Workflow for Visualization of Neuroimaging Data with an Augmented Reality Device.
Ontology highlight
ABSTRACT:
SUBMITTER: Karmonik C
PROVIDER: S-EPMC5788830 | biostudies-other | 2018 Feb
REPOSITORIES: biostudies-other
Publications
Workflow for Visualization of Neuroimaging Data with an Augmented Reality Device.
Karmonik Christof C Boone Timothy B TB Khavari Rose R
Journal of digital imaging 20180201 1
Commercial availability of three-dimensional (3D) augmented reality (AR) devices has increased interest in using this novel technology for visualizing neuroimaging data. Here, a technical workflow and algorithm for importing 3D surface-based segmentations derived from magnetic resonance imaging data into a head-mounted AR device is presented and illustrated on selected examples: the pial cortical surface of the human brain, fMRI BOLD maps, reconstructed white matter tracts, and a brain network o ...[more]
Similar Datasets
Project description:Unlike traditional visualization methods, augmented reality (AR) inserts virtual objects and information directly into digital representations of the real world, which makes these objects and data more easily understood and interactive. The integration of AR and GIS is a promising way to display spatial information in context. However, most existing AR-GIS applications only provide local spatial information in a fixed location, which is exposed to a set of problems, limited legibility, information clutter and the incomplete spatial relationships. In addition, the indoor space structure is complex and GPS is unavailable, so that indoor AR systems are further impeded by the limited capacity of these systems to detect and display location and semantic information. To address this problem, the localization technique for tracking the camera positions was fused by Bluetooth low energy (BLE) and pedestrian dead reckoning (PDR). The multi-sensor fusion-based algorithm employs a particle filter. Based on the direction and position of the phone, the spatial information is automatically registered onto a live camera view. The proposed algorithm extracts and matches a bounding box of the indoor map to a real world scene. Finally, the indoor map and semantic information were rendered into the real world, based on the real-time computed spatial relationship between the indoor map and live camera view. Experimental results demonstrate that the average positioning error of our approach is 1.47 m, and 80% of proposed method error is within approximately 1.8 m. The positioning result can effectively support that AR and indoor map fusion technique links rich indoor spatial information to real world scenes. The method is not only suitable for traditional tasks related to indoor navigation, but it is also promising method for crowdsourcing data collection and indoor map reconstruction.
| S-EPMC8444080 | biostudies-literature
Project description:Lymphaticovenular anastomosis (LVA) is a widely performed surgical procedure for the treatment of lymphedema. For good LVA outcomes, identifying lymphatic vessels and venules is crucial. Photoacoustic lymphangiography (PAL) is a new technology for visualizing lymphatic vessels. It can depict lymphatic vessels at high resolution; therefore, this study focused on how to apply PAL for lymphatic surgery. To visualize lymphatic vessels, indocyanine green was injected as a color agent. PAI-05 was used as the photoacoustic imaging device. Lymphatic vessels and veins were visualized at 797- and 835-nm wavelengths. First, it was confirmed whether the branching of the vasculature as depicted by the PAL was consistent with the actual branching of the vasculature as confirmed intraoperatively. Second, to use PAL images for surgical planning, preoperative photoacoustic images were superimposed onto the patient limb through augmented reality (AR) glasses (MOVERIO Smart Glass BT-30E). Lymphatics and venule markings drawn using AR glasses were consistent with the actual intraoperative images obtained during LVA. To anastomose multiple lymphatic vessels, a site with abundant venous branching was selected as the incision site; and selecting the incision site became easier. The anatomical morphology obtained by PAL matched the surgical field. AR-based marking could be very useful in future LVA.
| S-EPMC8745664 | biostudies-literature
Project description:The rise of virtual and online education in recent years has led to the development and popularization of many online tools, notably three-dimensional (3D) models and augmented reality (AR), for visualizing various structures in chemical sciences. The majority of the developed tools focus on either small molecules or biological systems, as information regarding their structure can be easily accessed from online databases or obtained through relatively quick calculations. As such, due to a lack of crystallographic and theoretical data available for nonbiological macromolecules, there is a noticeable lack of accessible online tools for the visualization of polymers in 3D. Herein, using a few sample polymers, we showcase a workflow for the generation of 3D models using molecular dynamics and Blender. The 3D structures can then be hosted on p3d.in, where AR models can be generated automatically. Furthermore, the hosted 3D models can then be shared via quick response (QR) codes and used in various settings without the need to download any applications.
