Methodology for registration of distended recutms in pelvic CT studies

Purpose: Accurate delineation of the rectum is of high importance in off-line adaptive radiation therapy since it is a major dose-limiting organ in prostate cancer radiotherapy. The intensity-based deformable image registration (DIR) methods cannot create a correct spatial transformation if there is no correspondence between the template and the target images. The variation of rectal filling, gas, or feces, creates a noncorrespondence in image intensities that becomes a great obstacle for intensity-based DIR. Methods: In this study the authors have designed and implemented a semiautomatic method to create a rectum mask in pelvic computed tomography (CT) images. The method, that includes a DIR based on the demons algorithm, has been tested in 13 prostate cancer cases, each comprising of two CT scans, for a total of 26 CT scans. Results: The use of the manual segmentation in the planning image and the proposed rectum mask method (RMM) method in the daily image leads to an improvement in the DIR performance in pelvic CT images, obtaining a mean value of overlap volume index = 0.89, close to the values obtained using the manual segmentations in both images. Conclusions: The application of the RMM method in the daily image and the manual segmentations in the planning image during prostate cancer treatments increases the performance of the registration in presence of rectal fillings, obtaining very good agreement with a physician's manual contours.

Methodology for registration of distended rectums in pelvic CT studies

Purpose: Accurate delineation of the rectum is of high importance in off-line adaptive radiation therapy since it is a major dose-limiting organ in prostate cancer radiotherapy. The intensity-based deformable image registration (DIR) methods cannot create a correct spatial transformation if there is no correspondence between the template and the target images. The variation of rectal filling, gas, or feces, creates a noncorrespondence in image intensities that becomes a great obstacle for intensity-based DIR. Methods: In this study the authors have designed and implemented a semiautomatic method to create a rectum mask in pelvic computed tomography (CT) images. The method, that includes a DIR based on the demons algorithm, has been tested in 13 prostate cancer cases, each comprising of two CT scans, for a total of 26 CT scans. Results: The use of the manual segmentation in the planning image and the proposed rectum mask method (RMM) method in the daily image leads to an improvement in the DIR performance in pelvic CT images, obtaining a mean value of overlap volume index = 0.89, close to the values obtained using the manual segmentations in both images. Conclusions: The application of the RMM method in the daily image and the manual segmentations in the planning image during prostate cancer treatments increases the performance of the registration in presence of rectal fillings, obtaining very good agreement with a physician's manual contours.

Fault detection and isolation on a noisy nonlinear circuit

In this paper fault detection and isolation (FDI) schemes are applied in the context of the surveillance of emerging faults in an electrical circuit. The FDI problem is studied on a noisy nonlinear circuit, where both abrupt and incipient faults in the voltage source are considered. A rigorous analysis of fault detectability precedes the application of the fault detection (FD) scheme; then, the fault isolation (FI) phase is accomplished with two alternative FI approaches, proposed as new extensions of that FD approach. Numerical simulations illustrate the applicability of the mentioned schemes.

A Propose-and-revise System for Real-time Traffic Management

The aim of this paper is to describe an intelligent system for the problem of real time road traffic control. The purpose of the system is to help traffic engineers in the selection of the state of traffic control devices on real time, using data recorded by traffic detectors on motorways. The system follows an advanced knowledge-based approach that implements an abstract generic problem solving method, called propose-and-revise, which was proposed in Artificial Intelligence, within the knowledge engineering field, as a standard cognitive structure oriented to solve configuration design problems. The paper presents the knowledge model of such a system together with the strategy of inference and describes how it was applied for the case of the M-40 urban ring for the city of Madrid.

Towards Accurate and Efficient Description of Excited States

Thesis (Ph.D.)--University of Washington, 2016-06

Improving the physical status and quality of life of women treated for breast cancer: A pilot study of a structured exercise intervention

Background and Objectives: This pilot project assessed the acceptability of a mixed-type, moderate-intensity exercise programme following breast cancer treatment, and the impact on presence of lymphoedema, fitness, body composition, fatigue, mood and quality of life. Methods: Ten women completed the programme and measures of fitness (submaximal ergometer test), body composition (bio-electrical impedance), lympoedema (bio-electrical impedance and arm circumferences), fatigue (revised Piper Fatigue Scale), mood (Hospital Anxiety and Depression Scale), quality of life (FACT-B) and general well-being, at baseline, completion of the programme, and 6-week and 3-month follow-up. Results: Participation in the programme caused no adverse effect on the presence of lymphoedema. There was a trend towards reduction in fatigue and improved quality of life across the testing phases. Women rated the programme extremely favourably, citing benefits of the support of other women, trained guidance, and the opportunity to experience different types of exercise. Conclusions: A mixed-type, moderate-intensity exercise program in a group format is acceptable to women following breast cancer treatment, with the potential to reduce fatigue and improve quality of life, without exacerbating or precipitating lymphoedema. This pilot work needs to be confirmed in larger randomised studies. (C) 2004 Wiley-Liss, Inc.

