Rigid and non-rigid point-based medical image registration

The primary goal of this dissertation is to develop point-based rigid and non-rigid image registration methods that have better accuracy than existing methods. We first present point-based PoIRe, which provides the framework for point-based global rigid registrations. It allows a choice of different search strategies including (a) branch-and-bound, (b) probabilistic hill-climbing, and (c) a novel hybrid method that takes advantage of the best characteristics of the other two methods. We use a robust similarity measure that is insensitive to noise, which is often introduced during feature extraction. We show the robustness of PoIRe using it to register images obtained with an electronic portal imaging device (EPID), which have large amounts of scatter and low contrast. To evaluate PoIRe we used (a) simulated images and (b) images with fiducial markers; PoIRe was extensively tested with 2D EPID images and images generated by 3D Computer Tomography (CT) and Magnetic Resonance (MR) images. PoIRe was also evaluated using benchmark data sets from the blind retrospective evaluation project (RIRE). We show that PoIRe is better than existing methods such as Iterative Closest Point (ICP) and methods based on mutual information. We also present a novel point-based local non-rigid shape registration algorithm. We extend the robust similarity measure used in PoIRe to non-rigid registrations adapting it to a free form deformation (FFD) model and making it robust to local minima, which is a drawback common to existing non-rigid point-based methods. For non-rigid registrations we show that it performs better than existing methods and that is less sensitive to starting conditions. We test our non-rigid registration method using available benchmark data sets for shape registration. Finally, we also explore the extraction of features invariant to changes in perspective and illumination, and explore how they can help improve the accuracy of multi-modal registration. For multimodal registration of EPID-DRR images we present a method based on a local descriptor defined by a vector of complex responses to a circular Gabor filter.

Efficacy of educational interventions to reduce homophobia on the *college campus

Homophobic attitudes, irrational fears and negative attitudes against gay men and lesbians exist on the college campus (Lance, 2002; Rankin, 2003). Educators wishing to change these attitudes need to know what types of intervention would be effective. This investigation empirically assessed the degree of homophobia in a group of college students, and changes in the degree of homophobia following two levels of educational intervention that were rooted in educational theories and social contact theory. A 25-item scale developed by Hudson and Ricketts to measure the degree of negative attitudes toward gay men and lesbians was used in English classes at a southeastern university. This study examined the relationship between different demographic groups and the degree of change obtained as a result of the interventions. ^ Findings did not suggest that either interaction with gay men and lesbians in the form of a speaker panel or viewing a “coming out” episode of the Ellen show reduced homophobia to a significant extent. Results did demonstrate the Caribbeans and right wing authoritarians tend to be more homophobic. Post hoc analysis investigated factors that may have contaminated the interventions. Speaker Identification was a significant predictor of change in degree of homophobia. ^

Rigid and Non-rigid Point-based Medical Image Registration

The primary goal of this dissertation is to develop point-based rigid and non-rigid image registration methods that have better accuracy than existing methods. We first present point-based PoIRe, which provides the framework for point-based global rigid registrations. It allows a choice of different search strategies including (a) branch-and-bound, (b) probabilistic hill-climbing, and (c) a novel hybrid method that takes advantage of the best characteristics of the other two methods. We use a robust similarity measure that is insensitive to noise, which is often introduced during feature extraction. We show the robustness of PoIRe using it to register images obtained with an electronic portal imaging device (EPID), which have large amounts of scatter and low contrast. To evaluate PoIRe we used (a) simulated images and (b) images with fiducial markers; PoIRe was extensively tested with 2D EPID images and images generated by 3D Computer Tomography (CT) and Magnetic Resonance (MR) images. PoIRe was also evaluated using benchmark data sets from the blind retrospective evaluation project (RIRE). We show that PoIRe is better than existing methods such as Iterative Closest Point (ICP) and methods based on mutual information. We also present a novel point-based local non-rigid shape registration algorithm. We extend the robust similarity measure used in PoIRe to non-rigid registrations adapting it to a free form deformation (FFD) model and making it robust to local minima, which is a drawback common to existing non-rigid point-based methods. For non-rigid registrations we show that it performs better than existing methods and that is less sensitive to starting conditions. We test our non-rigid registration method using available benchmark data sets for shape registration. Finally, we also explore the extraction of features invariant to changes in perspective and illumination, and explore how they can help improve the accuracy of multi-modal registration. For multimodal registration of EPID-DRR images we present a method based on a local descriptor defined by a vector of complex responses to a circular Gabor filter.

