Off-line Arabic Handwriting Recognition System Using Fast Wavelet Transform

In this research, off-line handwriting recognition system for Arabic alphabet is introduced. The system contains three main stages: preprocessing, segmentation and recognition stage. In the preprocessing stage, Radon transform was used in the design of algorithms for page, line and word skew correction as well as for word slant correction. In the segmentation stage, Hough transform approach was used for line extraction. For line to words and word to characters segmentation, a statistical method using mathematic representation of the lines and words binary image was used. Unlike most of current handwriting recognition system, our system simulates the human mechanism for image recognition, where images are encoded and saved in memory as groups according to their similarity to each other. Characters are decomposed into a coefficient vectors, using fast wavelet transform, then, vectors, that represent a character in different possible shapes, are saved as groups with one representative for each group. The recognition is achieved by comparing a vector of the character to be recognized with group representatives. Experiments showed that the proposed system is able to achieve the recognition task with 90.26% of accuracy. The system needs only 3.41 seconds a most to recognize a single character in a text of 15 lines where each line has 10 words on average

Off-line Arabic Handwriting Recognition System Using Fast Wavelet Transform

In this research, off-line handwriting recognition system for Arabic alphabet is introduced. The system contains three main stages: preprocessing, segmentation and recognition stage. In the preprocessing stage, Radon transform was used in the design of algorithms for page, line and word skew correction as well as for word slant correction. In the segmentation stage, Hough transform approach was used for line extraction. For line to words and word to characters segmentation, a statistical method using mathematic representation of the lines and words binary image was used. Unlike most of current handwriting recognition system, our system simulates the human mechanism for image recognition, where images are encoded and saved in memory as groups according to their similarity to each other. Characters are decomposed into a coefficient vectors, using fast wavelet transform, then, vectors, that represent a character in different possible shapes, are saved as groups with one representative for each group. The recognition is achieved by comparing a vector of the character to be recognized with group representatives. Experiments showed that the proposed system is able to achieve the recognition task with 90.26% of accuracy. The system needs only 3.41 seconds a most to recognize a single character in a text of 15 lines where each line has 10 words on average

Fast fully automatic myocardial segmentation in 4D cine cardiac magnetic resonance datasets

