Digital television applications

Studying development of interactive services for digital television is a leading edge area of work as there is minimal research or precedent to guide their design. Published research is limited and therefore this thesis aims at establishing a set of computing methods using Java and XML technology for future set-top box interactive services. The main issues include middleware architecture, a Java user interface for digital television, content representation and return channel communications. The middleware architecture used was made up of an Application Manager, Application Programming Interface (API), a Java Virtual Machine, etc., which were arranged in a layered model to ensure the interoperability. The application manager was designed to control the lifecycle of Xlets; manage set-top box resources and remote control keys and to adapt the graphical device environment. The architecture of both application manager and Xlet forms the basic framework for running multiple interactive services simultaneously in future set-top box designs. User interface development is more complex for this type of platform (when compared to that for a desktop computer) as many constraints are set on the look and feel (e.g., TV-like and limited buttons). Various aspects of Java user interfaces were studied and my research in this area focused on creating a remote control event model and lightweight drawing components using the Java Abstract Window Toolkit (AWT) and Java Media Framework (JMF) together with Extensible Markup Language (XML). Applications were designed aimed at studying the data structure and efficiency of the XML language to define interactive content. Content parsing was designed as a lightweight software module based around two parsers (i.e., SAX parsing and DOM parsing). The still content (i.e., text, images, and graphics) and dynamic content (i.e., hyperlinked text, animations, and forms) can then be modeled and processed efficiently. This thesis also studies interactivity methods using Java APIs via a return channel. Various communication models are also discussed that meet the interactivity requirements for different interactive services. They include URL, Socket, Datagram, and SOAP models which applications can choose to use in order to establish a connection with the service or broadcaster in order to transfer data. This thesis is presented in two parts: The first section gives a general summary of the research and acts as a complement to the second section, which contains a series of related publications.reviewe

A graph-based approach for the retrieval of multi-modality medical images

Medical imaging has revolutionised modern medicine and is now an integral aspect of diagnosis and patient monitoring. The development of new imaging devices for a wide variety of clinical cases has spurred an increase in the data volume acquired in hospitals. These large data collections offer opportunities for search-based applications in evidence-based diagnosis, education, and biomedical research. However, conventional search methods that operate upon manual annotations are not feasible for this data volume. Content-based image retrieval (CBIR) is an image search technique that uses automatically derived visual features as search criteria and has demonstrable clinical benefits. However, very few studies have investigated the CBIR of multi-modality medical images, which are making a monumental impact in healthcare, e.g., combined positron emission tomography and computed tomography (PET-CT) for cancer diagnosis. In this thesis, we propose a new graph-based method for the CBIR of multi-modality medical images. We derive a graph representation that emphasises the spatial relationships between modalities by structurally constraining the graph based on image features, e.g., spatial proximity of tumours and organs. We also introduce a graph similarity calculation algorithm that prioritises the relationships between tumours and related organs. To enable effective human interpretation of retrieved multi-modality images, we also present a user interface that displays graph abstractions alongside complex multi-modality images. Our results demonstrated that our method achieved a high precision when retrieving images on the basis of tumour location within organs. The evaluation of our proposed UI design by user surveys revealed that it improved the ability of users to interpret and understand the similarity between retrieved PET-CT images. The work in this thesis advances the state-of-the-art by enabling a novel approach for the retrieval of multi-modality medical images

Exploring Sparse, Unstructured Video Collections of Places

The abundance of mobile devices and digital cameras with video capture makes it easy to obtain large collections of video clips that contain the same location, environment, or event. However, such an unstructured collection is difficult to comprehend and explore. We propose a system that analyses collections of unstructured but related video data to create a Videoscape: a data structure that enables interactive exploration of video collections by visually navigating — spatially and/or temporally — between different clips. We automatically identify transition opportunities, or portals. From these portals, we construct the Videoscape, a graph whose edges are video clips and whose nodes are portals between clips. Now structured, the videos can be interactively explored by walking the graph or by geographic map. Given this system, we gauge preference for different video transition styles in a user study, and generate heuristics that automatically choose an appropriate transition style. We evaluate our system using three further user studies, which allows us to conclude that Videoscapes provides significant benefits over related methods. Our system leads to previously unseen ways of interactive spatio-temporal exploration of casually captured videos, and we demonstrate this on several video collections

