Individualised Clinical Neuroimaging in the Developing Brain: Abnormality Detection

Perinatal neuroanatomical structure is incredibly intricate and, at time of birth, is undergoing continuous change due to interweaving developmental processes (growth, myelination and gyrification). While there is some small variability in structure and rates of development, all follow proscribed pathways with well documented milestones. Brain injury or other disruption of these processes can result in poor neurodevelopmental outcomes or mortality, making their early identification critical to estimate, and potentially forestall, negative effects. MRI is an increasingly used method of investigating suspected neonatal encephalopathies and injuries.Identification of these injuries and malformations is more challenging in neonates compared to adults due to the brain’s continuously evolving appearance. This makes radiological review of neonatal MRI an intensive and time-consuming task which, in an ideal setting, requires a team of highly skilled clinicians and radiologists with complementary training and extensive experience. To assist this review process, some localisation method that highlights areas likely to contain tissue abnormalities would be highly desirable, as it could quickly draw attention to these locations. In addition, identifying neonates whose MRI is likely to contain some form of pathology could allow for review prioritisation.In this thesis, I first investigated using normative models of neonatal tissue intensity for brain tissue abnormality detection. I applied voxel-wise Gaussian process (GP) regression to a training cohort of neonates with no obvious lesions, all born preterm (<37 weeks) but imaged between 28-55 weeks. Gestational age at birth (GA), postmenstrual age at scan (PMA) and sex were used as input variables and voxel intensity as the output variable. GPs output a mean value and its variance inferred from neonates within the training cohort whose demographic information most closely matched those of the prediction target. The voxel specific models were put together to form a synthesised typical image and standard deviation image derived from the variance outputs. Z-score abnormality maps were constructed by taking the difference between neonates actual MRI and GP-calculated synthetic image and scaling by their standard deviation map. Higher Z-score map values indicate voxels more likely to contain abnormal tissue intensity. Using manually delineated masks of common brain injuries seen in a subset of neonates, these abnormality Z-score maps demonstrated good detection performance using area under the curve of receiver operating characteristic scores, with the exception of small punctate lesions.The initial voxel-wise models had substantial false positives around the edges of the brain where there is large typical heterogeneity. I next investigated if incorporating local structural information into predictive models could improve their ability to accommodate typical anatomical heterogeneity seen across individual brains and improve the accuracy of synthetic images and abnormality detection. To achieve this, voxel intensity values in a patch surrounding the prediction target were appended to the design matrix, alongside GMA, PMA and sex. The patch-based synthetic images were able to match an individual’s brain structure more closely and had lower false positives in normal appearing tissue. However, a weakness was that the centre of some larger lesions was included in the predictions (thereby classified as ‘healthy’ tissue), having a deleterious effect on their coverage, increasing false negatives. This was offset by much better coverage of smaller, more subtle lesions, to the extent that overall performance was higher compared to that seen in the earlier model.I also investigated if the Z-score abnormality maps could be used to classify neonates with MRI positive brain injury from those with normal appearing brains. While many machine learning algorism see frequent use in neuroimaging classification tasks, I opted for a logistic regression model due to its high levels of interpretability and simple implementation. Using the histograms of the Z-score abnormality maps as inputs, the model demonstrated good performance, being able to correctly identify neonates with injuries, but not those with subtle lesions like punctate lesions, whilst minimising false identification of neonates with normal appearing brains.To ascertain if performance could be improved, I explored multiple classification methods. Specifically, the use of other more complex classifiers (random forest, support vector machines, GP classification) and the use of a regional abnormal voxel count, that allowed localisation of lesioned tissue rather than the more global detection ability of the Z-score histograms. Using these innovations, I investigated their application towards a specific pathology; hypoxic ischemic encephalopathy (HIE). This is a good test for the system, as HIE has high incidence rates, multiple associated lesion types and a time dependant appearance. Further, I wanted to know if, given a positive HIE diagnosis, the Z-score abnormality maps could be used to predict long-term outcomes (normal vs poor). Several models demonstrated an excellent ability to separate HIE and healthy control neonates achieving >90% accuracy, a statistically significant result even after false discovery rate (FDR) correction (p-value < 0.05). While the outcome prediction models achieved reasonable accuracy, >70% in multiple models, none of these were statistically significant after FDR correction.Overall, this work demonstrates how normative modelling can be used to create individual voxel-wise / image-wise estimation of tissue abnormality for neonatal MRI across a range of gestational ages. It further demonstrates that these abnormality maps can be utilised for additional tasks, in this instance, three increasingly challenging neurological classification problems. These include the separation of neonates with and without MRI positive lesions, identification of neonates with a specific pathological condition (HIE) and prediction of long-term functional outcome (normal vs poor). Within a radiological setting, these classifications task can be considered analogous to three radiological challenges, image triage, diagnostic detection and estimation of developmental prognosis, important for the clinical team but also infants and their families