Dissertação de mestrado integrado em Engenharia BiomédicaCardiovascular diseases (CVDs) are the leading cause of death in the world, representing 30% of all global deaths. Among others, assessment of the left ventricular (LV) morphology and global function using non-invasive cardiac imaging is an interesting technique for diagnosis and treatment follow-up of patients with CVDs. Nowadays, cardiac magnetic resonance (CMR) imaging is the gold-standard technique for the quantification of LV volumes, mass and ejection fraction, requiring the delineation of endocardial and epicardial contours of the left ventricle from cine MR images. In clinical practice, the physicians perform this segmentation manually, being a tedious, time consuming and unpractical task. Even though several (semi-)automated methods have been presented for LV CMR segmentation, fast, automatic and optimal boundaries assessment is still lacking, usually requiring the physician to manually correct the contours. In the present work, we propose a novel fast fully automatic 3D+time LV segmentation framework for CMR datasets. The proposed framework presents three conceptual blocks: 1) an automatic 2D mid-ventricular initialization and segmentation; 2) an automatic stack initialization followed by a 3D segmentation at the end-diastolic phase; and 3) a tracking procedure to delineate both endo and epicardial contours throughout the cardiac cycle. In each block, specific CMR-targeted algorithms are proposed for the different steps required. Hereto, we propose automatic and feasible initialization procedures. Moreover, we adapt the recent B-spline Explicit Active Surfaces (BEAS) framework to the properties of CMR image segmentation by integrating dedicated energy terms and making use of a cylindrical coordinate system that better fits the topology of CMR data. At last, two tracking methods are presented and compared. The proposed framework has been validated on 45 4D CMR datasets from a publicly available database and on a large database from an ongoing multi-center clinical trial with 318 4D datasets. In the technical validation, the framework showed competitive results against the state-of-the-art methods, presenting leading results in both accuracy and average computational time in the common database used for comparative purposes. Moreover, the results in the large scale clinical validation confirmed the high feasibility and robustness of the proposed framework for accurate LV morphology and global function assessment. In combination with the low computational burden of the method, the present methodology seems promising to be used in daily clinical practice.As doenças cardiovasculares (DCVs) são a principal causa de morte no mundo, representando 30% destas a nível global. Na prática clínica, uma técnica empregue no diagnóstico de pacientes com DCVs é a avaliação da morfologia e da função global do ventrículo esquerdo (VE), através de técnicas de imagiologia não-invasivas. Atualmente, a ressonância magnética cardíaca (RMC) é a modalidade de referência na quantificação dos volumes, massa e fração de ejeção do VE, exigindo a delimitação dos contornos do endocárdio e epicárdio a partir de imagens dinâmicas de RMC. Na prática clínica diária, o método preferencial é a segmentação manual. No entanto, esta é uma tarefa demorada, sujeita a erro humano e pouco prática. Apesar de até à data diversos métodos (semi)-automáticos terem sido apresentados para a segmentação do VE em imagens de RMC, ainda não existe um método capaz de avaliar idealmente os contornos de uma forma automática, rápida e precisa, levando a que geralmente o médico necessite de corrigir manualmente os contornos. No presente trabalho é proposta uma nova framework para a segmentação automática do VE em imagens 3D+tempo de RMC. O algoritmo apresenta três blocos principais: 1) uma inicialização e segmentação automática 2D num corte medial do ventrículo; 2) uma inicialização e segmentação tridimensional no volume correspondente ao final da diástole; e 3) um algoritmo de tracking para obter os contornos ao longo de todo o ciclo cardíaco. Neste sentido, são propostos procedimentos de inicialização automática com elevada robustez. Mais ainda, é proposta uma adaptação da recente framework “B-spline Explicit Active Surfaces” (BEAS) com a integração de uma energia específica para as imagens de RMC e utilizando uma formulação cilíndrica para tirar partido da topologia destas imagens. Por último, são apresentados e comparados dois algoritmos de tracking para a obtenção dos contornos ao longo do tempo. A framework proposta foi validada em 45 datasets de RMC provenientes de uma base de dados disponível ao público, bem como numa extensa base de dados com 318 datasets para uma validação clínica. Na avaliação técnica, a framework proposta obteve resultados competitivos quando comparada com outros métodos do estado da arte, tendo alcançado resultados de precisão e tempo computacional superiores a estes. Na validação clínica em larga escala, a framework provou apresentar elevada viabilidade e robustez na avaliação da morfologia e função global do VE. Em combinação com o baixo custo computacional do algoritmo, a presente metodologia apresenta uma perspetiva promissora para a sua aplicação na prática clínica diária

Novel Approaches to Pervasive and Remote Sensing in Cardiovascular Disease Assessment

