Abstract
With high-throughput and high-resolution imaging technologies such as Knife-Edge Scanning Microscopy (KESM), it is possible to acquire teravoxel sized three-dimensional neuronal and microvascular images of the whole mouse brain with sub-micrometer resolution. It is imperative to be able to visualize and share these teravoxel volumes efficiently, to facilitate group efforts from research communities. However, due to the immense size of the data sets, sharing and managing them have always been a big challenge. This paper describes an image processing pipeline for a real-time 3D visualization framework that allows research groups to work in collaboration. The proposed work can visualize and share terabyte-sized three-dimensional images for study and analysis of mammalian brain morphology. Although the image processing pipeline used a KESM data set to show the feasibility of it, the proposed pipeline can also be used for other larger data sets. We believe that this novel framework for Web-based real-time 3D visualization can facilitate data sharing of teravoxel volumes across research communities.
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Ashwini, A., Kwon, J. (2018). Image Processing Pipeline for Web-Based Real-Time 3D Visualization of Teravoxel Volumes. In: Tan, Y., Shi, Y., Tang, Q. (eds) Data Mining and Big Data. DMBD 2018. Lecture Notes in Computer Science(), vol 10943. Springer, Cham. https://doi.org/10.1007/978-3-319-93803-5_19
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DOI: https://doi.org/10.1007/978-3-319-93803-5_19
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