Bayesian computational methods for spatial analysis of images

This thesis introduces a new way of using prior information in a spatial model and develops scalable algorithms for fitting this model to large imaging datasets. These methods are employed for image-guided radiation therapy and satellite based classification of land use and water quality. This study has utilized a pre-computation step to achieve a hundredfold improvement in the elapsed runtime for model fitting. This makes it much more feasible to apply these models to real-world problems, and enables full Bayesian inference for images with a million or more pixels.

A Phenomenologically Sensitized Analysis of Images Depicting Stressed Embodiment in an Adolescent Male with Autism Spectrum Disorder (ASD)

Each person with Autism Spectrum Disorder (ASD) comes with unique characteristics (idiosyncratic) that give clues to the world they know (Connolly, 2008). It is through their body that they (a) know the world they are experiencing, (b) make meaning, and (c) express certain behaviours. I used Laban’s Movement Analysis (LMA) to practice an attuned and appreciative approach to describing and understanding the body movement in one severe manifestation of autism in an adolescent male. LMA observes human movement across many disciplines and can be applied in many contexts providing a body honoring discourse for description (Connolly, 2008). The framework examines movement in body, space, quality, and relation. Each theme provides a detailed description of the individual’s movement, thus, giving us a richer understanding of patterns and possible triggers to self-injurious behaviours (SIB). During the summer of August 2013, I participated in Brock University’s annual Autism Camp and worked with a 15 year old male named “Aaron” who manifests with low functioning autism. The purpose of my research project was to code and analyze a series of photos taken to help gain insight into movement patterns associated with stressed embodiment and self-injury in “Aaron”. As I understood more about these embodied expressions, I uncovered valuable information on how to read patterns and discover what triggers these events, thus providing strategies on how to help people do more refined observations and make meaning of the behaviour. Laban’s movement analysis provided a sensitized discourse appropriate to the embodied expressions depicted in the photos.

English Channel towed sledge seabed images. Phase 2: Analysis of selected tow images

During the 1970s and 1980s, the late Dr Norman Holme undertook extensive towed sledge surveys in the English Channel and some in the Irish Sea. Only a minority of the resulting images were analysed and reported before his death in 1989 but logbooks, video and film material has been archived in the National Marine Biological Library (NMBL) in Plymouth. A study was therefore commissioned by the Joint Nature Conservation Committee and as a part of the Mapping European Seabed Habitats (MESH) project to identify the value of the material archived and the procedure and cost to undertake further work (Phase 1 of the study reported here: Oakley & Hiscock, 2005). Some image analysis was undertaken as a part of Phase 1. Phase 2 (this report) was to further analyse selected images. Having determined in Phase 1 that only the 35 mm photographic transparencies provided sufficient clarity to identify species and biotopes, the tows selected for analysis were ones where 35mm images had been taken. The tows selected for analysis of images were mainly in the vicinity of Plymouth and especially along the area between Rame Head and the region of the Eddystone. The 35 mm films were viewed under a binocular microscope and the taxa that could be recognised recorded in note form. Twenty-five images were selected for inclusion in the report. Almost all of the images were of level sediment seabed. Where rocks were included, it was usually unplanned and the sled was hauled before being caught or damaged. The main biotopes or biotope complexes identified were: SS.SMU.CSaMu. Circalittoral sandy mud. Extensively present between the shore and the Eddystone Reef complex and at depths of about 48 to 52 m. At one site offshore of Plymouth Sound, the turret shell Turritella communis was abundant. In some areas, this biotope had dense anemones, Mesacmaea mitchelli and (more rarely) Cerianthus lloydii. Queen scallops, Aequipecten opercularis and king scallops, Pecten maximus, were sometimes present in small numbers. Hard substratum species such as hydroids, dead mens fingers Alcyonium digitatum and the cup coral Caryophyllia smithii occurred in a few places, probably attached to shells or stones beneath the surface. South of the spoil ground off Hilsea Point at 57m depth, the sediment was muddier but is still assigned to this biotope complex. It is notable that three small sea pens, most likely Virgularia mirabilis, were seen here. SS.SMx.CMx. Circalittoral mixed sediment. Further offshore but at about the same depth as SS.SMU.CSaMu occurred, coarse gravel with some silt was present. The sediment was characterised must conspicuously by small queen scallops, Aequipecten opercularis. Peculiarly, there were ‘bundles’ of the branching bryozoan Cellaria sp. – a species normally found attached to rock. It could not be seen whether these bundles of Cellaria had been brought-together by terebellid worms but it is notable that Cellaria is recorded in historical surveys. As with many other sediments, there were occasional brittle stars, Ophiocomina nigra and Ophiura ophiura. Where sediments were muddy, the burrowing anemone Mesacmaea mitchelli was common. Where pebbles or cobbles occurred, there were attached species such as Alcyonium digitatum, Caryophyllia smithii and the fleshy bryozoan Alcyonidium diaphanum. Undescribed biotope. Although most likely a part of SS.SMx.CMx, the biotope visually dominated by a terebellid worm believed to be Thelepus cincinnatua, is worth special attention as it may be an undescribed biotope. The biotope occurred about 22 nautical miles south of the latitude of the Eddystone and in depths in excess of 70 m. SS.SCS.CCS.Blan. Branchiostoma lanceolatum in circalittoral coarse sand with shell gravel at about 48m depth and less. This habitat was the ‘classic’ ‘Eddystone Shell Gravel’ which is sampled for Branchiostoma lanceolatum. However, no Branchiostoma lanceolatum could be seen. The gravel was almost entirely bare of epibiota. There were occasional rock outcrops or cobbles which had epibiota including encrusting calcareous algae, the sea fan Eunicella verrucosa, cup corals, Caryophyllia smithii, hydroids and a sea urchin Echinus esculentus. The variety of species visible on the surface is small and therefore identification to biotope not usually possible. Historical records from sampling surveys that used grabs and dredges at the end of the 19th century and early 20th century suggest similar species present then. Illustrations of some of the infaunal communities from work in the 1920’s is included in this report to provide a context to the epifaunal photographs.