Anchoring The Cognitive Map To The Visual World

To interact rapidly and effectively with the environment, the mammalian brain needs a representation of the spatial layout of the external world (or a “cognitive map”). A person might need to know where she is standing to find her way home, for instance, or might need to know where she is looking to reach for her out-of-sight keys. For many behaviors, however, simply possessing a map is not enough; in order for a map to be useful in a dynamic world, it must be anchored to stable environmental cues. The goal of the present research is to address this spatial anchoring problem in two different domains: navigation and vision. In the first part of the thesis, which comprises Chapters 1-3, we examine how navigators use perceptual information to re-anchor their cognitive map after becoming lost, a process known as spatial reorientation. Using a novel behavioral paradigm with rodents, in Chapter 2 we show that the cognitive map is reoriented by dissociable inputs for identifying where one is and recovering which way one is facing. The findings presented in Chapter 2 also highlight the importance of environmental boundaries, such as the walls of a room, for anchoring the cognitive map. We thus predicted that there might exist a brain region that is selectively involved in boundary perception during navigation. Accordingly, in Chapter 3, we combine transcranial magnetic stimulation and virtual-reality navigation to reveal the existence of such a boundary perception region in humans. In the second part of this thesis, Chapter 4, we explore whether the same mechanisms that support the cognitive map of navigational space also mediate a map of visual space (i.e., where one is looking). Using functional magnetic resonance imaging and eye tracking, we show that human entorhinal cortex supports a map-like representation of visual space that obeys the same principles of boundary-anchoring previously observed in rodent maps of navigational space. Together, this research elucidates how mental maps are anchored to the world, thus allowing the mammalian brain to form durable spatial representations across body and eye movements

Visual Techniques for Geological Fieldwork Using Mobile Devices

Visual techniques in general and 3D visualisation in particular have seen considerable adoption within the last 30 years in the geosciences and geology. Techniques such as volume visualisation, for analysing subsurface processes, and photo-coloured LiDAR point-based rendering, to digitally explore rock exposures at the earth’s surface, were applied within geology as one of the first adopting branches of science. A large amount of digital, geological surface- and volume data is nowadays available to desktop-based workflows for geological applications such as hydrocarbon reservoir exploration, groundwater modelling, CO2 sequestration and, in the future, geothermal energy planning. On the other hand, the analysis and data collection during fieldwork has yet to embrace this ”digital revolution”: sedimentary logs, geological maps and stratigraphic sketches are still captured in each geologist’s individual fieldbook, and physical rocks samples are still transported to the lab for subsequent analysis. Is this still necessary, or are there extended digital means of data collection and exploration in the field ? Are modern digital interpretation techniques accurate and intuitive enough to relevantly support fieldwork in geology and other geoscience disciplines ? This dissertation aims to address these questions and, by doing so, close the technological gap between geological fieldwork and office workflows in geology. The emergence of mobile devices and their vast array of physical sensors, combined with touch-based user interfaces, high-resolution screens and digital cameras provide a possible digital platform that can be used by field geologists. Their ubiquitous availability increases the chances to adopt digital workflows in the field without additional, expensive equipment. The use of 3D data on mobile devices in the field is furthered by the availability of 3D digital outcrop models and the increasing ease of their acquisition. This dissertation assesses the prospects of adopting 3D visual techniques and mobile devices within field geology. The research of this dissertation uses previously acquired and processed digital outcrop models in the form of textured surfaces from optical remote sensing and photogrammetry. The scientific papers in this thesis present visual techniques and algorithms to map outcrop photographs in the field directly onto the surface models. Automatic mapping allows the projection of photo interpretations of stratigraphy and sedimentary facies on the 3D textured surface while providing the domain expert with simple-touse, intuitive tools for the photo interpretation itself. The developed visual approach, combining insight from all across the computer sciences dealing with visual information, merits into the mobile device Geological Registration and Interpretation Toolset (GRIT) app, which is assessed on an outcrop analogue study of the Saltwick Formation exposed at Whitby, North Yorkshire, UK. Although being applicable to a diversity of study scenarios within petroleum geology and the geosciences, the particular target application of the visual techniques is to easily provide field-based outcrop interpretations for subsequent construction of training images for multiple point statistics reservoir modelling, as envisaged within the VOM2MPS project. Despite the success and applicability of the visual approach, numerous drawbacks and probable future extensions are discussed in the thesis based on the conducted studies. Apart from elaborating on more obvious limitations originating from the use of mobile devices and their limited computing capabilities and sensor accuracies, a major contribution of this thesis is the careful analysis of conceptual drawbacks of established procedures in modelling, representing, constructing and disseminating the available surface geometry. A more mathematically-accurate geometric description of the underlying algebraic surfaces yields improvements and future applications unaddressed within the literature of geology and the computational geosciences to this date. Also, future extensions to the visual techniques proposed in this thesis allow for expanded analysis, 3D exploration and improved geological subsurface modelling in general.publishedVersio