| S-EPMC10173869 | biostudies-literature
Project description:For years, immersive interfaces using virtual and augmented reality (AR) for molecular visualization and modeling have promised a revolution in the way how we teach, learn, communicate and work in chemistry, structural biology and related areas. However, most tools available today for immersive modeling require specialized hardware and software, and are costly and cumbersome to set up. These limitations prevent wide use of immersive technologies in education and research centers in a standardized form, which in turn prevents large-scale testing of the actual effects of such technologies on learning and thinking processes. Here, I discuss building blocks for creating marker-based AR applications that run as web pages on regular computers, and explore how they can be exploited to develop web content for handling virtual molecular systems in commodity AR with no more than a webcam- and internet-enabled computer. Examples span from displaying molecules, electron microscopy maps and molecular orbitals with minimal amounts of HTML code, to incorporation of molecular mechanics, real-time estimation of experimental observables and other interactive resources using JavaScript. These web apps provide virtual alternatives to physical, plastic-made molecular modeling kits, where the computer augments the experience with information about spatial interactions, reactivity, energetics, etc. The ideas and prototypes introduced here should serve as starting points for building active content that everybody can utilize online at minimal cost, providing novel interactive pedagogic material in such an open way that it could enable mass-testing of the effect of immersive technologies on chemistry education.
| S-EPMC7924717 | biostudies-literature
Project description:The use of augmented reality (AR) in providing three-dimensional (3D) visual support and image depth have been applied in education, tourism, historical studies, and medical training. In research and development, there has been a slow but growing use of AR tools in chemical and drug discovery, but little has been implemented for whole 3D antibody structures (IgE, IgM, IgA, IgG, and IgD) and in communicating their interactions with the antigens or receptors in publications. Given that antibody interactions can vary significantly between different monoclonal antibodies, a convenient and easy to use 3D visualization can convey structural mechanisms clearer to readers, especially in how residues may interact with one another. While this was previously constrained to the use of stereo images on printed material or molecular visualization software on the computer, the revolution of smartphone and phablets now allows visualization of whole molecular structures on-the-go, allowing rotations, zooming in and out, and even animations without complex devices or the training of visual prowess. While not yet as versatile as molecular visualization software on the computer, such technology is an improvement from stereo-images and bridges the gap with molecular visualization tools. In this report, we discuss the use of AR and how they can be employed in the holistic view of antibodies and the future of the technology for better scientific communication.
| S-EPMC7990256 | biostudies-literature
Project description:PurposeTo evaluate the utility of visualizing preprocedural MR images in 3-dimensional (3D) space using augmented reality (AR) before transarterial embolization of hepatocellular carcinoma (HCC) in a preclinical model.Materials and methodsA total of 28 rats with diethylnitrosamine-induced HCCs > 5 mm treated with embolization were included in a prospective study. In 12 rats, 3D AR visualization of preprocedural MR images was performed before embolization. Procedural metrics including catheterization time and radiation exposure were compared vs a prospective cohort of 16 rats in which embolization was performed without AR. An additional cohort of 15 retrospective cases was identified and combined with the prospective control cohort (n = 31) to improve statistical power.ResultsA 37% reduction in fluoroscopy time, from 11.7 min to 7.4 minutes, was observed with AR when compared prospectively, which did not reach statistical significance (P = .12); however, when compared with combined prospective and retrospective controls, the reduction in fluoroscopy time from 14.1 min to 7.4 minutes (48%) was significant (P = .01). A 27% reduction in total catheterization time, from 42.7 minutes to 31.0 minutes, was also observed with AR when compared prospectively, which did not reach statistical significance (P = .11). No significant differences were seen in dose-area product or air kerma prospectively.ConclusionsThree-dimensional AR visualization of preprocedural imaging may aid in the reduction of procedural metrics in a preclinical model of transarterial embolization. These data support the need for further studies to evaluate the potential of AR in endovascular oncologic interventions.
| S-EPMC7541417 | biostudies-literature
Project description:To investigate the accuracy of augmented reality (AR) navigation using the Magic Leap head mounted device (HMD), pedicle screws were minimally invasively placed in four spine phantoms. AR navigation provided by a combination of a conventional navigation system integrated with the Magic Leap head mounted device (AR-HMD) was used. Forty-eight screws were planned and inserted into Th11-L4 of the phantoms using the AR-HMD and navigated instruments. Postprocedural CT scans were used to grade the technical (deviation from the plan) and clinical (Gertzbein grade) accuracy of the screws. The time for each screw placement was recorded. The mean deviation between navigation plan and screw position was 1.9 ± 0.7 mm (1.9 [0.3-4.1] mm) at the entry point and 1.4 ± 0.8 mm (1.2 [0.1-3.9] mm) at the screw tip. The angular deviation was 3.0 ± 1.4° (2.7 [0.4-6.2]°) and the mean time for screw placement was 130 ± 55 s (108 [58-437] s). The clinical accuracy was 94% according to the Gertzbein grading scale. The combination of an AR-HMD with a conventional navigation system for accurate minimally invasive screw placement is feasible and can exploit the benefits of AR in the perspective of the surgeon with the reliability of a conventional navigation system.
