Virtual Reality applied to biomedical engineering

Actualment, la realitat virtual esta sent tendència i s'està expandint a l'àmbit mèdic, fent possible l'aparició de nombroses aplicacions dissenyades per entrenar metges i tractar pacients de forma més eficient, així com optimitzar els processos de planificació quirúrgica. La necessitat mèdica i objectiu d'aquest projecte és fer òptim el procés de planificació quirúrgica per a cardiopaties congènites, que compren la reconstrucció en 3D del cor del pacient i la seva integració en una aplicació de realitat virtual. Seguint aquesta línia s’ha combinat un procés de modelat 3D d’imatges de cors obtinguts gracies al Hospital Sant Joan de Déu i el disseny de l’aplicació mitjançant el software Unity 3D gracies a l’empresa VISYON. S'han aconseguit millores en quant al software emprat per a la segmentació i reconstrucció, i s’han assolit funcionalitats bàsiques a l’aplicació com importar, moure, rotar i fer captures de pantalla en 3D de l'òrgan cardíac i així, entendre millor la cardiopatia que s’ha de tractar. El resultat ha estat la creació d'un procés òptim, en el que la reconstrucció en 3D ha aconseguit ser ràpida i precisa, el mètode d’importació a l’app dissenyada molt senzill, i una aplicació que permet una interacció atractiva i intuïtiva, gracies a una experiència immersiva i realista per ajustar-se als requeriments d'eficiència i precisió exigits en el camp mèdic

Immersive Visualization for Enhanced Computational Fluid Dynamics Analysis

Modern biomedical computer simulations produce spatiotemporal results that are often viewed at a single point in time on standard 2D displays. An immersive visualization environment (IVE) with 3D stereoscopic capability can mitigate some shortcomings of 2D displays via improved depth cues and active movement to further appreciate the spatial localization of imaging data with temporal computational fluid dynamics (CFD) results. We present a semi-automatic workflow for the import, processing, rendering, and stereoscopic visualization of high resolution, patient-specific imaging data, and CFD results in an IVE. Versatility of the workflow is highlighted with current clinical sequelae known to be influenced by adverse hemodynamics to illustrate potential clinical utility

Trends in virtual reality technologies for the learning patient

NextMed convened the Medicine Meets Virtual Reality 22 (MMVR 22) conference in 2016. Since 1992, the conference has brought together a diverse group of researchers to share creative solutions for the evolving challenge of integrating virtual reality tools into medical education. Virtual reality (VR) and its enabling technologies utilize hardware and software to simulate environments and encounters where users can interact and learn. The MMVR 22 symposium proceedings contain projects that support a variety of learners: medical students, practitioners, soldiers, and patients. This report will contemplate the trends in virtual reality technologies for patients navigating their medical and healthcare learning. The learning patient seeks more than intervention; they seek prevention. From virtual humans and environments to motion sensors and haptic devices, patients are surrounded by increasingly rich and transformative data-driven tools. Applied data enables VR applications to simulate experience, predict health outcomes, and motivate new behavior. The MMVR 22 presents investigations into the usability of wearable devices, the efficacy of avatar inclusion, and the viability of multi-player gaming. With increasing need for individualized and scalable programming, only committed open source efforts will align instructional designers, technology integrators, trainers, and clinicians. Curriculum and InstructionCurriculum and Instructio

Advanced Visualization and Intuitive User Interface Systems for Biomedical Applications

Modern scientific research produces data at rates that far outpace our ability to comprehend and analyze it. Such sources include medical imaging data and computer simulations, where technological advancements and spatiotemporal resolution generate increasing amounts of data from each scan or simulation. A bottleneck has developed whereby medical professionals and researchers are unable to fully use the advanced information available to them. By integrating computer science, computer graphics, artistic ability and medical expertise, scientific visualization of medical data has become a new field of study. The objective of this thesis is to develop two visualization systems that use advanced visualization, natural user interface technologies and the large amount of biomedical data available to produce results that are of clinical utility and overcome the data bottleneck that has developed. Computational Fluid Dynamics (CFD) is a tool used to study the quantities associated with the movement of blood by computer simulation. We developed methods of processing spatiotemporal CFD data and displaying it in stereoscopic 3D with the ability to spatially navigate through the data. We used this method with two sets of display hardware: a full-scale visualization environment and a small-scale desktop system. The advanced display and data navigation abilities provide the user with the means to better understand the relationship between the vessel\u27s form and function. Low-cost 3D, depth-sensing cameras capture and process user body motion to recognize motions and gestures. Such devices allow users to use hand motions as an intuitive interface to computer applications. We developed algorithms to process and prepare the biomedical and scientific data for use with a custom control application. The application interprets user gestures as commands to a visualization tool and allows the user to control the visualization of multi-dimensional data. The intuitive interface allows the user to control the visualization of data without manual contact with an interaction device. In developing these methods and software tools we have leveraged recent trends in advanced visualization and intuitive interfaces in order to efficiently visualize biomedical data in such a way that provides meaningful information that can be used to further appreciate it

