We develop efficient techniques for the non-rigid registration of medical images by using representations that adapt to the anatomy found in such images. Images of anatomical structures typically have uniform intensity interiors and smooth boundaries. We create methods to represent such regions compactly using tetrahedra. Unlike voxel-based representations, tetrahedra can accurately describe the expected smooth surfaces of medical objects. Furthermore, the interior of such objects can be represented using a small number of tetrahedra. Rather than describing a medical object using tens of thousands of voxels, our representations generally contain only a few thousand elements. Tetrahedra facilitate the creation of efficient non-rigid registration algorithms based on finite element methods (FEM). We create a fast, FEM-based method to non-rigidly register segmented anatomical structures from two subjects. Using our compact tetrahedral representations, this method generally requires less than one minute of processing time on a desktop PC. We also create a novel method for the non-rigid registration of gray scale images. To facilitate a fast method, we create a tetrahedral representation of a displacement field that automatically adapts to both the anatomy in an image and to the displacement field. The resulting algorithm has a computational cost that is dominated by the number of nodes in the mesh (about 10,000), rather than the number of voxels in an image (nearly 10,000,000). For many non-rigid registration problems, we can find a transformation from one image to another in five minutes. This speed is important as it allows use of the algorithm during surgery. We apply our algorithms to find correlations between the shape of anatomical structures and the presence of schizophrenia. We show that a study based on our representations outperforms studies based on other representations. We also use the results of our non-rigid registration algorithm as the basis of a segmentation algorithm. That algorithm also outperforms other methods in our tests, producing smoother segmentations and more accurately reproducing manual segmentations.

Radiotherapy is a potential curative option for liver cancer; however, respiratory motion creates uncertainty in treatment delivery. Advances in imaging and registration techniques can provide information regarding changes in respiratory motion. Currently image registration is challenged by computation and manual intervention. A Navigator Channel (NC) technique was developed to overcome these limitations. A population motion model was generated to predict patient-specific motion, while a point motion detection technique was developed to calculate the patient-specific liver edge motion from images. An adaptation technique uses the relative difference between the population and patient calculated liver edge motion to determine the patient's liver volume motion. The NC technique was tested on patient 4D-CT images for initial validation to determine the accuracy. Accuracy was less than 0.10 mm in liver edge detection and approximately 0.25 cm in predicting patient-specific motion. This technique can be used to ensure accurate treatment delivery for liver radiotherapy.

Radiotherapy is a potential curative option for liver cancer; however, respiratory motion creates uncertainty in treatment delivery. Advances in imaging and registration techniques can provide information regarding changes in respiratory motion. Currently image registration is challenged by computation and manual intervention. A Navigator Channel (NC) technique was developed to overcome these limitations. A population motion model was generated to predict patient-specific motion, while a point motion detection technique was developed to calculate the patient-specific liver edge motion from images. An adaptation technique uses the relative difference between the population and patient calculated liver edge motion to determine the patient's liver volume motion. The NC technique was tested on patient 4D-CT images for initial validation to determine the accuracy. Accuracy was less than 0.10 mm in liver edge detection and approximately 0.25 cm in predicting patient-specific motion. This technique can be used to ensure accurate treatment delivery for liver radiotherapy.

It is well known that biological structures such as human brains, although may contain the same global structures, differ in shape, orientation, and fine structures across individuals and at different times. Such variabilities during registration are usually represented by nonrigid transformations. This research seeks to address this issue by developing physically based models in which transformations are constructed to obey certain physical laws. <br /><br /> In this thesis, a novel registration technique is presented based on the physical behavior of particles. Regarding the image as a particle system without mutual interaction, we simulate the registration process by a set of free particles moving toward the target positions under applied forces. The resulting partial differential equations are a nonlinear hyperbolic system whose solution describes the spatial transformation between the images to be registered. They can be numerically solved using finite difference methods. <br /><br /> This technique extends existing physically based models by completely excluding mutual interaction and highly localizing image deformations. We demonstrate its performance on a variety of images including two-dimensional and three-dimensional, synthetic and clinical data. Deformable images are achieved with sharper edges and clearer texture at less computational cost.

It is well known that biological structures such as human brains, although may contain the same global structures, differ in shape, orientation, and fine structures across individuals and at different times. Such variabilities during registration are usually represented by nonrigid transformations. This research seeks to address this issue by developing physically based models in which transformations are constructed to obey certain physical laws. <br /><br /> In this thesis, a novel registration technique is presented based on the physical behavior of particles. Regarding the image as a particle system without mutual interaction, we simulate the registration process by a set of free particles moving toward the target positions under applied forces. The resulting partial differential equations are a nonlinear hyperbolic system whose solution describes the spatial transformation between the images to be registered. They can be numerically solved using finite difference methods. <br /><br /> This technique extends existing physically based models by completely excluding mutual interaction and highly localizing image deformations. We demonstrate its performance on a variety of images including two-dimensional and three-dimensional, synthetic and clinical data. Deformable images are achieved with sharper edges and clearer texture at less computational cost.