Cardiovascular diseases (CVDs) are the leading cause of death worldwide, responsible for 45% of all deaths. Nevertheless, their mortality is decreasing in the last decade due to better prevention, diagnosis, and treatment resources. An important medical instrument for the latter processes is the Electrocardiogram (ECG). The ECG is a versatile technique used worldwide for its ease of use, low cost, and accessibility, having evolved from devices that filled up a room, to small patches or wrist- worn devices. Such evolution allowed for more pervasive and near-continuous recordings. The analysis of an ECG allows for studying the functioning of other physiological systems of the body. One such is the Autonomic Nervous System (ANS), responsible for controlling key bodily functions. The ANS can be studied by analyzing the characteristic inter-beat variations, known as Heart Rate Variability (HRV). Leveraging this relation, a pilot study was developed, where HRV was used to quantify the contribution of the ANS in modulating cardioprotection offered by an experimental medical procedure called Remote Ischemic Conditioning (RIC), offering a more objective perspective. To record an ECG, electrodes are responsible for converting the ion-propagated action potential to electrons, needed to record it. They are produced from different materials, including metal, carbon-based, or polymers. Also, they can be divided into wet (if an elec- trolyte gel is used) or dry (if no added electrolyte is used). Electrodes can be positioned either inside the body (in-the-person), attached to the skin (on-the-body), or embedded in daily life objects (off-the-person), with the latter allowing for more pervasive recordings. To this effect, a novel mobile acquisition device for recording ECG rhythm strips was developed, where polymer-based embedded electrodes are used to record ECG signals similar to a medical-grade device. One drawback of off-the-person solutions is the increased noise, mainly caused by the intermittent contact with the recording surfaces. A new signal quality metric was developed based on delayed phase mapping, a technique that maps time series to a two-dimensional space, which is then used to classify a segment into good or noisy. Two different approaches were developed, one using a popular image descriptor, the Hu image moments; and the other using a Convolutional Neural Network, both with promising results for their usage as signal quality index classifiers.As doenças cardiovasculares (DCVs) são a principal causa de morte no mundo, res- ponsáveis por 45% de todas estas. No entanto, a sua mortalidade tem vindo a diminuir na última década, devido a melhores recursos na prevenção, diagnóstico e tratamento. Um instrumento médico importante para estes recursos é o Eletrocardiograma (ECG). O ECG é uma técnica versátil utilizada em todo o mundo pela sua facilidade de uso, baixo custo e acessibilidade, tendo evoluído de dispositivos que ocupavam uma sala inteira para pequenos adesivos ou dispositivos de pulso. Tal evolução permitiu aquisições mais pervasivas e quase contínuas. A análise de um ECG permite estudar o funcionamento de outros sistemas fisiológi- cos do corpo. Um deles é o Sistema Nervoso Autônomo (SNA), responsável por controlar as principais funções corporais. O SNA pode ser estudado analisando as variações inter- batidas, conhecidas como Variabilidade da Frequência Cardíaca (VFC). Aproveitando essa relação, foi desenvolvido um estudo piloto, onde a VFC foi utilizada para quantificar a contribuição do SNA na modulação da cardioproteção oferecida por um procedimento mé- dico experimental, denominado Condicionamento Isquêmico Remoto (CIR), oferecendo uma perspectiva mais objetiva. Na aquisição de um ECG, os elétrodos são os responsáveis por converter o potencial de ação propagado por iões em eletrões, necessários para a sua recolha. Estes podem ser produzidos a partir de diferentes materiais, incluindo metal, à base de carbono ou polímeros. Além disso, os elétrodos podem ser classificados em húmidos (se for usado um gel eletrolítico) ou secos (se não for usado um eletrólito adicional). Os elétrodos podem ser posicionados dentro do corpo (dentro-da-pessoa), colocados em contacto com a pele (na-pessoa) ou embutidos em objetos da vida quotidiana (fora-da-pessoa), sendo que este último permite gravações mais pervasivas . Para este efeito, foi desenvolvido um novo dispositivo de aquisição móvel para gravar sinal de ECG, onde elétrodos embutidos à base de polímeros são usados para recolher sinais de ECG semelhantes a um dispositivo de grau médico. Uma desvantagem das soluções onde os elétrodos estão embutidos é o aumento do ruído, causado principalmente pelo contato intermitente com as superfícies de aquisição. Uma nova métrica de qualidade de sinal foi desenvolvida com base no mapeamento de fase atrasada, uma técnica que mapeia séries temporais para um espaço bidimensional, que é então usado para classificar um segmento em bom ou ruidoso. Duas abordagens diferentes foram desenvolvidas, uma usando um popular descritor de imagem, e outra utilizando uma Rede Neural Convolucional, com resultados promissores para o seu uso como classificadores de qualidade de sinal

Automatic Cancer Tissue Detection Using Multispectral Photoacoustic Imaging

Convolutional neural networks (CNNs) have become increasingly popular in recent years because of their ability to tackle complex learning problems such as object detection, and object localization. They are being used for a variety of tasks, such as tissue abnormalities detection and localization, with an accuracy that comes close to the level of human predictive performance in medical imaging. The success is primarily due to the ability of CNNs to extract the discriminant features at multiple levels of abstraction. Photoacoustic (PA) imaging is a promising new modality that is gaining significant clinical potential. The availability of a large dataset of three dimensional PA images of ex-vivo human prostate and thyroid specimens has facilitated this current study aimed at evaluating the efficacy of CNN for cancer diagnosis. In PA imaging, a short pulse of near-infrared laser light is sent into the tissue, but the image is created by focusing the ultrasound waves that are photoacoustically generated due to the absorption of light, thereby mapping the optical absorption in the tissue. By choosing multiple wavelengths of laser light, multispectral photoacoustic (MPA) images of the same tissue specimen can be obtained. The objective of this thesis is to implement deep learning architecture for cancer detection using the MPA image dataset. In this study, we built and examined a fully automated deep learning framework that learns to detect and localize cancer regions in a given specimen entirely from its MPA image dataset. The dataset for this work consisted of samples with size ranging from 12 × 45 × 200 pixels to 64 × 64 × 200 pixels at five wavelengths namely, 760 nm, 800 nm, 850 nm, 930 nm, and 970 nm. The proposed algorithms first extract features using convolutional kernels and then detect cancer tissue using the softmax function, the last layer of the network. The AUC was calculated to evaluate the performance of the cancer tissue detector with a very promising result. To the best of our knowledge, this is one of the first examples of the application of deep 3D CNN to a large cancer MPA dataset for the prostate and thyroid cancer detection. While previous efforts using the same dataset involved decision making using mathematically extracted image features, this work demonstrates that this process can be automated without any significant loss in accuracy. Another major contribution of this work has been to demonstrate that both prostate and thyroid datasets can be combined to produce improved results for cancer diagnosis

