ConnectomeExplorer: Query-Guided Visual Analysis of Large Volumetric Neuroscience Data

Beyer, Johanna; Al-Awami, Ali K.; Kasthuri, Narayanan; Lichtman, Jeff W.; Pfister, Hanspeter; Hadwiger, Markus

doi:10.1109/tvcg.2013.142

Cited by 65 publications

(79 citation statements)

References 42 publications

(54 reference statements)

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“…On a cell level, individual neurons can be represented as nodes in a connectivity graph, with synapses being the actual links between nodes. Examples of this are shown in the Viking Viewer [24] and ConnectomeExplorer [25]. None of these tools, however, support the visualization of astrocytes.…”

Section: Visualization For Connectomicsmentioning

confidence: 99%

“…The above preserves a relative spatial information regarding the abstracted anatomical objects. In more abstract connectivity visualizations, on the other hand, the spatial location of nodes is completely independent of their original spatial positions [25,18]. They are usually used in combination with other techniques such as linking and brushing to indicate in another view the selected object as a 3D model.…”

Section: Network Layoutsmentioning

confidence: 99%

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Abstractocyte: A Visual Tool for Exploring Nanoscale Astroglial Cells

Mohammed

Al-Awami

Beyer

et al. 2018

IEEE Trans. Visual. Comput. Graphics

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This thesis presents the design and implementation of Abstractocyte, a system for the visual analysis of astrocytes, and their relation to neurons, in nanoscale volumes of brain tissue. Astrocytes are glial cells, i.e., non-neuronal cells that support neurons and the nervous system. Even though glial cells make up around 50 percent of all cells in the mammalian brain, so far they have been far less studied than neurons. Nevertheless, the study of astrocytes has immense potential for understanding brain function. However, the complex and widely-branching structure of astrocytes requires high-resolution electron microscopy imaging and makes visualization and analysis challenging. Using Abstractocyte, biologists can explore the morphology of astrocytes at various visual abstraction levels, while simultaneously analyzing neighboring neurons and their connectivity. We define a novel, conceptual 2D abstraction space for jointly visualizing astrocytes and neurons. Neuroscientists can choose a joint visualization as a specific point in that 2D abstraction space. Dragging this point allows them to smoothly transition between different abstraction levels in an intuitive manner. We describe the design of Abstractocyte, and present three case studies in which neuroscientists have successfully used our system to assess astrocytic coverage of synapses, glycogen distribution in relation to synapses, and astrocyticmitochondria coverage.

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Section: Visualization For Connectomicsmentioning

confidence: 99%

Section: Network Layoutsmentioning

confidence: 99%

Abstractocyte: A Visual Tool for Exploring Nanoscale Astroglial Cells

Mohammed

Al-Awami

Beyer

et al. 2018

IEEE Trans. Visual. Comput. Graphics

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“…⃝ 2017 The Institute of Electronics, Information and Communication Engineers boring voxels when they satisfy a certain criterion, which is usually based on intensity thresholds [8] or a diffusion metric [9]. It allows fast segmentation and corresponds well to the volume data with ideal growing criteria.…”

Section: Copyright Cmentioning

confidence: 99%

A Hybrid Approach via SRG and IDE for Volume Segmentation

Wang

Tang

Zhang

et al. 2017

IEICE Trans. Inf. & Syst.

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SUMMARY Volume segmentation is of great significances for feature visualization and feature extraction, essentially volume segmentation can be viewed as generalized cluster. This paper proposes a hybrid approach via symmetric region growing (SRG) and information diffusion estimation (IDE) for volume segmentation, the volume dataset is over-segmented to series of subsets by SRG and then subsets are clustered by K-Means basing on distance-metric derived from IDE, experiments illustrate superiority of the hybrid approach with better segmentation performance.

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“…None of them, however, focus on exploring the connectivity between neurites at the level of individual synapses. More recently, we have presented ConnectomeExplorer [5], which supports fully dynamic visual queries, volume visualization of EM and segmentation data, as well as labeled meta-data such as synapse locations. However, in contrast to NeuroLines, ConnectomeExplorer does not focus on detailed neural connectivity analysis and does not offer visual abstractions of neurites and their synapses.…”

Section: Related Workmentioning

confidence: 99%

“…Our third contribution is the NeuroLines application, based on the topology-preserving visual abstraction of neurites to support the analysis of neurite connectivity. It is integrated into ConnectomeExplorer [5], a visualization and visual analysis framework for petascale connectomics data. Finally, our fourth contribution is a demonstration of the utility of NeuroLines, based on two case studies performed by domain experts on real-world connectomics data.…”

Section: Introductionmentioning

confidence: 99%