Multi-site genetic analysis of diffusion images and voxelwise heritability analysis: A pilot project of the ENIGMA-DTI working group

The ENIGMA (Enhancing NeuroImaging Genetics through Meta-Analysis) Consortium was set up to analyze brain measures and genotypes from multiple sites across the world to improve the power to detect genetic variants that influence the brain. Diffusion tensor imaging (DTI) yields quantitative measures sensitive to brain development and degeneration, and some common genetic variants may be associated with white matter integrity or connectivity. DTI measures, such as the fractional anisotropy (FA) of water diffusion, may be useful for identifying genetic variants that influence brain microstructure. However, genome-wide association studies (GWAS) require large populations to obtain sufficient power to detect and replicate significant effects, motivating a multi-site consortium effort. As part of an ENIGMA-DTI working group, we analyzed high-resolution FA images from multiple imaging sites across North America, Australia, and Europe, to address the challenge of harmonizing imaging data collected at multiple sites. Four hundred images of healthy adults aged 18-85 from four sites were used to create a template and corresponding skeletonized FA image as a common reference space. Using twin and pedigree samples of different ethnicities, we used our common template to evaluate the heritability of tract-derived FA measures. We show that our template is reliable for integrating multiple datasets by combining results through meta-analysis and unifying the data through exploratory mega-analyses. Our results may help prioritize regions of the FA map that are consistently influenced by additive genetic factors for future genetic discovery studies. Protocols and templates are publicly available at (http://enigma.loni.ucla.edu/ongoing/dti-working-group/).

Spectral analysis of pair-correlation bandwidth: Application to cell biology images

Images from cell biology experiments often indicate the presence of cell clustering, which can provide insight into the mechanisms driving the collective cell behaviour. Pair-correlation functions provide quantitative information about the presence, or absence, of clustering in a spatial distribution of cells. This is because the pair-correlation function describes the ratio of the abundance of pairs of cells, separated by a particular distance, relative to a randomly distributed reference population. Pair-correlation functions are often presented as a kernel density estimate where the frequency of pairs of objects are grouped using a particular bandwidth (or bin width), Δ>0. The choice of bandwidth has a dramatic impact: choosing Δ too large produces a pair-correlation function that contains insufficient information, whereas choosing Δ too small produces a pair-correlation signal dominated by fluctuations. Presently, there is little guidance available regarding how to make an objective choice of Δ. We present a new technique to choose Δ by analysing the power spectrum of the discrete Fourier transform of the pair-correlation function. Using synthetic simulation data, we confirm that our approach allows us to objectively choose Δ such that the appropriately binned pair-correlation function captures known features in uniform and clustered synthetic images. We also apply our technique to images from two different cell biology assays. The first assay corresponds to an approximately uniform distribution of cells, while the second assay involves a time series of images of a cell population which forms aggregates over time. The appropriately binned pair-correlation function allows us to make quantitative inferences about the average aggregate size, as well as quantifying how the average aggregate size changes with time.

