A Tomografia por Emissão de Pósitrons (PET) está se definindo como um dos métodos preferidos para diagnóstico e seguimento de inúmeras doenças em Oncologia, Neurologia e Cardiologia. Esta modalidade é realizada com sistemas dedicados e sistemas baseados em câmaras de cintilação, que podem ser também usados em tomografia por emissão de fótons únicos (SPECT). Neste trabalho, efetuamos uma avaliação dos fatores que favorecem a quantificação em imagens PET com câmaras de cintilação em coincidência, caracterizadas por urna menor sensibilidade em relação a sistemas dedicados. Avaliamos as condições de quantificação de imagens sob os modos 2D e 3D de aquisição, obtidas por métodos de reconstrução 2D e 3D diversos e correções associadas. Dados de aquisição foram simulados por método de Monte Carlo empregando parâmetros realistas. Objetos de interesse diversos foram modelados. Imagens foram reconstruídas pelos métodos FBP, ART, MLEM e OSEM e consideramos correções de sensibilidade, normalização de detector, espalhamento e atenuação de radiação. Estabelecemos uma metodologia de avaliação de detectabilidade e recuperação de contrastes em imagens que contemplam, a partir de dois parâmetros mensuráveis, os aspectos mais relevantes em quantificação. Análises visuais também foram consideradas. Verificamos que o modo 3D é mais adequado que 2D na recuperação de baixos contrastes no objeto com a aplicação das correções selecionadas. A detectabilidade de pequenas estruturas está limitada pelos efeitos de volume parcial e pela resolução espacial finita dos sistemas de detecção. Os métodos ART, MLEM e, em particular, OSEM com 8 subconjuntos, apresentam-se adequados para estudos quantitativos no modo 3D. Os parâmetros definidos para avaliação podem ser empregados como indicadores de condições propícias a estudos quantitativos. / Volumetric reconstruction in gamma camera based PET imaging Positron Emission Tomography (PET) is considered as a very useful tool for diagnosing and following several diseases in Oncology, Neurology and Cardiology. Two types of systems are available for this imaging modality: the dedicated systems and those based on gamma camera technology. In this work, we assessed a number of factors affecting the quantitation of gamma camera based PET imaging, characterized by a lower sensitivity compared to those of dedicated systems. We also evaluated image quantitation conditions under 2D and 3D acquisition/reconstruction modes, for different reconstruction methods and associated corrections. Acquisition data were simulated by Monte Carla method, using realistic parameters. Several objects of interest were modelled. We reconstructed slices and volumes using FBP, ART, MLEM and OSEM and also included four corrections: detector sensitivity, detector normalization, scatter and attenuation of annihilation photons. We proposed a method to assess detectability and object contrast recovery by using two measurable parameters. Visual analysis was also considered. We found that 3D mode is more effective than 2D for low contrast recovery when the selected (J corrections are applied. Detectability of small structures is limited by partial volume effects and device finite spatial resolution. ART, MLEM and specially 8-subsets OSEM are the most adequate methods for quantitative studies in 3D mode. The parameter that we have defined may also be used as indicators of suitable conditions for quantitation in images.

by He Xinggang. / "December 2000." / Thesis (Ph.D.)--Chinese University of Hong Kong, 2000. / Includes bibliographical references (p. 69-73). / Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Mode of access: World Wide Web. / Abstracts in English and Chinese.

Chan, Kwan Chung. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2011. / Includes bibliographical references (leaves 63-69). / Abstracts in English and Chinese. / Abstract --- p.v / Acknowledgements --- p.ix / List of Figures --- p.xiii / List of Tables --- p.xv / Chapter 1 --- Introduction --- p.1 / Chapter 1.1 --- Main contributions --- p.4 / Chapter 1.2 --- Overview --- p.4 / Chapter 2 --- Related Work --- p.7 / Chapter 2.1 --- Point cloud processing --- p.7 / Chapter 2.2 --- Model repairing --- p.9 / Chapter 2.3 --- Deformation and reconstruction --- p.10 / Chapter 3 --- Iterative Consolidation on Un-orientated Point Clouds --- p.11 / Chapter 3.1 --- Algorithm overview --- p.12 / Chapter 3.2 --- Down-sampling and outliers removal --- p.14 / Chapter 3.2.1 --- Normal estimation --- p.14 / Chapter 3.2.2 --- Down-sampling --- p.15 / Chapter 3.2.3 --- Particle noise removal --- p.17 / Chapter 3.3 --- APSS based repulsion --- p.19 / Chapter 3.4 --- Refinement --- p.22 / Chapter 3.4.1 --- Adaptive up-sampling --- p.22 / Chapter 3.4.2 --- Selection of up-sampled points --- p.23 / Chapter 3.4.3 --- Sample noise removal --- p.23 / Chapter 3.5 --- Set constraints to sample points --- p.24 / Chapter 4 --- Shape Modeling by Point Set --- p.27 / Chapter 4.1 --- Principle of deformation --- p.27 / Chapter 4.2 --- Selection --- p.29 / Chapter 4.3 --- Stretching and compressing --- p.30 / Chapter 4.4 --- Bending and twisting --- p.30 / Chapter 4.5 --- Inserting points --- p.30 / Chapter 5 --- Results and Discussion --- p.37 / Chapter 5.1 --- Program environment --- p.37 / Chapter 5.2 --- Results of iterative consolidation on un-orientated points --- p.37 / Chapter 5.3 --- Effect of our de-noising based on up-sampled points --- p.44 / Chapter 6 --- Conclusions --- p.49 / Chapter 6.1 --- Advantages --- p.49 / Chapter 6.2 --- Factors affecting our algorithm --- p.50 / Chapter 6.3 --- Possible future works --- p.51 / Chapter 6.3.1 --- Improve on the quality of results --- p.51 / Chapter 6.3.2 --- Reduce user input --- p.52 / Chapter 6.3.3 --- Multi-thread computation --- p.52 / Chapter A --- Finding Neighbors --- p.53 / Chapter A.1 --- k-d Tree --- p.53 / Chapter A.2 --- Octree --- p.54 / Chapter A.3 --- Minimum spanning tree --- p.55 / Chapter B --- Principle Component Analysis --- p.57 / Chapter B.1 --- Principle component analysis --- p.57 / Chapter C --- UI of the program --- p.59 / Chapter C.1 --- User Interface --- p.59 / Chapter D --- Publications --- p.61 / Bibliography --- p.63