Efficacy of Educational Interventions to Reduce Homophobia on the College Campus

Homophobic attitudes, irrational fears and negative attitudes against gay men and lesbians exist on the college campus (Lance, 2002; Rankin, 2003). Educators wishing to change these attitudes need to know what types of intervention would be effective. This investigation empirically assessed the degree of homophobia in a group of college students, and changes in the degree of homophobia following two levels of educational intervention that were rooted in educational theories and social contact theory. A 25-item scale developed by Hudson and Ricketts to measure the degree of negative attitudes toward gay men and lesbians was used in English classes at a southeastern university. This study examined the relationship between different demographic groups and the degree of change obtained as a result of the interventions. Findings did not suggest that either interaction with gay men and lesbians in the form of a speaker panel or viewing a “coming out” episode of the Ellen show reduced homophobia to a significant extent. Results did demonstrate the Caribbeans and right wing authoritarians tend to be more homophobic. Post hoc analysis investigated factors that may have contaminated the interventions. Speaker Identification was a significant predictor of change in degree of homophobia.

Parallel Problem Solving from Nature – PPSN XIV:14th International Conference, Edinburgh, UK, September 17-21, 2016, Proceedings

This book constitutes the refereed proceedings of the 14th International Conference on Parallel Problem Solving from Nature, PPSN 2016, held in Edinburgh, UK, in September 2016. The total of 93 revised full papers were carefully reviewed and selected from 224 submissions. The meeting began with four workshops which offered an ideal opportunity to explore specific topics in intelligent transportation Workshop, landscape-aware heuristic search, natural computing in scheduling and timetabling, and advances in multi-modal optimization. PPSN XIV also included sixteen free tutorials to give us all the opportunity to learn about new aspects: gray box optimization in theory; theory of evolutionary computation; graph-based and cartesian genetic programming; theory of parallel evolutionary algorithms; promoting diversity in evolutionary optimization: why and how; evolutionary multi-objective optimization; intelligent systems for smart cities; advances on multi-modal optimization; evolutionary computation in cryptography; evolutionary robotics - a practical guide to experiment with real hardware; evolutionary algorithms and hyper-heuristics; a bridge between optimization over manifolds and evolutionary computation; implementing evolutionary algorithms in the cloud; the attainment function approach to performance evaluation in EMO; runtime analysis of evolutionary algorithms: basic introduction; meta-model assisted (evolutionary) optimization. The papers are organized in topical sections on adaption, self-adaption and parameter tuning; differential evolution and swarm intelligence; dynamic, uncertain and constrained environments; genetic programming; multi-objective, many-objective and multi-level optimization; parallel algorithms and hardware issues; real-word applications and modeling; theory; diversity and landscape analysis.

Deep Head Pose: Gaze-Direction Estimation in Multimodal Video

In this paper we present a convolutional neuralnetwork (CNN)-based model for human head pose estimation inlow-resolution multi-modal RGB-D data. We pose the problemas one of classification of human gazing direction. We furtherfine-tune a regressor based on the learned deep classifier. Next wecombine the two models (classification and regression) to estimateapproximate regression confidence. We present state-of-the-artresults in datasets that span the range of high-resolution humanrobot interaction (close up faces plus depth information) data tochallenging low resolution outdoor surveillance data. We buildupon our robust head-pose estimation and further introduce anew visual attention model to recover interaction with theenvironment. Using this probabilistic model, we show thatmany higher level scene understanding like human-human/sceneinteraction detection can be achieved. Our solution runs inreal-time on commercial hardware

Evaluating laser-driven Bremsstrahlung radiation sources for imaging and analysis of nuclear waste packages

