Web DiVE- A Browser-Based Platform for Interactive dMRI Visualization
Poster No:
1791
Submission Type:
Abstract Submission
Authors:
Siddharth Narula1, Iyad Ba Gari1, Aarya Vakharia1, Neda Jahanshad2
Institutions:
1University of Southern California, Los Angeles, CA, 2University of Southern California,, Marina del Rey, CA
First Author:
Co-Author(s):
Introduction:
Diffusion MRI tractography is a technique used to analyze the brain's white matter (WM) pathways. Last year we presented the Diffusion Visualization Explorer (DiVE) Tool, designed for tractography visualization, offering integration of streamlines, masks, meshes and statistical overlays to aid brain connectivity analysis. We have since expanded the development of DiVE to include an interactive, browser-based component designed to streamline numerous forms of tractography visualization. The web-application provides the core functionality of the original DiVE, including visualization of above mentioned formats in the same space but removes the need for local software installation, making it easier to visualize brain tracts and related statistical metrics on both individual and population levels; we also aim to enhance the speed, accessibility, and interactivity of the original DiVE, allowing for faster data exploration. We release this as an open-source webpage for the neuroscience community.
Methods:
The core component of Web DiVE is Shiny (https://shiny.posit.co/py), a framework to create a reactive and dynamic interface, allowing users to interact in real time with 3D visualizations and adjusting parameters like colors, visibility, etc. We leverage ReactJS, a JavaScript library, to build custom user interfaces, render efficiently, and manage complex web components to create a smooth and interactive front-end experience where users can easily adjust visualization parameters and change different views without any performance lag. We use Plotly[1] to display 3D tractography streamlines, brain masks, and meshes and create 2D statistical plots. Like the original DiVE, the web application processes these data into 3D contours, fibers, and meshes. It also supports various formats (e.g tck, trk and trx) for visualization of streamlines. It allows centroid-based segmentation such as that used in automated fiber-tract quantification (AFQ) [2], and medial tractography analysis (MeTA) method [3], which use hyperplanes to take into account the fanning of WM bundles, to overlay statistical measures like t-values and p-values. The key feature of a web app is its real-time interactivity, where the user can manipulate the view and change colors, width, opacity, and statistical results, all from the comfort of a web browser. The integration of Plotly's interactive 3D rendering allows for zooming, panning, and rotation, enabling users to closely examine the spatial organization of the fiber bundles. Users can overlay brain masks and surface meshes on top of the tractography visualizations, with the option to map scalar values (such as tissue microstructure information) to color or opacity, offering a deeper understanding of the data.
Results:
Web DiVE has been made available at https://brainescience.shinyapps.io/dive with code available https://github.com/USC-LoBeS/web-dive. It provides a user-friendly visualization experience, eliminating the need for local software installation and configurations. This accessibility allows for more researchers to use the tool, without requiring computational resources. The interactive 3D and 2D visualization gives the user a dynamic real-time rendering. The user can add an overlay of brain masks and map on statistical results or labels. The compatibility with diverse tractography datatypes ensures seamless integration of user-generated data. Customizing rendering options allows researchers to store visualizations that meet their specific needs, enhancing presentation and publication quality (Figure 1).
Conclusions:
Web DiVE enhances the visualization of dMRI tractography and bundle data. Users are not required to install and configure applications on their local computers due to its web-based development. The app leverages the visualization features of the original DiVE and integrates it with modern web technology, making it quicker and easier to use. We invite the users to give us their feedback.
Modeling and Analysis Methods:
Diffusion MRI Modeling and Analysis
Neuroanatomy, Physiology, Metabolism and Neurotransmission:
White Matter Anatomy, Fiber Pathways and Connectivity 1
Neuroinformatics and Data Sharing:
Informatics Other 2
Novel Imaging Acquisition Methods:
Diffusion MRI
Keywords:
MRI
Open-Source Code
Open-Source Software
Tractography
WHITE MATTER IMAGING - DTI, HARDI, DSI, ETC
1|2Indicates the priority used for review
Abstract Information
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Provide references using APA citation style.
[2] Gari, Iyad Ba, et al. Along-Tract Parameterization of White Matter Microstructure Using Medial Tractography Analysis (MeTA). Institute of Electrical and Electronics Engineers Inc., 2023.
[3] Yeatman, Jason D., et al. “Tract Profiles of White Matter Properties: Automating Fiber-Tract Quantification.” PloS One, vol. 7, no. 11, Nov. 2012, p. e49790.
Acknowledgements:
This work is supported in part by NIH grants: R01MH134004, R01NS136995 and S10OD032285. Alzheimer’s Disease Neuroimaging Initiative (ADNI) database (adni.loni.usc.edu). As such, the investigators within the ADNI contributed to the design and implementation of ADNI and/or provided data but did not participate in analysis or writing of this report. A complete listing of ADNI investigators can be found at: http://adni.loni.usc.edu/wp-content/uploads/how_to_apply/ADNI_Acknowledgement_List.pdf.