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State-of-the-art three-dimensional endo-luminal virtual colonoscopy (VC) or CT colonography (CTC) is a minimally invasive medical procedure that examines the entire colon in order to detect polyps and colorectal cancer. Most colon cancers malignantly transform from polyps, which are extra growths on the surface of the mucous membrane. Three dimensional endoscopic colon lumen interior images offered by CTC allow physicians to examine the colon interactively. Thus, CTC has several advantages over conventional optical colonoscopy including reduced risk. One of the challenging problems that prevent practical use in clinical situations is the complexity of the human colon. The colon's deformation by peristalsis and the diverse shapes of polyps make it difficult to distinguish polyps from other non-threatening entities in the colon. Hence, most CTC protocols acquire both prone and supine images to improve the visualization of the lumen wall, reduce false positives, and improve sensitivity. Comparisons between the prone and supine images can be facilitated by computerized registration between the scans. In this dissertation, two algorithms for registering colons segmented from prone and supine images are presented. First is an algorithm for three dimensional registration of the prone and supine colon when both are well distended and there is a single connected lumen. Second is another registration algorithm between colons with topological differences caused by inadequate bowel preparation or peristalsis. Such topological changes make deformable registrations of the colons difficult, and at present there are no registration algorithms which can accommodate them. The first algorithm uses feature matching of the colon centerline and a modified version of the demons deformable registration algorithm to define a deformation field between the prone and supine lumen surface. The second method utilizes embedded map representation of colon volume. The two proposed colon registration methods will contribute to improving the accuracy of the computerized registration process and increasing the versatility of the clinical use of CT colonoscopy. / Ph. D.

In medical images, intensity changes caused by certain pathology can change the topology of image level-sets and are thus commonly referred to as topological changes. Topological changes cause false deformation in existing deformable registration algorithms, which in turn leads to unreliable observations in the clinical study that relies on the deformation fields, such as deformation based morphometry (DBM). In this work, we develop a new deformable registration algorithm for images with topological changes. In our proposed algorithm, 3D images are embedded as 4D surfaces in a Riemannian space. The registration is therefore conducted as a surface evolution, which is modeled by a diffusion process. Our algorithm differs from existing methods in the sense that it takes an a-priori estimation of areas with topological change as an additional input and generates dense deformation vector fields which are free of false deformation. In particular, the output of our algorithm is composed of a diffeomorphic deformation field and an intensity displacement which corrects intensity difference caused by topological changes. By conducting multiple sets of experiments, we demonstrate that our proposed algorithm is capable of accurately registering images with considerable topological changes. More importantly, the resulting deformation field is not impacted by topological changes, i.e., there is no false deformation. / Ph. D.

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Du Xin. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2004. / Includes bibliographical references (leaves 67-68). / Abstracts in English and Chinese. / Abstract --- p.i-ii / Acknowledgement --- p.iii / Table of Contents --- p.iv-v / Chapter Chapter 1 --- Introduction --- p.1 / Chapter 1.1 --- Background information and history of VRM auctions in Hong Kong --- p.2 / Chapter 1.2 --- VRM auctions in other countries --- p.6 / Chapter 1.3 --- Chinese numerology in brief --- p.8 / Chapter Chapter 2 --- "Data Set, literature review and models" --- p.11 / Chapter 2.1 --- Data Set --- p.11 / Chapter 2.2 --- Literature review --- p.13 / Chapter 2.3 --- Variables --- p.14 / Chapter 2.4 --- Model set-up --- p.18 / Chapter 2.4.1 --- Sub-sample estimation --- p.18 / Chapter 2.4.1.1 --- LENGTH as the segmentation criterion --- p.18 / Chapter 2.4.1.2 --- Price range as the segmentation criterion --- p.20 / Chapter 2.4.2 --- Taking logarithm to smooth the fluctuation --- p.22 / Chapter Chapter 3 --- Estimations of hedonic pricing models using the entire sample --- p.23 / Chapter 3.1 --- Estimation results for sub-samples using LENGTH as the segmentation criterion --- p.23 / Chapter 3.2 --- Estimation results for sub-samples using price range as the segmentation criterion --- p.29 / Chapter 3.2.1 --- Estimation of models for the first sub-sample --- p.30 / Chapter 3.2.2 --- Estimation of models for the second sub-sample --- p.33 / Chapter 3.2.3 --- Estimation of models for the third sub-sample --- p.36 / Chapter Chapter 4 --- Estimations of hedonic pricing models using the 99% sample --- p.42 / Chapter 4.1 --- Estimation results for sub-samples using LENGTH as the segmentation criterion --- p.42 / Chapter 4.2 --- Estimation results for sub-samples using price range as the segmentation criterion --- p.49 / Chapter 4.2.1 --- Estimation of models for the first sub-sample --- p.50 / Chapter 4.2.2 --- Estimation of models for the second sub-sample --- p.52 / Chapter 4.2.3 --- Estimation of models for the third sub-sample --- p.52 / Chapter Chapter 5 --- Estimations of hedonic pricing models for LNP --- p.60 / Chapter Chapter 6 --- Conclusion --- p.65 / References --- p.67 / Appendix A Normality test for LNP --- p.69