The main topic of this thesis is nonrigid image registration for medical applications. We start with an overview and classification of existing registration techniques. We develop a general nonrigid image registration algorithm. It uses spline functions to describe the deformation and uses multi-scale strategy to search for the optimal transformation. Then we present a new registration operator that is transitive and symmetric. We investigate the theoretical implication of these properties and apply this operator to the registration of sequences of MR cardiac images. In the second part of the thesis, two methods, one 2D and one 3D, for validation of nonrigid image registration algorithms are proposed and compared to a manual validation strategy. Both methods provide pairs of deformed images as well as corresponding true displacement fields with known accuracy. Nonrigid registration algorithms can be run on the pairs of images and their outputs can be compared to the true displacement fields that were generated manually by five observers. While these phantom validation studies do not provide physically correct deformations, they are certainly a useful way to test the algorithm's ability to recover various deformation patterns.

After the reformation and opening, China moves from planned economy towards market economy. Active development of merchandise market and affection of loose household register system promotes the enormous population flow between town and country. However, the research found out that there are deep problems existed in population movement that need to be solved. These problems included the shifting of labor force from farming industry, the employments, managements and services of floating population in urban areas, as well as the reforms and innovations on the duality household registration system in the urban and rural areas. Particularly, it would be a good proposal to solve the ¡§Tri-Agricultural Problem¡¨ and city development at this particular period. This research probed into the increasing factors and development features of the floating population and emphasized mainly on the analysis of positive and negative influences to economic and society development. How to properly plan the population movement towards the modernized development aim of China is what this research about to discuss. The research is to discuss theories related to population flow. However, push and pull theory is commonly used in the world. In accordance with the idea of ¡§Equal emphasis on agriculture and industry, equal development of town and country¡¨ of developed economy M. Todaro Model, lifting agricultural productivity, improving rural life conditions, and shortening difference between town and country will ultimately make duality disappear and is practicable to the economic development with Chinese characteristics.

The globalization and frequent contact with other nations not only change the private enteritis but also the governments. Government offices related to the public service are seeking ways to improve their efficiency and quality of service in order to boost the competitive advantage of the country. Household Registration Offices is one of the department in the government that closely connect to people¡¦s daily life and its performance represents a part of the government performance, too. Therefore, how to improve the efficiency of administration and service quality of Household Registration Offices is one of the hottest issues currently. The goal of this paper is to investigate how to improve the service quality and satisfactions of the Household Registration Offices in communities of the Kaohsiung county area. This research is based on the survey conducted in the communities within the Kaohsiung County, Taiwan. The design of the survey employs the modified SERVQUAL measure in the PZB service quality concept model combining with 5 major aspects of the Household Registration Offices : ¡§reliability¡¨, ¡§the ability to response¡¨, ¡¨availability¡¨, ¡§assurance¡¨ and ¡§carefulness¡¨ and the other 26 attributes to measure the difference between the service quality providing to the public and the services quality expected from the communities. Moreover, we have conducted deviation analyses on the service quality awareness and satisfaction of the Household Registration Offices according to the population variables in the communities. The analyses include statistic analyses such as description analysis, T test and ANOVA. The conclusion obtained is listed as following points: 1. The expectation to the service quality of the Household Registration Offices from the communities is between important and very important. 2. The actual satisfaction of the communities reports that the service quality provided by the Household Registration Offices is above the satisfy level. 3. The analyses show that the actual service quality observed by the communities and the expected service quality is significantly different. In general, the actual service quality provided is less than the service quality expected. 4.The statistical analyses show that variables such as ¡§gender¡¨, ¡§age¡¨, ¡¨education¡¨, ¡§Household Registration Offices district¡¨ and ¡§overall satisfaction¡¨ has significant differences in the awareness of the service quality. 5. The statistical analyses show that the ¡§age¡¨, ¡§Household Registration Offices district¡¨ and ¡§overall satisfaction¡¨ variables have significant differences in the level of satisfaction. Finally, base on the conclusion of the paper, we also provide suggestions on how to improve the service quality of the Household Registration Offices and its satisfaction rate. We hope our suggestions can be served as the reference for the future studies as well as the guidelines for the government departments.

Includes bibliographical references (p. 51-54).

Spectral recomposition splits a seismic spectrum into Ricker components. It provides a tool for imaging and mapping temporal bed thicknesses and geologic discontinuities. I propose an application of separable, nonlinear, least-squares estimation in spectral recomposition. Employing the Gauss-Newton method, this approach estimates fundamental signal parameters such as peak frequencies and amplitudes. I applied spectral recomposition to multicomponent seismic data, which provides new perspectives of seismic attributes and multicomponent data interpretation. Correlating S-wave reflection with P -wave reflection is one of the very first steps in multicomponent data interpretation. In a given stratigraphic interval of a geologic section, registration correlates P and S-wave profiles to determine ts /tp ratios, which are equivalent to Vp /Vs ratios for vertical propagation paths. The registration process is largely driven by the availability of dipole sonic logs. However, dipole sonic logs are not as common as standard sonic logs and tend to be affected by various borehole factors. Therefore, new techniques are needed for accurate P P and P S correlation and registration. Assuming P P and P S reflection events have been correctly positioned laterally in migrated images, and the difference between P P wave image and P S wave image can be explained only by vertical transformation, I adopt a multistep approach to register PP and PS images automatically. Setting PP time as a coordinate system, I was able to squeeze P S traces accordingly while keeping the signal pattern of P S wave data. Local seismic attributes, such as the local similarity, help improve registration accuracy. / text