Identifying sequence regions undergoing conformational change via predicted continuum secondary structure

Motivation: Conformational flexibility is essential to the function of many proteins, e.g. catalytic activity. To assist efforts in determining and exploring the functional properties of a protein, it is desirable to automatically identify regions that are prone to undergo conformational changes. It was recently shown that a probabilistic predictor of continuum secondary structure is more accurate than categorical predictors for structurally ambivalent sequence regions, suggesting that such models are suited to characterize protein flexibility. Results: We develop a computational method for identifying regions that are prone to conformational change directly from the amino acid sequence. The method uses the entropy of the probabilistic output of an 8-class continuum secondary structure predictor. Results for 171 unique amino acid sequences with well-characterized variable structure (identified in the 'Macromolecular movements database') indicate that the method is highly sensitive at identifying flexible protein regions, but false positives remain a problem. The method can be used to explore conformational flexibility of proteins (including hypothetical or synthetic ones) whose structure is yet to be determined experimentally.

Building user commitment to implementing a knowledge management strategy

In the IS literature, commitment is typically considered to involve organizational or managerial support for a system and not that of its users. This paper however reports on a field study involving 16 organizations that attempted to build user involvement in developing a knowledge management strategy by having them design it. Twenty-two IT-supported group workshops (involving 183 users) were run to develop action plans for better knowledge management that users would like to see implemented. Each workshop adopted the same problem structuring technique to assist group members develop a politically feasible action plan to which they were psychologically and emotionally dedicated. In addition to reviewing the problem structuring method, this paper provides qualitative insight into the factors a knowledge management strategy should have to encourage user commitment. © 2004 Elsevier B.V. All rights reserved.

Journey making group workshops as a research tool

Problem-structuring group workshops can be used in organizations as a consulting tool and as a research tool. One example of the latter is using a problem-structuring method (PSM) to help a group tackle an organizational issue; meanwhile, researchers collect the participants' initial views, discussion of divergent views, the negotiated agreement, and the reasoning for outcomes emerging. Technology can help by supporting participants in freely sharing their opinions and by logging data for post-workshop analyses. For example, computers let participants share views anonymously and without being influenced by others (as well as logging those views), and video-cameras can record discussions and intra-group dynamics. This paper evaluates whether technology-supported Journey Making workshops can be effective research tools that can capture quality research data when compared against theoretical performance benchmarks and other qualitative research tools. © 2006 Operational Research Society Ltd. All rights reserved.

Mass transfer coefficient for drying of moist particulate in a bubbling fluidized bed

Experiments on drying of moist particles by ambient air were carried out to measure the mass transfer coefficient in a bubbling fluidized bed. Fine glass beads of mean diameter 125?µm were used as the bed material. Throughout the drying process, the dynamic material distribution was recorded by electrical capacitance tomography (ECT) and the exit air condition was recorded by a temperature/humidity probe. The ECT data were used to obtain qualitative and quantitative information on the bubble characteristics. The exit air moisture content was used to determine the water content in the bed. The measured overall mass transfer coefficient was in the range of 0.0145–0.021?m/s. A simple model based on the available correlations for bubble-cloud and cloud-dense interchange (two-region model) was used to predict the overall mass transfer coefficient. Comparison between the measured and predicted mass transfer coefficient have shown reasonable agreement. The results were also used to determine the relative importance of the two transfer regions.

Palette-colouring: a belief propagation approach

We consider a variation of the prototype combinatorial optimization problem known as graph colouring. Our optimization goal is to colour the vertices of a graph with a fixed number of colours, in a way to maximize the number of different colours present in the set of nearest neighbours of each given vertex. This problem, which we pictorially call palette-colouring, has been recently addressed as a basic example of a problem arising in the context of distributed data storage. Even though it has not been proved to be NP-complete, random search algorithms find the problem hard to solve. Heuristics based on a naive belief propagation algorithm are observed to work quite well in certain conditions. In this paper, we build upon the mentioned result, working out the correct belief propagation algorithm, which needs to take into account the many-body nature of the constraints present in this problem. This method improves the naive belief propagation approach at the cost of increased computational effort. We also investigate the emergence of a satisfiable-to-unsatisfiable 'phase transition' as a function of the vertex mean degree, for different ensembles of sparse random graphs in the large size ('thermodynamic') limit.