Advances in Robotics, Automation and Control

The book presents an excellent overview of the recent developments in the different areas of Robotics, Automation and Control. Through its 24 chapters, this book presents topics related to control and robot design; it also introduces new mathematical tools and techniques devoted to improve the system modeling and control. An important point is the use of rational agents and heuristic techniques to cope with the computational complexity required for controlling complex systems. Through this book, we also find navigation and vision algorithms, automatic handwritten comprehension and speech recognition systems that will be included in the next generation of productive systems developed by man

Deep Neural Networks and Data for Automated Driving

This open access book brings together the latest developments from industry and research on automated driving and artificial intelligence. Environment perception for highly automated driving heavily employs deep neural networks, facing many challenges. How much data do we need for training and testing? How to use synthetic data to save labeling costs for training? How do we increase robustness and decrease memory usage? For inevitably poor conditions: How do we know that the network is uncertain about its decisions? Can we understand a bit more about what actually happens inside neural networks? This leads to a very practical problem particularly for DNNs employed in automated driving: What are useful validation techniques and how about safety? This book unites the views from both academia and industry, where computer vision and machine learning meet environment perception for highly automated driving. Naturally, aspects of data, robustness, uncertainty quantification, and, last but not least, safety are at the core of it. This book is unique: In its first part, an extended survey of all the relevant aspects is provided. The second part contains the detailed technical elaboration of the various questions mentioned above

Documentation du patrimoine de l'assemblage de fossiles du site de Kromdraai contenant des hominines (Afrique du Sud) : techniques de numérisation 3D, analyse spatiale quantitative et estimation de volume