陳潔珊. / 書名中之「貯」「履」二字原為金文. / 論文(碩士) -- 香港中文大學硏究院中國語言及文學學部, 1997. / 參考文獻: leaves 281-302. / Chen Jieshan. / Chapter 第一章 --- 引言 --- p.1 / 第一章注釋 --- p.4 / Chapter 第二章 --- 金文中的「？」字 --- p.5 / Chapter (1) --- 金文中「？」字及「？田」的解釋 --- p.5 / Chapter (a) --- 「？」隸定爲「？」（「貯」）字 --- p.5 / Chapter (b) --- 「？田」即「租田」說 --- p.16 / Chapter (c) --- 「？田」即「賈田」說 --- p.26 / Chapter (d) --- 「？田」即「予田」或「舍田」說 --- p.41 / Chapter (e) --- 「？田」即「償田」說 --- p.46 / Chapter (f) --- 「？田」即「除田」說 --- p.47 / Chapter (g) --- 「？」、「？」義近說 --- p.48 / Chapter (2) --- 小結 --- p.50 / 第二章 注釋 --- p.53 / Chapter 第三章 --- 金文中的「舍」字 --- p.78 / Chapter (1) --- 金文中「舍」字及「舍田」的解釋 --- p.78 / Chapter (a) --- 「舍」即「賜予」說 --- p.78 / Chapter (b) --- 「舍田」即「予田」說 --- p.88 / Chapter (2） --- 小結 --- p.94 / 第三章 注釋 --- p.104 / Chapter 第四章 --- 金文中的「？」字 --- p.114 / Chapter (1) --- 《散氏盤》「？」字的解釋 --- p.114 / Chapter (a) --- 「？」即「眉」字說 --- p.114 / Chapter (i) --- 「？」」即「堳埒」的「堳」 --- p.114 / Chapter (ii) --- 「？」即周初微國 --- p.120 / Chapter (b) --- 「？」即「履」字說 --- p.123 / Chapter (2) --- 金文「履田」考 --- p.129 / Chapter (3) --- 小結 --- p.144 / 第四章 注釋 --- p.152 / Chapter 第五章 --- 金文中的「封」字 --- p.167 / Chapter (1) --- 金文中「封」字的解釋 --- p.167 / Chapter (2) --- 「封」、「邦」二字同源考 --- p.172 / Chapter (3) --- 金文中有關封疆劃界的記載 --- p.180 / Chapter (4) --- 小結 --- p.191 / 第五章 注釋 --- p.194 / Chapter 第六章 --- 「？田」、「舍田」、「履田」、「立封」所反映的西 周土地交換情況 --- p.201 / Chapter (1) --- 土地交換並非私下買賣 --- p.201 / Chapter (2) --- 土地交換的原因 --- p.207 / Chapter (3) --- 土地交換的程序 --- p.210 / Chapter (4) --- 小結 --- p.223 / 第六章 注釋 --- p.226 / Chapter 第七章 --- 總結 --- p.236 / 第七章 注釋 --- p.242 / 附錄 --- p.243 / 附錄一 本文引用銘文的拓本及釋文 --- p.243 / 附錄二 《毛公鼎》銘「？」字考釋 --- p.273 / 附錄三 《牆盤》銘「？」字考釋 --- p.276 / 參考書目 --- p.281

This dissertation presents a new inverse consistent image registration (ICIR) method called boundary-constrained inverse consistent image registration (BICIR). ICIR algorithms jointly estimate the forward and reverse transformations between two images while minimizing the inverse consistency error (ICE). The ICE at a point is defined as the distance between the starting and ending location of a point mapped through the forward transformation and then the reverse transformation. The novelty of the BICIR method is that a region of interest (ROI) in one image is registered with its corresponding ROI. This is accomplished by first registering the boundaries of the ROIs and then matching the interiors of the ROIs using intensity registration. The advantages of this approach include providing better registration at the boundary of the ROI, eliminating registration errors caused by registering regions outside the ROI, and theoretically minimizing computation time since only the ROIs are registered. The first step of the BICIR algorithm is to inverse consistently register the boundaries of the ROIs. The resulting forward and reverse boundary transformations are extended to the entire ROI domains using the Element Free Galerkin Method (EFGM). The transformations produced by the EFGM are then made inverse consistent by iteratively minimizing the ICE. These transformations are used as initial conditions for inverse-consistent intensity-based registration of the ROI interiors. Weighted extended B-splines (WEB-splines) are used to parameterize the transformations. WEB-splines are used instead of B-splines since WEB-splines can be defined over an arbitrarily shaped ROI. Results are presented showing that the BICIR method provides better registration of 2D and 3D anatomical images than the small-deformation, inverse-consistent, linear-elastic (SICLE) image registration algorithm which registers entire images. Specifically, the BICIR method produced registration results with lower similarity cost, reduced boundary matching error, increased ROI relative overlap, and lower inverse consistency error than the SICLE algorithm.

Despite the launching of e-service by household registration offices, there have been few studies and examples associated with the organization streamlining. This study constructs a research framework for changes in Taiwan¡¦s first household registration office organization structure resulting from township/city consolidation, as well as the resulting work stress, and explores the correlation between members¡¦ cognition concerning their organization¡¦s merger and their work stress after the merger with organizations possessing similar functions. This study is a qualitative research, in which the staff members of Donggang Household Registration Office, Pingtung County, are taken as the subjects for in-depth interviews. Interview data analysis and research hypothesis are employed for verification. This case study focuses on structural change. An examination of the potential stress factors after organization structure change finds that, after the merger, the staff members did not have to learn new skills, nor were their work routines or workplace locations changed, in adapting to the new organization. Only high-level supervisors were impacted because fewer of them were needed after the merger. Accordingly, the merger of household registration offices with similar functions did not have a significant effect on work stress for most staff members.