INFORMATION TECHNOLOGY FOR NEXT-GENERATION OF SURGICAL ENVIRONMENTS

Minimally invasive surgeries (MIS) are fundamentally constrained by image quality,access to the operative field, and the visualization environment on which thesurgeon relies for real-time information. Although invasive access benefits the patient,it also leads to more challenging procedures, which require better skills andtraining. Endoscopic surgeries rely heavily on 2D interfaces, introducing additionalchallenges due to the loss of depth perception, the lack of 3-Dimensional imaging,and the reduction of degrees of freedom.By using state-of-the-art technology within a distributed computational architecture,it is possible to incorporate multiple sensors, hybrid display devices, and3D visualization algorithms within a exible surgical environment. Such environmentscan assist the surgeon with valuable information that goes far beyond what iscurrently available. In this thesis, we will discuss how 3D visualization and reconstruction,stereo displays, high-resolution display devices, and tracking techniques arekey elements in the next-generation of surgical environments

Dynamic Volume Rendering of Functional Medical Data on Dissimilar Hardware Platforms

In the last 30 years, medical imaging has become one of the most used diagnostic tools in the medical profession. Computed Tomography (CT) and Magnetic Resonance Imaging (MRI) technologies have become widely adopted because of their ability to capture the human body in a non-invasive manner. A volumetric dataset is a series of orthogonal 2D slices captured at a regular interval, typically along the axis of the body from the head to the feet. Volume rendering is a computer graphics technique that allows volumetric data to be visualized and manipulated as a single 3D object. Iso-surface rendering, image splatting, shear warp, texture slicing, and raycasting are volume rendering methods, each with associated advantages and disadvantages. Raycasting is widely regarded as the highest quality renderer of these methods. Originally, CT and MRI hardware was limited to providing a single 3D scan of the human body. The technology has improved to allow a set of scans capable of capturing anatomical movements like a beating heart. The capturing of anatomical data over time is referred to as functional imaging. Functional MRI (fMRI) is used to capture changes in the human body over time. While fMRI’s can be used to capture any anatomical data over time, one of the more common uses of fMRI is to capture brain activity. The fMRI scanning process is typically broken up into a time consuming high resolution anatomical scan and a series of quick low resolution scans capturing activity. The low resolution activity data is mapped onto the high resolution anatomical data to show changes over time. Academic research has advanced volume rendering and specifically fMRI volume rendering. Unfortunately, academic research is typically a one-off solution to a singular medical case or set of data, causing any advances to be problem specific as opposed to a general capability. Additionally, academic volume renderers are often designed to work on a specific device and operating system under controlled conditions. This prevents volume rendering from being used across the ever expanding number of different computing devices, such as desktops, laptops, immersive virtual reality systems, and mobile computers like phones or tablets. This research will investigate the feasibility of creating a generic software capability to perform real-time 4D volume rendering, via raycasting, on desktop, mobile, and immersive virtual reality platforms. Implementing a GPU-based 4D volume raycasting method for mobile devices will harness the power of the increasing number of mobile computational devices being used by medical professionals. Developing support for immersive virtual reality can enhance medical professionals’ interpretation of 3D physiology with the additional depth information provided by stereoscopic 3D. The results of this research will help expand the use of 4D volume rendering beyond the traditional desktop computer in the medical field. Developing the same 4D volume rendering capabilities across dissimilar platforms has many challenges. Each platform relies on their own coding languages, libraries, and hardware support. There are tradeoffs between using languages and libraries native to each platform and using a generic cross-platform system, such as a game engine. Native libraries will generally be more efficient during application run-time, but they require different coding implementations for each platform. The decision was made to use platform native languages and libraries in this research, whenever practical, in an attempt to achieve the best possible frame rates. 