Programming by demonstration is an end-user programming technique that allows people to create programs by showing the computer examples of what they want to do. Users do not need specialised programming skills. Instead, they instruct the computer by demonstrating examples, much as they might show another person how to do the task. Programming by demonstration empowers users to create programs that perform tedious and time-consuming computer chores. However, it is not in widespread use, and is instead confined to research applications that end users never see. This makes it difficult to evaluate programming by demonstration tools and techniques. This thesis claims that domain-independent programming by demonstration can be made available in existing applications and used to automate iterative tasks by end users. It is supported by Familiar, a domain-independent, AppleScript-based programming-by-demonstration tool embodying standard machine learning algorithms. Familiar is designed for end users, so works in the existing applications that they regularly use. The assertion that programming by demonstration can be made available in existing applications is validated by identifying the relevant platform requirements and a range of platforms that meet them. A detailed scrutiny of AppleScript highlights problems with the architecture and with many implementations, and yields a set of guidelines for designing applications that support programming-by-demonstration. An evaluation shows that end users are capable of using programming by demonstration to automate iterative tasks. However, the subjects tended to prefer other tools, choosing Familiar only when the alternatives were unsuitable or unavailable. Familiar's inferencing is evaluated on an extensive set of examples, highlighting the tasks it can perform and the functionality it requires.

The development process for complex system is typically iterative in nature. Among the critical decisions in managing such process involves deciding how to partition the system development into iterations. This paper proposes a mathematical model that captures the dynamics of such iterative process. The analysis of two special cases of the model provides an insight into how such decision should be made. / Singapore-MIT Alliance (SMA)

Iterative solutions of the Boltzmann transport equation are computationally intensive. Spatial multigrid methods have led to efficient iterative algorithms for solving a variety of partial differential equations; thus, it is natural to explore their application to transport equations. Manteuffel et al. conducted such an exploration in one spatial dimension, using two-cell inversions as the relaxation or smoothing operation, and reported excellent results. In this dissertation we extensively test Manteuffel??s one-dimensional method and our modified versions thereof. We demonstrate that the performance of such spatial multigrid methods can degrade significantly given strong heterogeneities. We also extend Manteuffel??s basic approach to two-dimensional problems, employing four-cell inversions for the relaxation operation. We find that for uniform homogeneous problems the two-dimensional multigrid method is not as rapidly convergent as the one-dimensional method. For strongly heterogeneous problems the performance of the two-dimensional method is much like that of the one-dimensional method, which means it can be slow to converge. We conclude that this approach to spatial multigrid produces a method that converges rapidly for many problems but not for others. That is, this spatial multigrid method is not unconditionally rapidly convergent. However, our analysis of the distribution of eigenvalues of the iteration operators indicates that this spatial multigrid method may work very well as a preconditioner within a Krylov iteration algorithm, because its eigenvalues tend to be relatively well clustered. Further exploration of this promising result appears to be a fruitful area of further research.

The presence of dispersive fading and inter-carrier interference (ICI) constitute the major impediment to reliable communications in orthogonal frequency-division multiplexing (OFDM) systems. Recently iterative (``Turbo'') processing techniques, which have been successfully applied to many detection/decoding problems, have received considerable attention. In this thesis, we first aim on the design of iterative receiver for single antenna OFDM system with frequency offset and dispersive fading. Further work is then extended to space-time block coded (STBC) OFDM system. At last, the technique is applied to STBC-OFDM system through a newly built channel model, which is based on a physical description of the propagation environment. The performance of such systems are verified by computer simulations. The simulation results show that the iterative techniques work well in OFDM systems.