AI in Medical Imaging Informatics: Current Challenges and Future Directions

This paper reviews state-of-the-art research solutions across the spectrum of medical imaging informatics, discusses clinical translation, and provides future directions for advancing clinical practice. More specifically, it summarizes advances in medical imaging acquisition technologies for different modalities, highlighting the necessity for efficient medical data management strategies in the context of AI in big healthcare data analytics. It then provides a synopsis of contemporary and emerging algorithmic methods for disease classification and organ/ tissue segmentation, focusing on AI and deep learning architectures that have already become the de facto approach. The clinical benefits of in-silico modelling advances linked with evolving 3D reconstruction and visualization applications are further documented. Concluding, integrative analytics approaches driven by associate research branches highlighted in this study promise to revolutionize imaging informatics as known today across the healthcare continuum for both radiology and digital pathology applications. The latter, is projected to enable informed, more accurate diagnosis, timely prognosis, and effective treatment planning, underpinning precision medicine

Comparative analysis of plant genomes through data integration

When we started our research in 2008, several online resources for genomics existed, each with a different focus. TAIR (The Arabidopsis Information Resource) has a focus on the plant model species Arabidopsis thaliana, with (at that time) little or no support for evolutionary or comparative genomics. Ensemble provided some basic tools and functions as a data warehouse, but it would only start incorporating plant genomes in 2010. There was no online resource at that time however, that provided the necessary data content and tools for plant comparative and evolutionary genomics that we required. As such, the plant community was missing an essential component to get their research at the same level as the biomedicine oriented research communities. We started to work on PLAZA in order to provide such a data resource that could be accessed by the plant community, and which also contained the necessary data content to help our research group’s focus on evolutionary genomics. The platform for comparative and evolutionary genomics, which we named PLAZA, was developed from scratch (i.e. not based on an existing database scheme, such as Ensemble). Gathering the data for all species, parsing this data into a common format and then uploading it into the database was the next step. We developed a processing pipeline, based on sequence similarity measurements, to group genes into gene families and sub families. Functional annotation was gathered through both the original data providers and through InterPro scans, combined with Interpro2GO. This primary data information was then ready to be used in every subsequent analysis. Building such a database was good enough for research within our bioinformatics group, but the target goal was to provide a comprehensive resource for all plant biologists with an interest in comparative and evolutionary genomics. Designing and creating a user-friendly, visually appealing web interface, connected to our database, was the next step. While the most detailed information is commonly presented in data tables, aesthetically pleasing graphics, images and charts are often used to visualize trends, general statistics and also used in specific tools. Design and development of these tools and visualizations is thus one of the core elements within my PhD. The PLAZA platform was designed as a gene-centric data resource, which is easily navigated when a biologist wants to study a relative small number of genes. However, using the default PLAZA website to retrieve information for dozens of genes quickly becomes very tedious. Therefore a ’gene set’-centric extra layer was developed where user-defined gene sets could be quickly analyzed. This extra layer, called the PLAZA workbench, functions on top of the normal PLAZA website, implicating that only gene sets from species present within the PLAZA database can be directly analyzed. The PLAZA resource for comparative and evolutionary genomics was a major success, but it still had several issues. We tried to solve at least two of these problems at the same time by creating a new platform. The first issue was the building procedure of PLAZA: adding a single species, or updating the structural annotation of an existing one, requires the total re-computation of the database content. The second issue was the restrictiveness of the PLAZA workbench: through a mapping procedure gene sets could be entered for species not present in the PLAZA database, but for species without a phylogenetic close relative this approach did not always yield satisfying results. Furthermore, the research in question might just focus on the difference between a species present in PLAZA and a close relative not present in PLAZA (e.g. to study adaptation to a different ecological niche). In such a case, the mapping procedure is in itself useless. With the advent of NGS transcriptome data sets for a growing number of species, it was clear that a next challenge had presented itself. We designed and developed a new platform, named TRAPID, which could automatically process entire transcriptome data sets, using a reference database. The target goal was to have the processing done quickly with the results containing both gene family oriented data (such as multiple sequence alignments and phylogenetic trees) and functional characterization of the transcripts. Major efforts went into designing the processing pipeline so it could be reliable, fast and accurate