Analysis of spatio-temporal dynamic pattern and driving forces of urban land in China in 1990s using TM images and GIS

China has witnessed fast urban growth in the recent decade. This study analyzes spatio-temporal characteristics of urban expansion in China using satellite images and regionalization methods. Landsat TM images at three time periods, 1990/1991, 1995/1996, and 1999/2000, are interpreted to get 1:100000 vector land use datasets. The study calculates the urban land percentage and urban land expansion index of every 1 km(2) cell throughout China. The study divides China into 27 urban regions to conceive dynamic patterns of urban land changes. Urban development was achieving momentum in the western region, expanding more noticeably than in the previous five years, and seeing an increased growth percentage. Land use dynamic changes reflect the strong impacts of economic growth environments and macro-urban development policies. The paper helps to distinguish the influences of newly market-oriented forces from traditional administrative controls on China's urban expansion. (c) 2005 Elsevier Ltd. All rights reserved.

Extracting Salient Curves from Images: An Analysis of the Saliency Network

The Saliency Network proposed by Shashua and Ullman is a well-known approach to the problem of extracting salient curves from images while performing gap completion. This paper analyzes the Saliency Network. The Saliency Network is attractive for several reasons. First, the network generally prefers long and smooth curves over short or wiggly ones. While computing saliencies, the network also fills in gaps with smooth completions and tolerates noise. Finally, the network is locally connected, and its size is proportional to the size of the image. Nevertheless, our analysis reveals certain weaknesses with the method. In particular, we show cases in which the most salient element does not lie on the perceptually most salient curve. Furthermore, in some cases the saliency measure changes its preferences when curves are scaled uniformly. Also, we show that for certain fragmented curves the measure prefers large gaps over a few small gaps of the same total size. In addition, we analyze the time complexity required by the method. We show that the number of steps required for convergence in serial implementations is quadratic in the size of the network, and in parallel implementations is linear in the size of the network. We discuss problems due to coarse sampling of the range of possible orientations. We show that with proper sampling the complexity of the network becomes cubic in the size of the network. Finally, we consider the possibility of using the Saliency Network for grouping. We show that the Saliency Network recovers the most salient curve efficiently, but it has problems with identifying any salient curve other than the most salient one.

Coordinated analysis of delayed sprites with high-speed images and remote electromagnetic fields

Simultaneous measurements of high-altitude optical emissions and magnetic fields produced by sprite-associated lightning discharges enable a close examination of the link between low-altitude lightning processes and high-altitude sprite processes. We report results of the coordinated analysis of high-speed sprite video and wideband magnetic field measurements recorded simultaneously at Yucca Ridge Field Station and Duke University. From June to August 2005, sprites were detected following 67 lightning strokes, all of which had positive polarity. Our data showed that 46% of the 83 discrete sprite events in these sequences initiated more than 10 ms after the lightning return stroke, and we focus on these delayed sprites in this work. All delayed sprites were preceded by continuing current moments that averaged at least 11 kA km between the return stroke and sprites. The total lightning charge moment change at sprite initiation varied from 600 to 18,600 C km, and the minimum value to initiate long-delayed sprites ranged from 600 for 15 ms delay to 2000 C km for more than 120 ms delay. We numerically simulated electric fields at altitudes above these lightning discharges and found that the maximum normalized electric fields are essentially the same as fields that produce short-delayed sprites. Both estimated and simulation-predicted sprite initiation altitudes indicate that long-delayed sprites generally initiate around 5 km lower than short-delayed sprites. The simulation results also reveal that slow (5-20 ms) intensifications in continuing current can play a major role in initiating delayed sprites. Copyright 2008 by the American Geophysical Union.

Automatic Analysis of Digital Retinal Images for Glaucoma Detection

In this paper we propose a novel automated glaucoma detection framework for mass-screening that operates on inexpensive retinal cameras. The proposed methodology is based on the assumption that discriminative features for glaucoma diagnosis can be extracted from the optical nerve head structures,
such as the cup-to-disc ratio or the neuro-retinal rim variation. After automatically segmenting the cup and optical disc, these features are feed into a machine learning classifier. Experiments were performed using two different datasets and from the obtained results the proposed technique provides
better performance than approaches based on appearance. A main advantage of our approach is that it only requires a few training samples to provide high accuracy over several different glaucoma stages.