Interactive visualization of volumetric data with WebGL in real-time

Congote, John; Segura, Álvaro; Kabongo, Luis; Moreno, Aitor; Posada, Jorge; Ruiz-Salguero, Oscar

doi:10.1145/2010425.2010449

Cited by 82 publications

(51 citation statements)

References 19 publications

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“…WebGL provides hardware-based rendering, allowing fast and real-time visualizations. WebGL is designed for dynamic web applications (Parisi, 2012), and examples have been developed to implement 3D interactive visualization using WebGL (e.g., Congote et al, 2011;Birr et al, 2012;Henning et al,2013).…”

Section: Webgl Definitionmentioning

confidence: 99%

Web-based interactive visualization of PS-InSAR point clouds for education and training

Dong

Balz

Wang

et al. 2014

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci.

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ABSTRACT:In radar remote sensing education and training, only few people have a good knowledge of radar remote sensing and geology, which would be necessary fully analyse the surface motions estimated by persistent scatterer interferometry. Using scientific visualization, data can be presented in an intuitive way for surface motion analysis of non-radar experts. In this paper, we introduce a web-based interactive visualization of PS-InSAR point clouds for education and training.

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Section: Webgl Definitionmentioning

confidence: 99%

Web-based interactive visualization of PS-InSAR point clouds for education and training

Dong

Balz

Wang

et al. 2014

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci.

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Section: B Volume Renderingmentioning

confidence: 99%

“…The first set of experiments was conducted on both SYSTEM1 and SYSTEM2 to compare the performance of our single pass GPU ray caster against the current state-of-the-art WebGL ray caster [9]. For this experiment, we used the composite rendering mode with transfer function (shown in Fig.…”

Section: A Comparison Of Single-pass Ray Caster To Multi-pass Ray Camentioning

confidence: 99%

“…However, there are very few reports on using WebGL for volume rendering. The only relevant work was reported in [9]. The authors presented an algorithm for extracting the 2D slice from the 2D flat texture layout.…”

mentioning

confidence: 99%

“…Since WebGL is based on the OpenGL ES 2.0 API which is a restricted subset of the desktop OpenGL, there are some functionalities missing, in particular, there is no 3D texture which is a crucial requirement for volume rendering. As shown in the figure, in our design, this limitation is circumvented by tiling each slice of the 3D texture into a 2D flat texture layout [9].The volume rendering approach is based on an optical model to approximate the emission/absorption characteristics of the participating medium. The volume rendering integral models the emission, absorption and transmission properties that map the physical attributes stored in the 3D density function.…”

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confidence: 99%

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Mobile Visualization of Biomedical Volume Datasets

Mobeen¹,

Lin²

2012

JITST

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Abstract-The WebGL platform has been introduced based on the OpenGL ES 2.0 API. It allows scripts embedded in a web browser to have native access to GPU hardware. Now that more and more real-time systems are moving towards a cloud-based architecture, it becomes important to capitalize on existing tools to extend the biomedical imaging and visualization domain. One such tool that can enable ubiquitous biomedical imaging and visualization is the WebGL platform. Existing work relies on a multi-pass strategy. We extend the visualization using a single pass approach. This gives much better performance especially on the mobile platforms where every additional texture access is costly. Quantitative evaluation reveals that the proposed algorithm outperforms the existing algorithm by a consistent 2x speedup not only on desktop platforms but also on the mobile platforms. Current mobile phones and tablets have limited support for dynamic loops thus, sampling rate cannot be changed dynamically and high quality renderings cannot be carried out.To circumvent these problems, we present the first 3D texture slicer. Since 3D texture slicing uses the rasterization hardware and support of the rasterizer is pervasive, we can not only modify the sampling rate but also carry out advanced effects. The design of our approach and extensive experiments are presented in this paper which proves the effectiveness of the proposed approach for pervasive biomedical data processing and visualization. Index Terms-Ubiquitous computing, Biomedical imaging, Data visualization, Biomedical image processing, Computer graphics I. INTRODUCTIONHE healthcare scenario has changed to accommodate better clinical decision and higher patient satisfaction. It has moved from traditional one-point contact to a conglomeration of multidisciplinary people working together to obtain best results. With the availability of internet, we have seen a large number of hospitals using integrated Health Information Systems (HIS) which help them to maintain a seamless flow of patient's information, insurance, clinical data, etc. between different departments. However, currently Manuscript received September 16, 2012. This work is partially supported by two research grants, M408020000 from Nanyang Technological University and M4080634.B40 from Institute for Media Innovation, NTU, and a grant MOE2011-T2-2-037 from Ministry of Education, Singapore.Movania Muhammad Mobeen is with the School of Computer Engineering, Nanyang Technological University, Singapore, e-mail: mova0002@ e.ntu.edu.sg.Lin Feng is with the School of Computer Engineering, Nanyang Technological University, Singapore, e-mail: asflin@ntu.edu.sg. these systems are often synonymous with filling innumerable forms and storing bulky files filled with patient information. In the instrumental examinations, such as Computed Tomography (CT) and Magnetic Resonance Imaging (MRI), the resulting images and documents have to be processed offline. Ambiguous and incomplete data, or data fragmentation, often lead to lack of overvi...

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Multiuser collaborative illustration and visualization for volumetric scientific data

et al. 2020

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Multiuser can collaboratively complete complex visualization tasks that cannot be completed by a single user. Although multiuser collaboration system has made great progress, there are many challenges in the collaborative visualization of 3D volumetric scientific data due to the difficulties in multiuser collaboration, and collaborative slice analysis. This article proposes a client‐server based collaborative visualization system, which consists of a 3D volume explorer and a 2D slice analyzer, to help domain experts to fully utilize their background domain knowledge to illustrate different parts of the data. For example, the brain surgeon expert, pulmonologist, and cardiologist can visualize and analyze the different subsets of the volumetric scientific data, that is, the corresponding subvolumes of the brain, heart, lungs, and blood vessels. It also allows taking full advantage of the hardware resources, because all the computation intensive tasks especially for the whole data rendering can be allocated to the powerful server while the light‐weight tasks can be allocated to the portable clients. Besides, we design a seed point tracing algorithm based on flood fill algorithm to illustrate the slice more efficiently. We evaluate the system by collecting the feedback from domain experts and the people who are unfamiliar with data computation or visualization. The evaluation shows that the 3D volume explorer and the 2D slice analyzer are capable of supporting peer‐expert discussion and medical case teaching, respectively.

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Interactive visualization of volumetric data with WebGL in real-time

Cited by 82 publications

References 19 publications

Web-based interactive visualization of PS-InSAR point clouds for education and training

Web-based interactive visualization of PS-InSAR point clouds for education and training

Mobile Visualization of Biomedical Volume Datasets

Multiuser collaborative illustration and visualization for volumetric scientific data

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