BrainPainter: A software for the visualisation of brain structures, biomarkers and associated pathological processes

We present BrainPainter, a software that automatically generates images of highlighted brain structures given a list of numbers corresponding to the output colours of each region. Compared to existing visualisation software (i.e. Freesurfer, SPM, 3D Slicer), BrainPainter has three key advantages: (1) it does not require the input data to be in a specialised format, allowing BrainPainter to be used in combination with any neuroimaging analysis tools, (2) it can visualise both cortical and subcortical structures and (3) it can be used to generate movies showing dynamic processes, e.g. propagation of pathology on the brain. We highlight three use cases where BrainPainter was used in existing neuroimaging studies: (1) visualisation of the degree of atrophy through interpolation along a user-defined gradient of colours, (2) visualisation of the progression of pathology in Alzheimer's disease as well as (3) visualisation of pathology in subcortical regions in Huntington's disease. Moreover, through the design of BrainPainter we demonstrate the possibility of using a powerful 3D computer graphics engine such as Blender to generate brain visualisations for the neuroscience community. Blender's capabilities, e.g. particle simulations, motion graphics, UV unwrapping, raster graphics editing, raytracing and illumination effects, open a wealth of possibilities for brain visualisation not available in current neuroimaging software. BrainPainter is customisable, easy to use, and can run straight from the web browser: https://brainpainter.csail.mit.edu , as well as from source-code packaged in a docker container: https://github.com/mrazvan22/brain-coloring . It can be used to visualise biomarker data from any brain imaging modality, or simply to highlight a particular brain structure for e.g. anatomy courses.Comment: Accepted at the MICCAI Multimodal Brain Imaging Analysis (MBIA) workshop, 201

Explainable Anatomical Shape Analysis through Deep Hierarchical Generative Models

Quantification of anatomical shape changes currently relies on scalar global indexes which are largely insensitive to regional or asymmetric modifications. Accurate assessment of pathology-driven anatomical remodeling is a crucial step for the diagnosis and treatment of many conditions. Deep learning approaches have recently achieved wide success in the analysis of medical images, but they lack interpretability in the feature extraction and decision processes. In this work, we propose a new interpretable deep learning model for shape analysis. In particular, we exploit deep generative networks to model a population of anatomical segmentations through a hierarchy of conditional latent variables. At the highest level of this hierarchy, a two-dimensional latent space is simultaneously optimised to discriminate distinct clinical conditions, enabling the direct visualisation of the classification space. Moreover, the anatomical variability encoded by this discriminative latent space can be visualised in the segmentation space thanks to the generative properties of the model, making the classification task transparent. This approach yielded high accuracy in the categorisation of healthy and remodelled left ventricles when tested on unseen segmentations from our own multi-centre dataset as well as in an external validation set, and on hippocampi from healthy controls and patients with Alzheimer's disease when tested on ADNI data. More importantly, it enabled the visualisation in three-dimensions of both global and regional anatomical features which better discriminate between the conditions under exam. The proposed approach scales effectively to large populations, facilitating high-throughput analysis of normal anatomy and pathology in large-scale studies of volumetric imaging

VEGF-A and neuropilin 1 (NRP1) shape axon projections in the developing CNS via dual roles in neurons and blood vessels

We thank Vann Bennett and Daizing Zhou (Department of Biochemistry, Duke University Medical Center) for the design and generation of the Brn3bCre knock-in mice. We are grateful to Bennett Alakakone and Susan Reijntjes for help with preliminary experiments and to Anastasia Lampropoulou for preparing tissue culture media. We thank the staff of the Biological Resource Unit at the UCL Institute of Ophthalmology and the University of Aberdeen Institute of Medical Sciences Microscopy and Histology Facility and Medical Research Facility for technical assistance. Funding This research was funded by project grants from the Wellcome Trust [085476/A/08/Z to L.E., C.R.] and Biotechnology and Biological Sciences Research Council (BBSRC) [BB/J00815X/1 to L.E.; BB/J00930X/1 to C.R.] and a Wellcome Trust PhD Fellowship [092839/Z/10/Z to M.T.]. Deposited in PMC for immediate release.Peer reviewedPublisher PD

Occupational therapists’ views of using a virtual reality interior design application within the pre-discharge home visit process

