Exploring the Connectome: Petascale Volume Visualization of Microscopy Data Streams

Recent advances in high-resolution microscopy let neuroscientists acquire neural-tissue volume data of extremely large sizes. However, the tremendous resolution and the high complexity of neural structures present big challenges to storage, processing, and visualization at interactive rates. A proposed system provides interactive exploration of petascale (petavoxel) volumes resulting from high-throughput electron microscopy data streams. The system can concurrently handle multiple volumes and can support the simultaneous visualization of high-resolution voxel segmentation data. Its visualization-driven design restricts most computations to a small subset of the data. It employs a multiresolution virtual-memory architecture for better scalability than previous approaches and for handling incomplete data. Researchers have employed it for a 1-teravoxel mouse cortex volume, of which several hundred axons and dendrites as well as synapses have been segmented and labeled.

[1]  Bernd Hamann,et al.  Multiresolution techniques for interactive texture-based volume visualization , 1999, Proceedings Visualization '99 (Cat. No.99CB37067).

[2]  Rüdiger Westermann,et al.  Acceleration techniques for GPU-based volume rendering , 2003, IEEE Visualization, 2003. VIS 2003..

[3]  Kwan-Liu Ma,et al.  A Scalable, Hybrid Scheme for Volume Rendering Massive Data Sets y , 2022 .

[4]  Markus Hadwiger,et al.  High-Quality Multimodal Volume Rendering for Preoperative Planning of Neurosurgical Interventions , 2007, IEEE Transactions on Visualization and Computer Graphics.

[5]  E. Gobbetti,et al.  A single-pass GPU ray casting framework for interactive out-of-core rendering of massive volumetric datasets , 2008, The Visual Computer.

[6]  Markus Hadwiger,et al.  Scalable and Interactive Segmentation and Visualization of Neural Processes in EM Datasets , 2009, IEEE Transactions on Visualization and Computer Graphics.

[7]  Sylvain Lefebvre,et al.  GigaVoxels: ray-guided streaming for efficient and detailed voxel rendering , 2009, I3D '09.

[8]  Won-Ki Jeong,et al.  Interactive Histology of Large-Scale Biomedical Image Stacks , 2010, IEEE Transactions on Visualization and Computer Graphics.

[9]  Markus Hadwiger,et al.  Ssecrett and NeuroTrace: Interactive Visualization and Analysis Tools for Large-Scale Neuroscience Data Sets , 2010, IEEE Computer Graphics and Applications.

[10]  Valerio Pascucci,et al.  Interactive editing of massive imagery made simple: Turning Atlanta into Atlantis , 2011, TOGS.

[11]  Arthur W. Wetzel,et al.  Network anatomy and in vivo physiology of visual cortical neurons , 2011, Nature.

[12]  Klaus Engel,et al.  CERA-TVR: A framework for interactive high-quality teravoxel volume visualization on standard PCs , 2011, 2011 IEEE Symposium on Large Data Analysis and Visualization.

[13]  Markus Hadwiger,et al.  Interactive Volume Exploration of Petascale Microscopy Data Streams Using a Visualization-Driven Virtual Memory Approach , 2012, IEEE Transactions on Visualization and Computer Graphics.

[14]  Andrew R. McKinstry-Wu,et al.  Connectome: How the Brain’s Wiring Makes Us Who We Are , 2013 .