Photoacoustic image guidance and tissue characterization in cardiovascular applications

Collectively, cardiovascular diseases continue to be the leading cause of death, across nations and across decades. Improved diagnostic imaging methods offer promise to alleviate the morbidity associated with these diseases. Photoacoustic (PA) imaging is one such method, poised to make a significant impact on cardiovascular imaging, both as a research tool, as well as a clinical imaging modality. Offering the potential of molecular imaging in real-time, PA methods have been demonstrated in proof-of-concept studies tracking myocyte calcium dynamics. These results open the door to non-invasive longitudinal assessment of cardiac electrophysiological function, with implications for drug and contrast agent development. PA image guidance has also been extended to the characterization of cardiac radiofrequency ablation lesions. This method has been demonstrated to utilize endogenous chromophore changes resulting from ablation for the generation of depth-resolved tissue characterization maps, capable of assessing lesion extent. The technique has been subsequently validated by assessing high-intensity focused ultrasound ablation lesions in myocardium, with the hope for offering thermographic capabilities as well. While PA imaging offers such promise in cardiac ablation procedures, it is also in the process of clinical translation for image guidance and characterization in coronary artery disease applications. Research has shown, using Monte Carlo optical modeling, that using a simple dual-wavelength PA imaging technique has great potential for successful visualization of atherosclerotic plaques across multiple tissue types and at clinically relevant multiple millimeters of depth. Collectively these results offer a suite of PA imaging tools with the potential for molecular and thermographic imaging across a broad range of cardiovascular applications.Biomedical Engineerin

Methods and Instrumentation for Non-Invasive Assessment of the Cardiovascular Condition

