webTDat: A Web-Based, Real-Time, 3D Visualization Framework for Mesoscopic Whole-Brain Images

Abstract

The popularity of mesoscopic whole-brain imaging techniques has increased dramatically, but these techniques generate teravoxel-sized volumetric image data. Visualizing or interacting with these massive data is both necessary and essential in the bioimage analysis pipeline; however, due to their size, researchers have difficulty using typical computers to process them. The existing solutions do not consider applying web visualization and three-dimensional (3D) volume rendering methods simultaneously to reduce the number of data copy operations and provide a better way to visualize 3D structures in bioimage data. Here, we propose webTDat, an open-source, web-based, real-time 3D visualization framework for mesoscopic-scale whole-brain imaging datasets. webTDat uses an advanced rendering visualization method designed with an innovative data storage format and parallel rendering algorithms. webTDat loads the primary information in the image first and then decides whether it needs to load the secondary information in the image. By performing validation on TB-scale whole-brain datasets, webTDat achieves real-time performance during web visualization. The webTDat framework also provides a rich interface for annotation, making it a useful tool for visualizing mesoscopic whole-brain imaging data.

Project, toolkit, and database of neuroinformatics ecosystem: A summary of previous studies on “Frontiers in Neuroinformatics”

“…At the meso/macro scale brain regions, visualization tools fall into two categories. The first is the visualization tool for a single mode, such as EEGVIS (Robbins, 2012 ), BrainBroswer (Tarek et al, 2014 ), Procortex (Gao et al, 2015 ), Fiberweb (Louis-Philippe et al, 2017 ), and webTaDat (Li et al, 2021 ); the second category is the visualization tools compatible with multi-modal data, such as DataView3D (Gouws et al, 2009 ), the virtual brain (Marmaduke et al, 2014 ), iBrainEEG (Rojas et al, 2016 ), and Visbrain (Combrisson et al, 2019 ).…”