Embodied geosensification-models, taxonomies and applications for engaging the body in immersive analytics of geospatial data

This thesis examines how we can use immersive multisensory displays and body-focused interaction technologies to analyze geospatial data. It merges relevant aspects from an array of interdisciplinary research areas, from cartography to the cognitive sciences, to form three taxonomies that describe the senses, data representations, and interactions made possible by these technologies. These taxonomies are then integrated into an overarching design model for such "Embodied Geosensifications". This model provides guidance for system specification and is validated with practical examples

Integrating light-sheet imaging with virtual reality to recapitulate developmental cardiac mechanics

Currently, there is a limited ability to interactively study developmental cardiac mechanics and physiology. We therefore combined light-sheet fluorescence microscopy (LSFM) with virtual reality (VR) to provide a hybrid platform for 3D architecture and time-dependent cardiac contractile function characterization. By taking advantage of the rapid acquisition, high axial resolution, low phototoxicity, and high fidelity in 3D and 4D (3D spatial + 1D time or spectra), this VR-LSFM hybrid methodology enables interactive visualization and quantification otherwise not available by conventional methods, such as routine optical microscopes. We hereby demonstrate multiscale applicability of VR-LSFM to (a) interrogate skin fibroblasts interacting with a hyaluronic acid–based hydrogel, (b) navigate through the endocardial trabecular network during zebrafish development, and (c) localize gene therapy-mediated potassium channel expression in adult murine hearts. We further combined our batch intensity normalized segmentation algorithm with deformable image registration to interface a VR environment with imaging computation for the analysis of cardiac contraction. Thus, the VR-LSFM hybrid platform demonstrates an efficient and robust framework for creating a user-directed microenvironment in which we uncovered developmental cardiac mechanics and physiology with high spatiotemporal resolution