time. We first develop the specific structure of a tree-structured piecewise linear adaptive filter and derive a stochastic gradient-based training algorithm. We then carry out a rigorous convergence analysis of the proposed training algorithm for the tree-structured filter. Here we show the mean-square convergence of the adaptively trained tree-structured piecewise linear filter to the optimal tree-structured piecewise linear filter. Same new techniques are developed for analyzing stochastic gradient algorithms with fixed gains and (nonstandard) dependent data. Finally, numerical experiments are performed to show the computational and performance advantages of the tree-structured piecewise linear filter over linear and polynomial filters for equalization of high frequency channels with severe intersymbol interference, echo cancellation in telephone networks and predictive coding of speech signals

A Subject-Specific EMG-Driven Musculoskeletal Model for the Estimation of Moments in Ankle Plantar-Dorsiflexion Movement

In traditional rehabilitation process, ankle movement ability is only qualitatively estimated by its motion performance, however, its movement is actually achieved by the forces acting on the joints produced by muscles contraction. In this paper, the musculoskeletal model is introduced to provide a more physiologic method for quantitative muscle forces and muscle moments estimation during rehabilitation. This paper focuses on the modeling method of musculoskeletal model using electromyography (EMG) and angle signals for ankle plantar-dorsiflexion (P-DF) which is very important in gait rehabilitation and foot prosthesis control. Due to the skeletal morphology differences among people, a subject-specific geometry model is proposed to realize the estimation of muscle lengths and muscle contraction force arms. Based on the principle of forward and inverse dynamics, difference evolutionary (DE) algorithm is used to adjust individual parameters of the whole model, realizing subject-specific parameters optimization. Results from five healthy subjects show the inverse dynamics joint moments are well predicted with an average correlation coefficient of 94.21% and the normalized RMSE of 12.17%. The proposed model provides a good way to estimate muscle moments during movement tasks

Simulated Space Radiation and Weightlessness: Vascular-Bone Coupling Mechanisms to Preserve Skeletal Health

Weightlessness causes a cephalad fluid shift and reduction in mechanical stimulation, adversely affecting both cortical and trabecular bone tissue in astronauts. In rodent models of weightlessness, the onset of bone loss correlates with reduced skeletal perfusion, reduced and rarified vasculature and lessened vasodilation, which resembles blood-bone symbiotic events that can occur with fracture repair and aging. These are especially serious risks for long term, exploration class missions when astronauts will face the challenge of increased exposure to space radiation and abrupt transitions between different gravity environments upon arrival and return. Previously, we found using the mouse hindlimb unloading model and exposure to heavy ion radiation, both disuse and irradiation cause an acute bone loss that was associated with a reduced capacity to produce bone-forming osteoblasts from the bone marrow. Together, these findings led us to hypothesize that exposure to space radiation exacerbates weightlessness-induced bone loss and impairs recovery upon return, and that treatment with anti-oxidants may mitigate these effects. The specific aims of this recently awarded grant are to: AIM 1 Determine the functional and structural consequences of prolonged weightlessness and space radiation (simulated spaceflight) for bone and skeletal vasculature in the context of bone cell function and oxidative stress. AIM 2 Determine the extent to which an anti-oxidant protects against weightlessness and space radiation-induced bone loss and vascular dysfunction. AIM 3 Determine how space radiation influences later skeletal and vasculature recovery from prolonged weightlessness and the potential of anti-oxidants to preserve adaptive remodeling

Model for an Intelligent Operating System for Executing Tasks on a Reconfigurable Parallel Architecture

Parallel processing is one approach to achieve the large computational processing capabilities required by many real-time computing tasks. One of the problems that must be addressed in the use of reconfigurable multiprocessor systems is matching the architecture configuration to the algorithms to be executed. This paper presents a conceptual model that explores the potential of artificial intelligence tools, specifically expert systems, to design an Intelligent Operating System for multiprocessor systems. The target task is the implementation of image understanding systems on multiprocessor architectures. PASM is used as an example multiprocessor. The Intelligent Operating System concepts developed here could also be used to address other problems requiring real-time processing. An example image understanding task is presented to illustrate the concept of intelligent scheduling by the Intelligent Operating System. Also considered is the use of the conceptual model when developing an image understanding system in order to test different strategies for choosing algorithms, imposing execution order constraints, and integrating results from various algorithms

Oxidative Stress Responses to Simulated Spaceflight in Mineralized and Marrow Compartments of Bone and Associated Vasculature

Long-term spaceflight causes profound changes to the musculoskeletal system attributable to unloading and fluid shifts in microgravity. Future space explorations beyond the earths magnetosphere will expose astronauts to space radiation, which may cause additional skeletal deficits that are not yet fully understood. Our long-term goals are twofold: to define the mechanisms and risk of bone loss in the spaceflight environment and to facilitate the development of effective countermeasures if necessary. Our central hypothesis is that oxidative stress plays a key role in progressive bone loss and vascular dysfunction caused by spaceflight. In animals models, overproduction of free radicals is associated with increased bone resorption, lower bone formation, and decrements in bone mineral density and structure which can ultimately lead to skeletal fragility. Evidence in support of a possible causative role for oxidative stress in spaceflight-induced bone loss derive from knockout and transgenic mouse studies and the use of pharmacological interventions with known anti-oxidant properties. In our studies to simulate spaceflight, 16-wk old, male C56Bl/6J mice were assigned to one of four groups: hind limb unloading to simulate weightlessness (HU), normally loaded Controls (NL) (sham irradiated, no hind limb unloading), irradiated at NASA Space Radiation Laboratory IR with 1-2Gy of (600MeV/n) alone, or in combination with protons (0.5Gy Protons/0.5Gy 56Fe), (IR) or both hind limb unloaded and irradiated, HU+IR. Mice were exposed to radiation 3 days after initiating HU and tissues harvested were 1-14 days after initiating treatments for analyses. Results from our laboratories, which employ various biochemical, gene expression, functional, and transgenic animal model methods, implicate dynamic regulation of redox-related pathways by spaceflight-related environmental factors. As one example, we found that combined HU and radiation exposure caused oxidative damage in skeletal tissues (lipid peroxidation) of wildtype mice, whereas bone from transgenic mice that overexpress human catalase in mitochondria were protected. Interestingly, marrow cells grown under culture conditions that select for endothelial progenitor cells (EPC), showed that HU but not IR reduced EPC cell migration; in contrast HU and IR each inhibited growth of marrow-derived osteoblast progenitors. Taken together, these results indicate that unloading and ionizing elicit distinct effects on progenitor and mature cells of vascular and skeletal tissue, and that oxidative damage may contribute to skeletal and vascular deficits that may emerge during extended space travel