| S-EPMC8779462 | biostudies-literature
Project description:Augmenting reality via head-mounted displays (HMD-AR) is an emerging technology in education. The interactivity provided by HMD-AR devices is particularly promising for learning, but presents a challenge to human activity recognition, especially with children. Recent technological advances regarding speech and gesture recognition concerning Microsoft's HoloLens 2 may address this prevailing issue. In a within-subjects study with 47 elementary school children (2nd to 6th grade), we examined the usability of the HoloLens 2 using a standardized tutorial on multimodal interaction in AR. The overall system usability was rated "good". However, several behavioral metrics indicated that specific interaction modes differed in their efficiency. The results are of major importance for the development of learning applications in HMD-AR as they partially deviate from previous findings. In particular, the well-functioning recognition of children's voice commands that we observed represents a novelty. Furthermore, we found different interaction preferences in HMD-AR among the children. We also found the use of HMD-AR to have a positive effect on children's activity-related achievement emotions. Overall, our findings can serve as a basis for determining general requirements, possibilities, and limitations of the implementation of educational HMD-AR environments in elementary school classrooms.
| S-EPMC8512836 | biostudies-literature
Project description:The visualization of medical images with advanced techniques, such as augmented reality and virtual reality, represent a breakthrough for medical professionals. In contrast to more traditional visualization tools lacking 3D capabilities, these systems use the three available dimensions. To visualize medical images in 3D, the anatomical areas of interest must be segmented. Currently, manual segmentation, which is the most commonly used technique, and semi-automatic approaches can be time consuming because a doctor is required, making segmentation for each individual case unfeasible. Using new technologies, such as computer vision and artificial intelligence for segmentation algorithms and augmented and virtual reality for visualization techniques implementation, we designed a complete platform to solve this problem and allow medical professionals to work more frequently with anatomical 3D models obtained from medical imaging. As a result, the Nextmed project, due to the different implemented software applications, permits the importation of digital imaging and communication on medicine (dicom) images on a secure cloud platform and the automatic segmentation of certain anatomical structures with new algorithms that improve upon the current research results. A 3D mesh of the segmented structure is then automatically generated that can be printed in 3D or visualized using both augmented and virtual reality, with the designed software systems. The Nextmed project is unique, as it covers the whole process from uploading dicom images to automatic segmentation, 3D reconstruction, 3D visualization, and manipulation using augmented and virtual reality. There are many researches about application of augmented and virtual reality for medical image 3D visualization; however, they are not automated platforms. Although some other anatomical structures can be studied, we focused on one case: a lung study. Analyzing the application of the platform to more than 1000 dicom images and studying the results with medical specialists, we concluded that the installation of this system in hospitals would provide a considerable improvement as a tool for medical image visualization.
| S-EPMC7288297 | biostudies-literature
Project description:Single-cell assays have transformed our ability to model heterogeneity within cell populations. As these assays have advanced in their ability to measure various aspects of molecular processes in cells, computational methods to analyze and meaningfully visualize such data have required matched innovation. Independently, Virtual Reality (VR) has recently emerged as a powerful technology to dynamically explore complex data and shows promise for adaptation to challenges in single-cell data visualization. However, adopting VR for single-cell data visualization has thus far been hindered by expensive prerequisite hardware or advanced data preprocessing skills. To address current shortcomings, we present singlecellVR, a user-friendly web application for visualizing single-cell data, designed for cheap and easily available virtual reality hardware (e.g., Google Cardboard, ∼$8). singlecellVR can visualize data from a variety of sequencing-based technologies including transcriptomic, epigenomic, and proteomic data as well as combinations thereof. Analysis modalities supported include approaches to clustering as well as trajectory inference and visualization of dynamical changes discovered through modelling RNA velocity. We provide a companion software package, scvr to streamline data conversion from the most widely-adopted single-cell analysis tools as well as a growing database of pre-analyzed datasets to which users can contribute.
| S-EPMC8582280 | biostudies-literature