Cette thèse explore l'utilisation de données multi-échelles pour modéliser une représentation tridimensionnelle (3D) et générer un registre numérique complet d'un assemblage de fossiles contenant des hominines à partir de l'unité lithostratigraphique P à Kromdraai situé dans le " berceau de l'humanité " classé au patrimoine mondial par l'UNESCO (Province de Gauteng, Afrique du Sud). Les objectifs principaux de cette recherche sont d'illustrer en 3D la progression temporelle et spatiale des fouilles de Kromdraai sur la période 2014-2018, d'analyse la distribution spatiale des vestiges d'homininés et de faune, comme des outils, et finalement, de fournir une documentation sur le patrimoine archéologique de Kromdraai. Nous avons réalisé une analyse multi-scalaire du site, avec l'application de méthodes de photogrammétrie terrestre et aérienne. Conformément aux principes et directives de la gestion du patrimoine archéologique mandatés par les agences internationales telles que l'UNESCO, nous présentons également un protocole de documentation du patrimoine. Nous avons utilisé des technologies de capture de données 3D pour numériser le site de Kromdraai et ses éléments archéologiques découverts entre 2014 et 2018 lors des fouilles. Cette recherche présente une technique originale développée pour la visualisation et la quantification des sédiments volumiques prélevés sur le site à chaque période de fouille par chaque fouilleur. Les estimations de volume calculées à l'aide de la photogrammétrie 3D fournissent un contexte temporel et spatial des sédiments prélevés lors des fouilles successives, et permettent un repositionnement virtuel et plus précis des vestiges découverts ex situ. De plus, nous avons mis en place une modélisation des métadonnées pour démontrer l'utilisation d'un système de gestion de base de données 4D pour la fusion, l'organisation et la diffusion de l'ensemble des données du site de Kromdraai et le partage de la propriété intellectuelle. Nous introduisons également l'une des premières approches statistiques de la modélisation spatiale 3D dans un site Plio-Pléistocène porteurs d'hominines en en Afrique du Sud. En mettant en œuvre des méthodes classiques de tests statistiques telles le partitionnement de données spatiales 3D, nous avons étudié les modèles de l'assemblage de fossiles dans l'unité P, ainsi qu'un échantillon de 810 spécimens catalogués entre 2014 et 2018. Le regroupement de bovidés, de carnivores, d'homininés et de primates non humains a révélé un modèle de distribution spatiale non uniforme des fossiles in situ. Cette recherche présente des méthodes précieuses qui peuvent être appliquées à d'autres sites fossiles contenant des hominines dans le berceau de l'humanité. Ces méthodes peuvent être appliquées pour documenter une fouille archéologique et reconstruire un site en 3D, ainsi que pour documenter des informations patrimoniales. Nos résultats permettent d'améliorer l'interprétation des assemblages fossiles à l'aide d'analyses basées sur des modèles 3D au sein d'un assemblage contenant des hominines.This thesis uses multi-scalar data to create a three-dimensional (3D) representation and, to generate a complete digital record of the early hominin-bearing fossil assemblage from the lithostratigraphic Unit P at Kromdraai in the Cradle of Humankind World Heritage Site (Gauteng Province, South Africa). The main purposes of this research were to illustrate in 3D the temporal and spatial progression of the excavations at Kromdraai since 2014, to investigate the spatial distribution of the hominin, faunal assemblages and artefacts, and ultimately, to provide an archive documenting the archaeological heritage of Kromdraai. We provided a multi-scalar analysis of various aspects of the study site, with the application of methods such as multi-image land and aerial photogrammetry. In alignment with the principles and guidelines for the management of archaeological heritage mandated by international agencies such as UNESCO, we also present a protocol for heritage documentation. We used 3D data capture technologies to record the Kromdraai site and the archaeological evidence discovered between 2014 and 2018 from its main excavation. This research presents an original technique developed for the quantification and visualization of the volume sediments removed from the site during each excavation period. Volume estimations computed using 3D photogrammetry and digitization, provided a temporal and spatial context to the volume and location of material removed by each excavator and, a more precise and virtual repositioning of the fossil material discovered ex situ. Furthermore, we implemented metadata modelling to demonstrate the use of 4D relational database management systems for the fusion, organisation and dissemination of the Kromdraai site dataset and the sharing of intellectual property. We also introduce one of the first statistical approaches of 3D spatial patterning in Plio-Pleistocene early hominin-bearing assemblages in South Africa. Implementing classic statistical testing methods such as k-means and Density-Based Spatial Clustering and Application with Noise (DBSCAN) cluster computation in 3D, we investigated the spatial patterns of the fossil assemblage within Unit P, a sample of 810 individually catalogued specimens recovered between 2014 and 2018. The clustering of bovids, carnivores, hominins, and non-human primates revealed a non-uniform spatial distribution pattern of fossils in-situ. This research presents valuable methods that can be applied at other hominin-bearing fossil sites within the Cradle of Humankind to document an archaeological excavation and to reconstruct of the site in 3D, to document heritage information, and to enhance the interpretation of the fossil assemblages using evidence-based assessment of spatial patterns within a hominin-bearing assemblage

Issues in acute psychiatric inpatient services: staff experiences of suicide and risk-assessments:Clinical psychologists' experiences of patient death by suicide in psychiatric inpatient services: An IPA study; The quality of the psychometric properties of risk-to-self assessment tools validated on acute psychiatric inpatient samples: A systematic literature review

This thesis presents four chapters: section one: systematic literature review; section two: empirical research paper; section three: critical appraisal; section four: ethics application. The systematic literature reviews offers a summary of risk-to-self (e.g. self-harm and suicide) risk-assessment tools validated for acute psychiatric inpatient settings. Sixteen reports were included in the review and ten psychometric properties of 15 risk-assessment tools were appraised using a quality rating system. The empirical study qualitatively explores the experiences of clinical psychologists who have had a patient die by suicide whilst working in acute psychiatric inpatient settings. Six participants’ experiences were analysed and interpreted using ‘Interpretative Phenomenological Analysis’ (IPA). The critical appraisal synthesises the finding of the systematic review and empirical study, and offers a deeper exploration of clinical recommendations and limitations of the reports. The final section includes the ethics application for the empirical study, the approval letter and supplementary documentation used to conduct the research

Assessment of complex trauma symptoms in adults: a systematic review; and, Exploring consensus in best practice when working with trauma in male populations detained in secure forensic mental health settings: a Delphi study