Tese de doutoramento em Física (Pré-Bolonha), Especialidade de Física Tecnológica, apresentada à Faculdade de Ciências e Tecnologia da Universidade de CoimbraAs doenças cardiovasculares (DCVs) são a principal causa de morte a nível mundial e largamente responsáveis pelos custos crescentes nos sistemas de saúde. Nos últimos anos, a comunidade médica tem vindo a demonstrar um grande interesse na avaliação da rigidez arterial local, pressão arterial central e na análise da onda de pressão, devido aos seus valores preditivos no desenvolvimento deste tipo de patologias. Apesar da sua relevância, estes parâmetros hemodinâmicos permanecem particularmente difíceis de medir na prática clínica, já que a maioria dos dispositivos disponíveis exigem elevados conhecimentos técnicos (introduzindo a dependência de um operador), tecnologias dispendiosas ou apresentam abordagens de análise ineficientes. Este trabalho de investigação encontra assim a sua motivação no potencial impacto que instrumentação não-invasiva, exata e de fácil utilização pode ter na monitorização da condição hemodinâmica e no diagnóstico precoce e acompanhamento de DCVs. Neste contexto, uma nova geração de protótipos baseados na combinação de diferentes tipos de sensores eletromecânicos, bem como um conjunto de algoritmos de processamento de sinal adequados à extração de múltiplos parâmetros hemodinâmicos foram desenvolvidos. Dependendo do marcador de risco cardiovascular a ser avaliado, dois grandes grupos de dispositivos foram projetados. O primeiro grupo, focado na avaliação da rigidez arterial local, explorou uma configuração dupla inovadora com dois sensores acústicos ou piezoelétricos (PZs) para a medição da velocidade da onda de pulso (VOP) e outros índices temporais relevantes, num curto segmento da artéria carótida. O outro grupo, centrado na avaliação contínua da pressão arterial sanguínea (PAS) e onda de pressão arterial (OPA), também na artéria carótida, usou uma unidade vibrador-acelerómetro montada num mesmo suporte que permitiu ao acelerómetro detetar as vibrações produzidas, atenuadas e moduladas em amplitude quando em contacto mecânico com a parede do vaso. Os protótipos desenvolvidos foram extensivamente caracterizados em sistemas de bancada de teste, desenvolvidos para este efeito e capazes de reproduzir a variabilidade de uma ampla gama de situações clinicamente relevantes, bem como em condições in vivo. Relativamente à avaliação da rigidez arterial local, a primeira e segunda gerações de protótipos desenvolvidos apresentaram boa exatidão nos ensaios de resolução temporal realizados em tubos elásticos de bancadas de teste. O algoritmo de correlação cruzada exibiu a capacidade de medir VOPs altas (≈ 19 ms-1 e 14 ms-1) com erros relativos e coeficientes de variação inferiores a 10 % para os diferentes protótipos. Os sinais adquiridos provaram ser robustos e repetíveis, não sofrendo efeitos de crosstalk. Os resultados obtidos no estudo de validação pré-clínica em vinte indivíduos saudáveis com a segunda geração de protótipos foram ainda bastante satisfatórios. As VOPs carotídeas médias obtidas apresentaram uma correlação linear e forte entre si, estando os resultados próximos dos valores obtidos noutros estudos de referência. Além disso, a capacidade de reproduzir perfis de onda pressão distintos usando as sondas PZs foi também mostrada, quer utilizando o processo de desconvolução quer um circuito eletrónico integrador dedicado. No que diz respeito à avaliação da PAS e OPA, o processo de desmodulação produziu excelentes resultados na recuperação da morfologia da onda de pressão em condições de bancada de teste e in vivo. Para os dois protótipos desenvolvidos, várias formas de onda foram extraídas, com exatidão, das portadoras moduladas de aceleração, corrente ou potência elétricas, usando os algoritmos de deteção do envelope e do produto. Na bancada de teste foi possível reproduzir a forma de onda de pressão para posições de aplanação do tubo elástico sucessivamente mais elevadas com um erro quadrático médio de 2.4 ± 0.51 %, quando considerado o melhor método de extração. A eficácia de um novo método de calibração focado na utilização de curvas empíricas que convertem aceleração em pressão foi também demonstrado. Através da conservação da amplitude da portadora de aceleração, foi possível determinar os valores de pressão máximo, mínimo, médio e de pulso com erros relativos inferiores a 10 % em condições de bancada. Além disso, as diferenças de pressão entre o último protótipo desenvolvido e o sistema de referência foram, em média, ≤ 5 ± 8 mmHg, satisfazendo os critérios de exatidão de sistemas de medição de PAS clinicamente validados. Embora estudos de validação clínica sejam ainda necessários, os resultados globais obtidos neste trabalho para os dois principais tipos de protótipos dão bons indicadores quanto à sua utilização como alternativas válidas aos sistemas atualmente disponíveis, tanto em ambientes clínico quanto de investigação.Cardiovascular diseases (CVDs) are the leading cause of death worldwide and largely responsible for the ever increasing costs in healthcare systems. In the last few years, the medical community has demonstrated a great interest in local arterial stiffness, central blood pressure assessment and pressure waveform analysis, due to their predictive values in the development of this type of pathologies. Despite their significance, these hemodynamic parameters remain particularly challenging to measure in standard clinical practice since most available devices require high technical expertise (introducing operator dependence), burdensome technologies and/or present ineffective analysis approaches. This research work finds its motivation in the potential impact that non-invasive, accurate and easy-to-use instrumentation could have on the monitoring of hemodynamic condition and on the diagnosis and control of early stages of CVDs. In this context, a new generation of prototypes based on the combination of different types of electromechanical sensors, along with a set of signal processing algorithms suited to the extraction of multiple hemodynamic parameters were developed. Two major groups of devices were designed depending on the cardiovascular risk marker to be assessed. The first group, focused on local arterial stiffness evaluation, explored an innovative double headed probe configuration of acoustic or piezoelectric (PZ) sensors for the measurement of pulse wave velocity (PWV) and other relevant time-based indices, in a short segment of the carotid artery. The other main group, centered on the continuous assessment of arterial blood pressure (ABP) and arterial pressure waveform (APW), also at the carotid artery, used a vibrator-accelerometer unit mounted in a common support that enabled the accelerometer to sense the produced vibrations, attenuated and modulated in amplitude when in mechanical contact with the vessel wall. The developed prototypes were extensively characterized in test bench systems, purposely built and capable of reproducing the variability of a wide range of clinically relevant situations, as well as in in vivo conditions. Regarding local arterial stiffness evaluation, the first and second generations of developed prototypes presented good accuracy in time resolution experiments on elastic tubes at the test bench. Cross-correlation algorithm exhibited the capability of measuring high PWVs (≈ 19 ms-1 and 14 ms-1) with relative errors and coefficients of variation lower than 10 % for the different prototypes. The acquired signals proved to be robust and repeatable, not suffering from crosstalk effect. The results obtained in a pre-clinical validation trial of twenty healthy subjects with the second generation of prototypes were very satisfactory, demonstrating that the mean carotid PWVs obtained were linearly and strongly correlated and were in agreement with other reference studies. Additionally, the ability to reproduce distinct wave pressure profiles using the PZs probes was also shown, either using the demodulation algorithm-based process or a special circuit for electronic integration. Concerning APW and ABP assessment, the demodulation process yielded excellent results in recovering the morphology of pressure wave in test bench and in in vivo conditions. For the two developed prototypes, several waveforms were accurately extracted from the acceleration, current or power modulated carriers using the envelope and product detector algorithms. It was possible to reproduce the pressure waveform for successive higher applanation positions of the elastic tube at the test bench with a root mean square error of 2.4 ± 0.51 %, when considering the best extracting method. The effectiveness of a novel calibration method focused on the use of empirical curves which convert acceleration into pressure was also demonstrated. Through the conservation of the acceleration carrier amplitude, it was possible to determine the maximum, minimum, mean and pulse pressure values with relative errors lower than 10 % in bench conditions. Also, the mean pressure differences between the latest prototype and the reference system were, on average, ≤ 5 ± 8 mmHg, satisfying the accuracy criteria of clinically validated ABP devices. Although clinical validation studies are still required, the global results obtained in this work for the two major types of prototypes provide great prospects regarding their use as valid alternatives to currently available systems, both in clinical and research settings