Iterative decoding and codes on graphs were first devised by Gallager in 1960, and then rediscovered by Berrou, Glavieux and Thitimajshima in 1993. This technique plays an important role in modern communications, especially in coding theory and practice. In particular, low-density parity-check (LDPC) codes, introduced by Gallager in the 1960s, are the class of codes at the heart of iterative coding. Since these codes are quite general and exhibit good performance under message-passing decoding, they play an important role in communications research today. A thorough analysis of iterative decoding systems and the relationship between maximum a posteriori (MAP) and belief propagation (BP) decoding was initiated by Measson, Montanari, and Urbanke. This analysis is based on density evolution (DE), and extrinsic information transfer (EXIT) functions, introduced by ten Brink. Following their work, this thesis considers the MAP decoding thresholds of three iterative decoding systems. First, irregular repeat-accumulate (IRA) and accumulaterepeataccumulate (ARA) code ensembles are analyzed on the binary erasure channel (BEC). Next, the joint iterative decoding of LDPC codes is studied on the dicode erasure channel (DEC). The DEC is a two-state intersymbol-interference (ISI) channel with erasure noise, and it is the simplest example of an ISI channel with erasure noise. Then, we introduce a slight generalization of the EXIT area theorem and apply the MAP threshold bound for the joint decoder. Both the MAP and BP erasure thresholds are computed and compared with each other. The result quantities the loss due to iterative decoding Some open questions include the tightness of these bounds and the extensions to non-erasure channels.

This thesis studies advanced error control schemes using turbo-like codes, turbo-like coded modulations, turbo hybrid-ARQ (Automatic Repeat reQuest) schemes, and rate compatible puncturing techniques for reliable and adaptive commercial and tactical spread-spectrum communications, especially for code-division multiple access (CDMA) cellular systems and direct-sequence (DS) and frequency-hopping (FH) anti-jam systems. Furthermore, we utilize both the maximum-likelihood (ML) bounding techniques and convergence analysis to design and analyze various turbo-like coding schemes that show different behaviors in error performance from conventional trellis coding schemes. In the area of DS-CPM, we propose a DS concatenated coded CPM system for pulse-noise jamming channels and an anti-jam iterative receiver utilizing jammer state information. We also design a mixed concatenated CPM system that mixes CPM schemes with different convergence characteristics. In addition, we present the ML bound and convergence analysis for the jamming channel. In the area of FH-CPM, we propose anti-jam serially concatenated slow FH-CPM systems, whose phase is continuous during each hop interval, along with coherent and non-coherent iterative receivers. We also propose an iterative jamming estimation technique for the iterative receiver. In the area of multi-h CPM, we propose a power- and bandwidth-efficient serially concatenated multi-h CPM along with an appropriate iterative receiver structure. Serially concatenated multi-h CPM is shown to outperform single-h CPM. To design adaptive and versatile error control schemes using turbo-like codes for packet-data networks, we propose turbo hybrid-ARQ (HARQ) and rate compatible puncturing techniques for retransmission. In the area of turbo hybrid-ARQ, we propose a Type-I turbo HARQ scheme using a concatenated RS-turbo code and a packet combining technique for W-CDMA system to improve the performance of error and decoding latency. The W-CDMA system including the fast power control and coherent Rake receiver with a channel estimation technique for multipath fading channels is considered. Finally, in the area of rate compatible punctured turbo-like codes, we propose rate compatible punctured turbo (RCPT) codes and rate compatible punctured serially concatenated convolutional (RCPS) codes along with their puncturing methods. In addition, we propose Type-II RCPT-HARQ and RCPS-HARQ schemes to perform an efficient incremental redundancy retransmission.

The objective of the proposed research is to devise high-performance and low-complexity signal-detection algorithms for communication systems over fading channels. They include channel equalization to combat intersymbol interference (ISI) and multiple input multiple output (MIMO) signal detection to deal with multiple access interference (MAI) from other transmit antennas. As the demand for higher data-rate and more efficiency wireless communications increases, signal detection becomes more challenging. We propose novel transmission and iterative signal-detection techniques based on energy spreading transform (EST). Different from the existing iterative methods based on the turbo principle, the proposed schemes are independent of channel coding. EST is an orthonormal that spreads a symbol energy over the symbol block in time and frequency for channel equalization; space and time for MIMO signal detection with flat fading channels; and space, time, and frequency for MIMO signal detection with frequency-selective fading channels. Due to the spreading, EST obtains diversity in the available domains for the specific application and increases the reliability of the feedback signal. Moreover, it enables iterative signal detection that has near interference-free performance only at the complexity of linear detectors. Either a hard or soft decision can be fed back to the interference-cancellation stage at the subsequent iteration. The soft-decision scheme prevents error propagation of the hard-decision scheme for a low SNR and improves the performance. We analyze the performance of the proposed techniques. Analytical and simulation results show that these schemes perform very close to the interference-free systems.