Innovations in the Analysis of Chandra-ACIS Observations

As members of the instrument team for the Advanced CCD Imaging Spectrometer (ACIS) on NASA's Chandra X-ray Observatory and as Chandra General Observers, we have developed a wide variety of data analysis methods that we believe are useful to the Chandra community, and have constructed a significant body of publicly-available software (the ACIS Extract package) addressing important ACIS data and science analysis tasks. This paper seeks to describe these data analysis methods for two purposes: to document the data analysis work performed in our own science projects, and to help other ACIS observers judge whether these methods may be useful in their own projects (regardless of what tools and procedures they choose to implement those methods). The ACIS data analysis recommendations we offer here address much of the workflow in a typical ACIS project, including data preparation, point source detection via both wavelet decomposition and image reconstruction, masking point sources, identification of diffuse structures, event extraction for both point and diffuse sources, merging extractions from multiple observations, nonparametric broad-band photometry, analysis of low-count spectra, and automation of these tasks. Many of the innovations presented here arise from several, often interwoven, complications that are found in many Chandra projects: large numbers of point sources (hundreds to several thousand), faint point sources, misaligned multiple observations of an astronomical field, point source crowding, and scientifically relevant diffuse emission.Comment: Accepted by the ApJ, 2010 Mar 10 (\#343576) 39 pages, 16 figure

The investigation of a method to generate conformal lattice structures for additive manufacturing

Additive manufacturing (AM) allows a geometric complexity in products not seen in conventional manufacturing. This geometric freedom facilitates the design and fabrication of conformal hierarchical structures. Entire parts or regions of a part can be populated with lattice structure, designed to exhibit properties that differ from the solid material used in fabrication. Current computer aided design (CAD) software used to design products is not suitable for the generation of lattice structure models. Although conceptually simple, the memory requirements to store a virtual CAD model of a lattice structure are prohibitively high. Conventional CAD software defines geometry through boundary representation (B-rep); shapes are described by the connectivity of faces, edges and vertices. While useful for representing accurate models of complex shape, the sheer quantity of individual surfaces required to represent each of the relatively simple individual struts that comprise a lattice structure ensure that memory limitations are soon reached. Additionally, the conventional data flow from CAD to manufactured part is arduous, involving several conversions between file formats. As well as a lengthy process, each conversion risks the generation of geometric errors that must be fixed before manufacture. A method was developed to specifically generate large arrays of lattice structures, based on a general voxel modelling method identified in the literature review. The method is much less sensitive to geometric complexity than conventional methods and thus facilitates the design of considerably more complex structures. The ability to grade structure designs across regions of a part (termed functional grading ) was also investigated, as well as a method to retain connectivity between boundary struts of a conformal structure. In addition, the method streamlines the data flow from design to manufacture: earlier steps of the data conversion process are bypassed entirely. The effect of the modelling method on surface roughness of parts produced was investigated, as voxel models define boundaries with discrete, stepped blocks. It was concluded that the effect of this stepping on surface roughness was minimal. This thesis concludes with suggestions for further work to improve the efficiency, capability and usability of the conformal structure method developed in this work

Computational models for stuctural analysis of retinal images

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University LondonThe evaluation of retina structures has been of great interest because it could be used as a non-intrusive diagnosis in modern ophthalmology to detect many important eye diseases as well as cardiovascular disorders. A variety of retinal image analysis tools have been developed to assist ophthalmologists and eye diseases experts by reducing the time required in eye screening, optimising the costs as well as providing efficient disease treatment and management systems. A key component in these tools is the segmentation and quantification of retina structures. However, the imaging artefacts such as noise, intensity homogeneity and the overlapping tissue of retina structures can cause significant degradations to the performance of these automated image analysis tools. This thesis aims to provide robust and reliable automated retinal image analysis technique to allow for early detection of various retinal and other diseases. In particular, four innovative segmentation methods have been proposed, including two for retinal vessel network segmentation, two for optic disc segmentation and one for retina nerve fibre layers detection. First, three pre-processing operations are combined in the segmentation method to remove noise and enhance the appearance of the blood vessel in the image, and a Mixture of Gaussians is used to extract the blood vessel tree. Second, a graph cut segmentation approach is introduced, which incorporates the mechanism of vectors flux into the graph formulation to allow for the segmentation of very narrow blood vessels. Third, the optic disc segmentation is performed using two alternative methods: the Markov random field image reconstruction approach detects the optic disc by removing the blood vessels from the optic disc area, and the graph cut with compensation factor method achieves that using prior information of the blood vessels. Fourth, the boundaries of the retinal nerve fibre layer (RNFL) are detected by adapting a graph cut segmentation technique that includes a kernel-induced space and a continuous multiplier based max-flow algorithm. The strong experimental results of our retinal blood vessel segmentation methods including Mixture of Gaussian, Graph Cut achieved an average accuracy of 94:33%, 94:27% respectively. Our optic disc segmentation methods including Markov Random Field and Compensation Factor also achieved an average sensitivity of 92:85% and 85:70% respectively. These results obtained on several public datasets and compared with existing methods have shown that our proposed methods are robust and efficient in the segmenting retinal structures such the blood vessels and the optic disc.Brunel University Londonhttp://bura.brunel.ac.uk/bitstream/2438/10387/1/FulltextThesis.pd