Decision Trees for Applicability of Evolution Rules in Transition P Systems

Transition P Systems are a parallel and distributed computational model based on the notion of the cellular membrane structure. Each membrane determines a region that encloses a multiset of objects and evolution rules. Transition P Systems evolve through transitions between two consecutive configurations that are determined by the membrane structure and multisets present inside membranes. Moreover, transitions between two consecutive configurations are provided by an exhaustive non-deterministic and parallel application of active evolution rules subset inside each membrane of the P system. But, to establish the active evolution rules subset, it is required the previous calculation of useful and applicable rules. Hence, computation of applicable evolution rules subset is critical for the whole evolution process efficiency, because it is performed in parallel inside each membrane in every evolution step. The work presented here shows advantages of incorporating decision trees in the evolution rules applicability algorithm. In order to it, necessary formalizations will be presented to consider this as a classification problem, the method to obtain the necessary decision tree automatically generated and the new algorithm for applicability based on it.

Development of safety performance functions for empirical Bayes estimation of crash reduction factors

Crash reduction factors (CRFs) are used to estimate the potential number of traffic crashes expected to be prevented from investment in safety improvement projects. The method used to develop CRFs in Florida has been based on the commonly used before-and-after approach. This approach suffers from a widely recognized problem known as regression-to-the-mean (RTM). The Empirical Bayes (EB) method has been introduced as a means to addressing the RTM problem. This method requires the information from both the treatment and reference sites in order to predict the expected number of crashes had the safety improvement projects at the treatment sites not been implemented. The information from the reference sites is estimated from a safety performance function (SPF), which is a mathematical relationship that links crashes to traffic exposure. The objective of this dissertation was to develop the SPFs for different functional classes of the Florida State Highway System. Crash data from years 2001 through 2003 along with traffic and geometric data were used in the SPF model development. SPFs for both rural and urban roadway categories were developed. The modeling data used were based on one-mile segments that contain homogeneous traffic and geometric conditions within each segment. Segments involving intersections were excluded. The scatter plots of data show that the relationships between crashes and traffic exposure are nonlinear, that crashes increase with traffic exposure in an increasing rate. Four regression models, namely, Poisson (PRM), Negative Binomial (NBRM), zero-inflated Poisson (ZIP), and zero-inflated Negative Binomial (ZINB), were fitted to the one-mile segment records for individual roadway categories. The best model was selected for each category based on a combination of the Likelihood Ratio test, the Vuong statistical test, and the Akaike's Information Criterion (AIC). The NBRM model was found to be appropriate for only one category and the ZINB model was found to be more appropriate for six other categories. The overall results show that the Negative Binomial distribution model generally provides a better fit for the data than the Poisson distribution model. In addition, the ZINB model was found to give the best fit when the count data exhibit excess zeros and over-dispersion for most of the roadway categories. While model validation shows that most data points fall within the 95% prediction intervals of the models developed, the Pearson goodness-of-fit measure does not show statistical significance. This is expected as traffic volume is only one of the many factors contributing to the overall crash experience, and that the SPFs are to be applied in conjunction with Accident Modification Factors (AMFs) to further account for the safety impacts of major geometric features before arriving at the final crash prediction. However, with improved traffic and crash data quality, the crash prediction power of SPF models may be further improved.

Real-time biosensor for the assessment of nanotoxicity and cancer electrotherapy

Knowledge of cell electronics has led to their integration to medicine either by physically interfacing electronic devices with biological systems or by using electronics for both detection and characterization of biological materials. In this dissertation, an electrical impedance sensor (EIS) was used to measure the electrode surface impedance changes from cell samples of human and environmental toxicity of nanoscale materials in 2D and 3D cell culture models. The impedimetric response of human lung fibroblasts and rainbow trout gill epithelial cells when exposed to various nanomaterials was tested to determine their kinetic effects towards the cells and to demonstrate the biosensor's ability to monitor nanotoxicity in real-time. Further, the EIS allowed rapid, real-time and multi-sample analysis creating a versatile, noninvasive tool that is able to provide quantitative information with respect to alteration in cellular function. We then extended the application of the unique capabilities of the EIS to do real-time analysis of cancer cell response to externally applied alternating electric fields at different intermediate frequencies and low-intensity. Decreases in the growth profiles of the ovarian and breast cancer cells were observed with the application of 200 and 100 kHz, respectively, indicating specific inhibitory effects on dividing cells in culture in contrast to the non-cancerous HUVECs and mammary epithelial cells. We then sought to enhance the effects of the electric field by altering the cancer cell's electronegative membrane properties with HER2 antibody functionalized nanoparticles. An Annexin V/EthD-III assay and zeta potential were performed to determine the cell death mechanism indicating apoptosis and a decrease in zeta potential with the incorporation of the nanoparticles. With more negatively charged HER2-AuNPs attached to the cancer cell membrane, the decrease in membrane potential would thus leave the cells more vulnerable to the detrimental effects of the applied electric field due to the decrease in surface charge. Therefore, by altering the cell membrane potential, one could possibly control the fate of the cell. This whole cell-based biosensor will enhance our understanding of the responsiveness of cancer cells to electric field therapy and demonstrate potential therapeutic opportunities for electric field therapy in the treatment of cancer.