This article has been made available through the Brunel Open Access Publishing Fund.Background: A key role of Occupational Therapists (OTs) is to carry out pre-discharge home visits (PHV) and propose appropriate adaptations to the home environment, to enable patients to function independently after hospital-home discharge. However, research shows that more than 50% of specialist equipment installed as part of home adaptations is not used by patients. A key reason for this is that decisions about home adaptations are often made without adequate collaboration and consultation with the patient. Consequently, there is an urgent need to seek out new and innovative uses of technology to facilitate patient/practitioner collaboration, engagement and shared decision making in the PHV process. Virtual reality interior design applications (VRIDAs) primarily allow users to simulate the home environment and visualise changes prior to implementing them. Customised VRIDAs, which also model specialist occupational therapy equipment, could become a valuable tool to facilitate improved patient/practitioner collaboration if developed effectively and integrated into the PHV process. Objective: To explore the perceptions of occupational therapists with regards to using VRIDAs as an assistive tool within the PHV process. Methods: Task-oriented interactive usability sessions, utilising the think-aloud protocol and subsequent semi-structured interviews were carried out with seven Occupational Therapists who possessed significant experience across a range of clinical settings. Template analysis was carried out on the think-aloud and interview data. Analysis was both inductive and driven by theory, centring around the parameters that impact upon the acceptance, adoption and use of this technology in practice as indicated by the Technology Acceptance Model (TAM). Results: OTs’ perceptions were identified relating to three core themes: (1) perceived usefulness (PU), (2) perceived ease of use (PEoU), and (3) actual use (AU). Regarding PU, OTs believed VRIDAs had promising potential to increase understanding, enrich communications and patient involvement, and improved patient/practitioner shared understanding. However, it was unlikely that VRIDAs would be suitable for use with cognitively impaired patients. For PEoU, all OTs were able to use the software and complete the tasks successfully, however, participants noted numerous specialist equipment items that could be added to the furniture library. AU perceptions were positive regarding use of the application across a range of clinical settings including children/young adults, long-term conditions, neurology, older adults, and social services. However, some “fine tuning” may be necessary if the application is to be optimally used in practice. Conclusions: Participants perceived the use of VRIDAs in practice would enhance levels of patient/practitioner collaboration and provide a much needed mechanism via which patients are empowered to become more equal partners in decisions made about their care. Further research is needed to explore patient perceptions of VRIDAs, to make necessary customisations accordingly, and to explore deployment of the application in a collaborative patient/practitioner-based context

Determining geometric primitives for a 3D GIS : easy as 1D, 2D, 3D?

Acquisition techniques such as photo modelling, using SfM-MVS algorithms, are being applied increasingly in several fields of research and render highly realistic and accurate 3D models. Nowadays, these 3D models are mainly deployed for documentation purposes. As these data generally encompass spatial data, the development of a 3D GIS would allow researchers to use these 3D models to their full extent. Such a GIS would allow a more elaborate analysis of these 3D models and thus support the comprehension of the objects that the features in the model represent. One of the first issues that has to be tackled in order to make the resulting 3D models compatible for implementation in a 3D GIS is the choice of a certain geometric primitive to spatially represent the input data. The chosen geometric primitive will not only influence the visualisation of the data, but also the way in which the data can be stored, exchanged, manipulated, queried and understood. Geometric primitives can be one-, two- and three-dimensional. By adding an extra dimension, the complexity of the data increases, but the user is allowed to understand the original situation more intuitively. This research paper tries to give an initial analysis of 1D, 2D and 3D primitives in the framework of the integration of SfM-MVS based 3D models in a 3D GIS

TGVizTab: An ontology visualisation extension for Protégé

Ontologies are gaining a lot of interest and many are being developed to provide a variety of knowledge services. There is an increasing need for tools to graphically and in-teractively visualise such modelling structures to enhance their clarification, verification and analysis. Protégé 2000 is one of the most popular ontology modelling tools currently available. This paper introduces TGVizTab; a new Protégé plugin based on TouchGraph technology to graphically visualise Protégé?s ontologies

Decision-making process framework at the planning phase of housing development project

Every housing development project needs to go through several procedures which consist of a decision-making process. By practising the decision-making process since the planning phase, the relevant decision-maker is assisted in analysing and organising all issues arise such as the problem in identification and selection of a suitable contractor for housing development. However, the decisions are made without knowing precisely what will happen in the future. The research’s primary purpose is to develop a process model for decision-making at Malaysia’s housing development planning phase. This study also examines the decision-making process practised among Malaysian private housing developers at the planning phase and classifies four main aspects of decision-making: methods, tools, criteria and information. The study then discovers whether the four main aspects (methods, tools, criteria and information) are strongly related to the decision making process. This study comprises the development of a theoretical framework by integrating the models that have been developed by numerous authors and researchers on the subject of decision making. Besides, 67 private housing developers have been chosen as respondents for a questionnaire survey in this study. The descriptive statistical analysis and the correlated analysis are conducted employing the Statistical Package for Social Sciences (SPSS). The results of this study show different findings for every four main aspects studied. However, it still answers the research objectives, and the relationship between the four main aspects of the decision-making process is accepted. This study is useful because it serves as a guide for private housing developers and governments in decision making at the planning phase of housing development. Moreover, this study provides a new process framework for decision making at the planning phase of housing development in Malaysia and assists housing developers and governments to make better predictions before proceeding to the construction phase