Application of remote sensors in coastal zone observations

A review of processes taking place along coastlines and their biological consideration led to the determination of the elements which are required in the study of coastal structures and which are needed for better utilization of the resources from the oceans. The processes considered include waves, currents, and their influence on the erosion of coastal structures. Biological considerations include coastal fisheries, estuaries, and tidal marshes. Various remote sensors were analyzed for the information which they can provide and sites were proposed where a general ocean-observation plan could be tested

State of the Art in Dense Monocular Non-Rigid 3D Reconstruction

3D reconstruction of deformable (or non-rigid) scenes from a set of monocular 2D image observations is a long-standing and actively researched area of computer vision and graphics. It is an ill-posed inverse problem, since--without additional prior assumptions--it permits infinitely many solutions leading to accurate projection to the input 2D images. Non-rigid reconstruction is a foundational building block for downstream applications like robotics, AR/VR, or visual content creation. The key advantage of using monocular cameras is their omnipresence and availability to the end users as well as their ease of use compared to more sophisticated camera set-ups such as stereo or multi-view systems. This survey focuses on state-of-the-art methods for dense non-rigid 3D reconstruction of various deformable objects and composite scenes from monocular videos or sets of monocular views. It reviews the fundamentals of 3D reconstruction and deformation modeling from 2D image observations. We then start from general methods--that handle arbitrary scenes and make only a few prior assumptions--and proceed towards techniques making stronger assumptions about the observed objects and types of deformations (e.g. human faces, bodies, hands, and animals). A significant part of this STAR is also devoted to classification and a high-level comparison of the methods, as well as an overview of the datasets for training and evaluation of the discussed techniques. We conclude by discussing open challenges in the field and the social aspects associated with the usage of the reviewed methods.Comment: 25 page

State of the Art in Dense Monocular Non-Rigid 3D Reconstruction

3D reconstruction of deformable (or non-rigid) scenes from a set of monocular2D image observations is a long-standing and actively researched area ofcomputer vision and graphics. It is an ill-posed inverse problem,since--without additional prior assumptions--it permits infinitely manysolutions leading to accurate projection to the input 2D images. Non-rigidreconstruction is a foundational building block for downstream applicationslike robotics, AR/VR, or visual content creation. The key advantage of usingmonocular cameras is their omnipresence and availability to the end users aswell as their ease of use compared to more sophisticated camera set-ups such asstereo or multi-view systems. This survey focuses on state-of-the-art methodsfor dense non-rigid 3D reconstruction of various deformable objects andcomposite scenes from monocular videos or sets of monocular views. It reviewsthe fundamentals of 3D reconstruction and deformation modeling from 2D imageobservations. We then start from general methods--that handle arbitrary scenesand make only a few prior assumptions--and proceed towards techniques makingstronger assumptions about the observed objects and types of deformations (e.g.human faces, bodies, hands, and animals). A significant part of this STAR isalso devoted to classification and a high-level comparison of the methods, aswell as an overview of the datasets for training and evaluation of thediscussed techniques. We conclude by discussing open challenges in the fieldand the social aspects associated with the usage of the reviewed methods.<br

Phylogenomics and Geometric Morphometrics Define Species Flocks of Snowtrout (Teleostei: Schizothorax) in the Central Himalayas

Schizothorax (Snowtrout) is a genus of medium-sized minnows (Cypriniformes) inhabiting glacier-fed streams, rivers, and lakes in the Himalayas. There are more than 30 species of Schizothorax across the region. The speciation and diversity of the Snowtrout in the vast hinterlands of the Himalayan Region has not been fully explored. Three species in Lake Rara, Western Nepal are considered a species flock, comprising endemic ecotypes that are morphologically differentiated and reproductively isolated. My dissertation research examined the diversity of Schizothorax in the Central Himalayan region and evolutionary relationships among species distributed in the Tibet, Central and Southeast Asia. Chapter I describes the historical biogeography and distribution of Schizothorax species in the Himalayas and Tibetan Region. In Chapter II, morphological and genetic variation was examined among Schizothorax collected from three major drainage systems in Nepal using 18 anatomical landmarks (number of images, N=565) and mitochondrial gene (cytochrome b) sequence analysis (n=115). In Chapter III, machine learning algorithms were evaluated to discriminate morphological species based on head and body shape using Procrustes aligned data generated in Chapter 2. In Chapter IV, a phylogenetic tree of Schizothorax was constructed comprising Central (Nepal, haplotypes=14) and Eastern (Bhutan, haplotypes=18) Himalayan species to explore their evolutionary relationships within in a global species phylogeny based on GenBank data (n=51, outgroups=5). Chapter V employed a phylogenomic approach to examine fine-scale relationships amongst Schizothorax in Nepal and assess uniqueness of endemic forms in Lake Rara. Double digest restriction associated DNA (ddRAD)sequences were generated to extract 20,000 single nucleotide polymorphism (SNPs) loci. These data were used to trace the selection driven phenotypic convergence among species isolated largely due to the geographical and ecological barriers. Both species and basins were significant predictors of the shape. Classifiers, such as Linear Discriminant Analysis (LDA) and Support Vector Machine (SVM), assigned individuals to morphological species with high accuracy. However, a strong geographic structure was reflected in the mitochondrial (cytochrome b) gene sequence data. Conversely, phylogenomic analysis of SNPs uncovered basin-specific upstream and downstream clades, as well as Lake Rara endemic species as a monophyletic group that mitochondrial gene analyses failed to resolve in previous studies