A small scale sample nuclear waste package, consisting of a 28 mm diameter uranium penny encased in grout, was imaged by absorption contrast radiography using a single pulse exposure from an X-ray source driven by a high-power laser. The Vulcan laser was used to deliver a focused pulse of photons to a tantalum foil, in order to generate a bright burst of highly penetrating X-rays (with energy >500 keV), with a source size of <0.5 mm. BAS-TR and BAS-SR image plates were used for image capture, alongside a newly developed Thalium doped Caesium Iodide scintillator-based detector coupled to CCD chips. The uranium penny was clearly resolved to sub-mm accuracy over a 30 cm2 scan area from a single shot acquisition. In addition, neutron generation was demonstrated in situ with the X-ray beam, with a single shot, thus demonstrating the potential for multi-modal criticality testing of waste materials. This feasibility study successfully demonstrated non-destructive radiography of encapsulated, high density, nuclear material. With recent developments of high-power laser systems, to 10 Hz operation, a laser-driven multi-modal beamline for waste monitoring applications is envisioned.

Human traces in urban places.

Over the last two centuries many major cities have undergone large-scale modernisation that has led to the growing sense of homogenisation associated with such locales across the globe. The fractal logic that is at the heart of so many urban settings, where the whole system is made up of parts that are identical to the whole, seems to serve in making anonymous everyday experiences. Public transport and its corresponding street furniture, if thoughtfully designed and planned, has the potential to form an integral element in the promotion of a sense of identity, interconnectedness and flow within a city. Furthermore, bus stops, benches, litter bins, curb-sides, posts and pavements, to mention a few, offer interesting cases to consider how people truly engage with contemporary urban spaces. These objects—part of routine and made familiar—are elements of daily lives that are ingredients towards visual and multi-modal experiences. In addition, these are places where individuals encounter sociality and materiality in ordinary and sometimes extraordinary ways. This paper uses a visual ethnographic approach towards exploring the human traces of routine activities that have an impact on the cityscape. An Investigation of these details found within the urban landscape lead us towards understanding how we engage with and navigate cities. This is essentially an urban archaeological study that looks to reveal how non-designed phenomenon in urban places can contribute to our image of a city, providing a reflection on homogeneity within the built environment. Our visual ethnography focuses on six major cities: two each in Britain, Europe and North America. The findings of this work illustrate through visual analyses three key characteristics: first, how urban spaces are transformed intentionally and unintentionally; second, how transformations are practical, functional, beautiful and sometimes ridiculous; third, how transformations reveal values around visual and multi-modal experiences inherent to people.

Configuring an open pipeline fulfilment system - a simulation study in an automotive context

Automotive producers are adopting multi-modal fulfillment models in which customers can be fulfilled by products from stock, by allocating as yet unmade products that are in the planning pipeline, or by building a product to order. This study explores how fulfillment is sensitive to several parameters of the system and how they interact with different methods for sequencing products into the production plan.

Robust solutions of bi-blend recipe optimization with quadratic constraints

Production companies use raw materials to compose end-products. They often make different products with the same raw materials. In this research, the focus lies on the production of two end-products consisting of (partly) the same raw materials as cheap as possible. Each of the products has its own demand and quality requirements consisting of quadratic constraints. The minimization of the costs, given the quadratic constraints is a global optimization problem, which can be difficult because of possible local optima. Therefore, the multi modal character of the (bi-) blend problem is investigated. Standard optimization packages (solvers) in Matlab and GAMS were tested on their ability to solve the problem. In total 20 test cases were generated and taken from literature to test solvers on their effectiveness and efficiency to solve the problem. The research also gives insight in adjusting the quadratic constraints of the problem in order to make a robust problem formulation of the bi-blend problem.

Coupling instrumentation and methodology in the search for traces of life on the early Earth and Mars