4D volume raycasting provides unique challenges independent of the platform. Specifically, fMRI data loading, volume animation, and multiple volume rendering. Additionally, real-time raycasting has never been successfully performed on a mobile device. Previous research relied on less computationally expensive methods, such as orthogonal texture slicing, to achieve real-time frame rates. These challenges will be addressed as the contributions of this research. The first contribution was exploring the feasibility of generic functional data input across desktop, mobile, and immersive virtual reality. To visualize 4D fMRI data it was necessary to build in the capability to read Neuroimaging Informatics Technology Initiative (NIfTI) files. The NIfTI format was designed to overcome limitations of 3D file formats like DICOM and store functional imagery with a single high-resolution anatomical scan and a set of low-resolution anatomical scans. Allowing input of the NIfTI binary data required creating custom C++ routines, as no object oriented APIs freely available for use existed. The NIfTI input code was built using C++ and the C++ Standard Library to be both light weight and cross-platform. Multi-volume rendering is another challenge of fMRI data visualization and a contribution of this work. fMRI data is typically broken into a single high-resolution anatomical volume and a series of low-resolution volumes that capture anatomical changes. Visualizing two volumes at the same time is known as multi-volume visualization. Therefore, the ability to correctly align and scale the volumes relative to each other was necessary. It was also necessary to develop a compositing method to combine data from both volumes into a single cohesive representation. Three prototype applications were built for the different platforms to test the feasibility of 4D volume raycasting. One each for desktop, mobile, and virtual reality. Although the backend implementations were required to be different between the three platforms, the raycasting functionality and features were identical. Therefore, the same fMRI dataset resulted in the same 3D visualization independent of the platform itself. Each platform uses the same NIfTI data loader and provides support for dataset coloring and windowing (tissue density manipulation). The fMRI data can be viewed changing over time by either animation through the time steps, like a movie, or using an interface slider to “scrub” through the different time steps of the data. The prototype applications data load times and frame rates were tested to determine if they achieved the real-time interaction goal. Real-time interaction was defined by achieving 10 frames per second (fps) or better, based on the work of Miller [1]. The desktop version was evaluated on a 2013 MacBook Pro running OS X 10.12 with a 2.6 GHz Intel Core i7 processor, 16 GB of RAM, and a NVIDIA GeForce GT 750M graphics card. The immersive application was tested in the C6 CAVE™, a 96 graphics node computer cluster comprised of NVIDIA Quadro 6000 graphics cards running Red Hat Enterprise Linux. The mobile application was evaluated on a 2016 9.7” iPad Pro running iOS 9.3.4. The iPad had a 64-bit Apple A9X dual core processor with 2 GB of built in memory. Two different fMRI brain activity datasets with different voxel resolutions were used as test datasets. Datasets were tested using both the 3D structural data, the 4D functional data, and a combination of the two. Frame rates for the desktop implementation were consistently above 10 fps, indicating that real-time 4D volume raycasting is possible on desktop hardware. The mobile and virtual reality platforms were able to perform real-time 3D volume raycasting consistently. This is a marked improvement for 3D mobile volume raycasting that was previously only able to achieve under one frame per second [2]. Both VR and mobile platforms were able to raycast the 4D only data at real-time frame rates, but did not consistently meet 10 fps when rendering both the 3D structural and 4D functional data simultaneously. However, 7 frames per second was the lowest frame rate recorded, indicating that hardware advances will allow consistent real-time raycasting of 4D fMRI data in the near future

Challenges and Strategies for Educational Virtual Reality

Virtual reality (VR) is a rich visualization and analytic platform that furthers the library’s mission of providing access to all forms of information and supporting pedagogy and scholarship across disciplines. Academic libraries are increasingly adopting VR technology for a variety of research and teaching purposes, which include providing enhanced access to digital collections, offering new research tools, and constructing new immersive learning environments for students. This trend suggests that positive technological innovation is flourishing in libraries, but there remains a lack of clear guidance in the library community on how to introduce these technologies in effective ways and make them sustainable within different types of institutions. In June 2018, the University of Oklahoma hosted the second of three forums on the use of 3D and VR for visualization and analysis in academic libraries, as part of the project Developing Library Strategy for 3D and Virtual Reality Collection Development and Reuse(LIB3DVR), funded by a grant from the Institute of Museum and Library Services. This qualitative study invited experts from a range of disciplines and sectors to identify common challenges in the visualization and analysis of 3D data, and the management of VR programs, for the purpose of developing a national library strategy