Workshop on the Integration of Finite Element Modeling with Geometric Modeling

The workshop on the Integration of Finite Element Modeling with Geometric Modeling was held on 12 May 1987. It was held to discuss the geometric modeling requirements of the finite element modeling process and to better understand the technical aspects of the integration of these two areas. The 11 papers are presented except for one for which only the abstract is given

Memory function in multiple sclerosis

Multiple Sclerosis (MS) is a disease of the central nervous system. Its diffuse pathology results in a variety of physical and psychological symptoms. Memory dysfunction is one of the most prevalent cognitive deficits associated with MS. However, the accurate assessment of memory in MS is often compromised by the coincident physical and/or cognitive difficulties of the patients. Also, there are no conventional memory tests suitable for MS patients, which grade varying types of verbal and spatial memory ability. The aim of this thesis was to develop a new test of memory which reduced the handicap imposed by sensori-motor dysfunction on cognitive test performance, and assessed recall memory, paired association, and recognition memory using matched verbal and spatial tasks. The New Test Of Memory was standardised using a sample of 85 healthy controls, stratified for age, sex, and IQ. The measure demonstrated the effects of ageing on normal memory performance, and showed good internal reliability (Cronbach's alpha verbal sections: 0.76; spatial sections: 0.75), consistency, and construct and factorial validity. The validation sample comprised 100 MS patients. The applicability of the tasks for patients with MS was demonstrated by the absence of a relationship between memory performance and measures of visual integrity and manual dexterity. The patient assessments also showed good internal reliability (Cronbach's alpha verbal sections: 0.85; spatial sections: 0.74), consistency, and construct, factorial, convergent, and discriminant validity. Patient performance was significantly impaired relative to controls, with 23 % of patients scoring more than 2 standard deviations below the age group control mean on the verbal sections, and 15 % on the spatial sections. The patterns of impairment demonstrated by the patients did not provide support for either the acquisition or retrieval deficit hypotheses, suggesting that memory deficiencies in MS may not fit a simple, single deficit model

Determining normal and abnormal lip shapes during movement for use as a surgical outcome measure

Craniofacial assessment for diagnosis, treatment planning and outcome has traditionally relied on imaging techniques that provide a static image of the facial structure. Objective measures of facial movement are however becoming increasingly important for clinical interventions where surgical repositioning of facial structures can influence soft tissue mobility. These applications include the management of patients with cleft lip, facial nerve palsy and orthognathic surgery. Although technological advances in medical imaging have now enabled three-dimensional (3D) motion scanners to become commercially available their clinical application to date has been limited. Therefore, the aim of this study is to determine normal and abnormal lip shapes during movement for use as a clinical outcome measure using such a scanner. Lip movements were captured from an average population using a 3D motion scanner. Consideration was given to the type of facial movement captured (i.e. verbal or non-verbal) and also the method of feature extraction (i.e. manual or semi-automatic landmarking). Statistical models of appearance (Active Shape Models) were used to convert the video motion sequences into linear data and identify reproducible facial movements via pattern recognition. Average templates of lip movement were created based on the most reproducible lip movements using Geometric Morphometrics (GMM) incorporating Generalised Procrustes Analysis (GPA) and Principal Component Analysis (PCA). Finally lip movement data from a patient group undergoing orthognathic surgery was incorporated into the model and Discriminant Analysis (DA) employed in an attempt to statistically distinguish abnormal lip movement. The results showed that manual landmarking was the preferred method of feature extraction. Verbal facial gestures (i.e. words) were significantly more reproducible/repeatable over time when compared to non-verbal gestures (i.e. facial expressions). It was possible to create average templates of lip movement from the control group, which acted as an outcome measure, and from which abnormalities in movement could be discriminated pre-surgery. These abnormalities were found to normalise post-surgery. The concepts of this study form the basis of analysing facial movement in the clinical context. The methods are transferrable to other patient groups. Specifically, patients undergoing orthognathic surgery have differences in lip shape/movement when compared to an average population. Correcting the position of the basal bones in this group of patients appears to normalise lip mobility