Evaluating the nature of the earliest, often controversial, traces of life in the geological record (dating to the Palaeoarchaean, up to ~3.5 billion years before the present) is of fundamental relevance for placing constraints on the potential that life emerged on Mars at approximately the same time (the Noachian period). In their earliest histories, the two planets shared many palaeoenvironmental similarities, before the surface of Mars rapidly became inhospitable to life as we know it. Multi-scalar, multi-modal analyses of fossiliferous rocks from the Barberton greenstone belt of South Africa and the East Pilbara terrane of Western Australia are a window onto primitive prokaryotic ecoystems. Complementary petrographic, morphological, (bio)geochemical and nanostructural analyses of chert horizons and the carbonaceous material within using a wide range of techniques – including optical microscopy, SEM-EDS, Raman spectroscopy, PIXE, µCT, laser ablation ICP-MS, high-resolution TEM-based analytical techniques and secondary ion mass spectrometry – can characterise, at scales from macroscopic to nanoscopic, the fossilised biomes of the earliest Earth. These approaches enable the definition of the palaeoenvironments, and potentially metabolic networks, preserved in ancient rocks. Modifying these protocols is necessary for Martian exploration using rovers, since the range and power of space instrumentation is significantly reduced relative to terrestrial laboratories. Understanding the crucial observations possible using highly complementary rover-based payloads is therefore critical in scientific protocols aiming to detect traces of life on Mars.

Statistical Multi-Objective Structural Damage Identification based on Dynamic Parameters

Evolutionary algorithms are suitable to solve damage identification problems in a multi-objective context. However, the performance of these methods can deteriorate quickly with increasing noise intensities originating numerous uncertainties. In this paper, a statistic structural damage detection method formulated in a multi-objective context is proposed. The statistic analysis is implemented to take into account the uncertainties existing in the structural model and measured structural modal parameters. The presented method is verified by a number of simulated damage scenarios. The effects of noise and damage levels on damage detection are investigated.

RFID together with multi-agent systems to control global value chains

Nowadays, the cooperative intelligent transport systems are part of a largest system. Transportations are modal operations integrated in logistics and, logistics is the main process of the supply chain management. The supply chain strategic management as a simultaneous local and global value chain is a collaborative/cooperative organization of stakeholders, many times in co-opetition, to perform a service to the customers respecting the time, place, price and quality levels. The transportation, like other logistics operations must add value, which is achieved in this case through compression lead times and order fulfillments. The complex supplier's network and the distribution channels must be efficient and the integral visibility (monitoring and tracing) of supply chain is a significant source of competitive advantage. Nowadays, the competition is not discussed between companies but among supply chains. This paper aims to evidence the current and emerging manufacturing and logistics system challenges as a new field of opportunities for the automation and control systems research community. Furthermore, the paper forecasts the use of radio frequency identification (RFID) technologies integrated into an information and communication technologies (ICT) framework based on distributed artificial intelligence (DAI) supported by a multi-agent system (MAS), as the most value advantage of supply chain management (SCM) in a cooperative intelligent logistics systems. Logistical platforms (production or distribution) as nodes of added value of supplying and distribution networks are proposed as critical points of the visibility of the inventory, where these technological needs are more evident.

Identification of different heart tissues from MRI C-SENC images using an unsupervised multi-stage fuzzy clustering technique.

PURPOSE: To objectively characterize different heart tissues from functional and viability images provided by composite-strain-encoding (C-SENC) MRI. MATERIALS AND METHODS: C-SENC is a new MRI technique for simultaneously acquiring cardiac functional and viability images. In this work, an unsupervised multi-stage fuzzy clustering method is proposed to identify different heart tissues in the C-SENC images. The method is based on sequential application of the fuzzy c-means (FCM) and iterative self-organizing data (ISODATA) clustering algorithms. The proposed method is tested on simulated heart images and on images from nine patients with and without myocardial infarction (MI). The resulting clustered images are compared with MRI delayed-enhancement (DE) viability images for determining MI. Also, Bland-Altman analysis is conducted between the two methods. RESULTS: Normal myocardium, infarcted myocardium, and blood are correctly identified using the proposed method. The clustered images correctly identified 90 +/- 4% of the pixels defined as infarct in the DE images. In addition, 89 +/- 5% of the pixels defined as infarct in the clustered images were also defined as infarct in DE images. The Bland-Altman results show no bias between the two methods in identifying MI. CONCLUSION: The proposed technique allows for objectively identifying divergent heart tissues, which would be potentially important for clinical decision-making in patients with MI.

Identification des bases génétiques des myopathies à multi-minicores avec ou sans cardiomyopathie

Thèse réalisée en cotutelle avec l'Université Pierre et Marie Curie, Paris 6(UPMC, Paris, France).