Physics division annual report 2005.

This report highlights the research performed in 2005 in the Physics Division of Argonne National Laboratory. The Division's programs include operation of ATLAS as a national user facility, nuclear structure and reaction research, nuclear theory, medium energy nuclear research and accelerator research and development. The mission of Nuclear Physics is to understand the origin, evolution and structure of baryonic matter in the universe--the matter that makes up stars, planets and human life itself. The Division's research focuses on innovative new ways to address this mission and 2005 was a year of great progress. One of the most exciting developments is the initiation of the Californium Rare Ion Breeder Upgrade, CARIBU. By combining a Cf-252 fission source, the gas catcher technology developed for rare isotope beams, a high-resolution isobar separator, and charge breeding ECR technology, CARIBU will make hundreds of new neutron-rich isotope beams available for research. The cover illustration shows the anticipated intensities of low-energy beams that become available for low-energy experiments and for injection into ATLAS for reacceleration. CARIBU will be completed in early 2009 and provide us with considerable experience in many of the technologies developed for a future high intensity exotic beam facility. Notable results in research at ATLAS include a measurement of the isomeric states in {sup 252}No that helps pin down the single particle structure expected for superheavy elements, and a new low-background measurement of {sup 16}N beta-decay to determine the {sup 12}C({alpha},{gamma}){sup 16}O reaction rate that is so important in astrophysical environments. Precise mass measurements shed new light on the unitarity of the quark weak-mixing matrix in the search for physics beyond the standard model. ATLAS operated for 4686 hours of research in FY2005 while achieving 95% efficiency of beam delivery for experiments. In Medium-Energy Physics, radium isotopes were trapped in an atom trap for the first time, a major milestone in an innovative search for the violation of time-reversal symmetry. New results from HERMES establish that strange quarks carry little of the spin of the proton and precise results have been obtained at JLAB on the changes in quark distributions in light nuclei. New theoretical results reveal that the nature of the surfaces of strange quark stars. Green's function Monte Carlo techniques have been extended to scattering problems and show great promise for the accurate calculation, from first principles, of important astrophysical reactions. Flame propagation in type 1A supernova has been simulated, a numerical process that requires considering length scales that vary by factors of eight to twelve orders of magnitude. Argonne continues to lead in the development and exploitation of the new technical concepts that will truly make an advanced exotic beam facility, in the words of NSAC, 'the world-leading facility for research in nuclear structure and nuclear astrophysics'. Our science and our technology continue to point the way to this major advance. It is a tremendously exciting time in science for these new capabilities hold the keys to unlocking important secrets of nature. The great progress that has been made in meeting the exciting intellectual challenges of modern nuclear physics reflects the talents and dedication of the Physics Division staff and the visitors, guests and students who bring so much to the research