This thesis is completed in accordance with the academic component, in part fulfilment, of the Doctorate in Clinical Psychology at the University of Edinburgh. Following the research portfolio structure, a thesis abstract is presented. This is followed by a lay summary of the background, methods, results and conclusion sections of the presented projects. Chapter One illustrates a systematic review which examines instruments that assess complex trauma related symptoms in adult populations. Chapter Two describes an empirical study exploring what a best practice framework may entail when working with male populations detained in secure forensic mental health hospital settings. The reporting of the empirical study and the systematic review have been prepared for submission to the International Journal of Forensic Mental Health and the Journal of Trauma & Dissociation, respectively. The reporting format of both projects has followed the journal author guidelines, a summary of which has been included in Appendix F. Background: Exposure to adverse experiences, particularly those considered more repetitive and enduring (such as sexual abuse and neglect) has been associated to negative mental health outcomes including complex trauma. Though assessment tools to capture complex trauma-related symptomology have been developed, a systematic review of these measures does not appear to have been completed. Furthermore, researchers have argued for the better detection and intervention of trauma-related presentations in male populations detained in secure forensic mental health settings. Improved awareness in this area is likely to help inform treatment and rehabilitation delivery for this population. Method: A systematic review critically appraised the methodological and psychometric features of instruments assessing a range of complex trauma-related symptoms. The empirical study attempted to explore how such features may be understood, detected and responded to in clinical settings. Using a Delphi process, the empirical study investigated consensus among practitioner psychologists in the United Kingdom with expertise in working with male populations detained in secure forensic mental health settings. Through an online survey format, the study involved three rounds of data collection to assess consensus on what a best practice framework may entail when detecting and working with trauma in this population. Data from the open-ended questions in Round I was assessed using qualitative analysis. This generated a number of statements upon which consensus was explored; the respondents were required to rate their agreement with the statements in Round II and III of the survey. Results: The instruments identified from the systematic review, measuring complex trauma-related symptomology, had been subjected to some degree of evaluation regarding their validity and reliability. Views of the psychologists in the empirical study indicated consensus regarding several elements that may be considered best practice in relation to working with trauma in male populations detained in secure forensic mental health settings. These related to: a range of presentations that may indicate the need for a trauma assessment; trauma-related intervention goals in light of both mental health and criminogenic needs; training and guideline recommendations. The results also indicated however, more varied views about the theoretical models that underpinned their clinical practice and the interventions employed. Conclusion: From the systematic review, no measure was assessed to be better than the others at capturing complex trauma-related presentations, though the purpose of its use is likely to impact why one would be preferable to another (e.g. screening versus outcome monitoring). Interestingly, the more recently published measures appear to have been developed for diagnostic requirements. The empirical study identified several considerations for a best practice framework in relation to working with trauma in male populations detained in secure forensic mental health settings. Further exploration and guidance for implementing trauma-specific interventions in these settings, with individuals presenting with multiple complex needs (e.g. including mental health and criminogenic), may be warranted

Uptake of sensor data in emergency management

While disasters are becoming larger, more complex and more frequent, traditional emergency management response capacities are not increasing at the same rate. Sensor capabilities could fill this gap by providing improved situational awareness, or intelligence, for emergency managers. Data from sensors is increasing exponentially in quality and quantity while the cost of capturing and processing these data is decreasing. This creates immense opportunities to bring sensor data into emergency management practices. Unfortunately, not all sensors are created equal. The accuracy, precision, presentation and timeliness of data varies depending on the source, the way the product is structured and who produces it. It is therefore difficult for emergency managers to incorporate sensor data into decision making, particularly when they have not seen the data type before, and do not know where it originated, or how to use. This thesis researches how data product creators can tailor products to increase the likelihood of their product being incorporated in emergency management decision making. It focuses on the issue of data product uptake, which is inclusion of data products in decision making processes. This issue has been poorly covered in the existing literature. This thesis synthesises literature from a range of disciplines then designs and conducts three targeted studies to build upon this knowledge. The first study compares four international data systems which use the same data source but make different choices in the design of their products, this then provides examples of the impacts of these design choices. The second study looks at disaster inquiries in Australia to consider how sensor data has been used in decision making in the past, and what lessons have been learnt from these experiences. The third study surveys Australian emergency managers to collect their views on what products they use, trust and what factors lead to that trust. The results from these studies combine to create a comprehensive collection of design choices available to data product creators. This collection covers not just technical choices like accuracy, but also presentational and data policy choices, to create a more holistic picture of how creators can influence their products. The collection is then presented in a framework which, if applied throughout product development, would be expected to increase uptake of sensor data in emergency management decision making. Design choices and user-oriented design processes are emphasised as a crucially important yet poorly-examined aspect of data uptake in emergency management. This thesis finds that trust is key to whether emergency managers use a product or not, and that trust is created through a series of design choices which can be grouped into quality, reputation, maturity and data policy