Igneous: Distributed dense 3D segmentation meshing, neuron skeletonization, and hierarchical downsampling
Three-dimensional electron microscopy images of brain tissue and their dense segmentations are now petascale and growing. These volumes require the mass production of dense segmentation-derived neuron skeletons, multi-resolution meshes, image hierarchies (for both modalities) for visualization and a...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2022-11-01
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| Series: | Frontiers in Neural Circuits |
| Subjects: | |
| Online Access: | https://www.frontiersin.org/articles/10.3389/fncir.2022.977700/full |
| _version_ | 1828281357289127936 |
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| author | William Silversmith Aleksandar Zlateski Aleksandar Zlateski J. Alexander Bae J. Alexander Bae Ignacio Tartavull Nico Kemnitz Jingpeng Wu H. Sebastian Seung H. Sebastian Seung |
| author_facet | William Silversmith Aleksandar Zlateski Aleksandar Zlateski J. Alexander Bae J. Alexander Bae Ignacio Tartavull Nico Kemnitz Jingpeng Wu H. Sebastian Seung H. Sebastian Seung |
| author_sort | William Silversmith |
| collection | DOAJ |
| description | Three-dimensional electron microscopy images of brain tissue and their dense segmentations are now petascale and growing. These volumes require the mass production of dense segmentation-derived neuron skeletons, multi-resolution meshes, image hierarchies (for both modalities) for visualization and analysis, and tools to manage the large amount of data. However, open tools for large-scale meshing, skeletonization, and data management have been missing. Igneous is a Python-based distributed computing framework that enables economical meshing, skeletonization, image hierarchy creation, and data management using cloud or cluster computing that has been proven to scale horizontally. We sketch Igneous's computing framework, show how to use it, and characterize its performance and data storage. |
| first_indexed | 2024-04-13T08:14:44Z |
| format | Article |
| id | doaj.art-67106399db1f4c819fa84e17870aa527 |
| institution | Directory Open Access Journal |
| issn | 1662-5110 |
| language | English |
| last_indexed | 2024-04-13T08:14:44Z |
| publishDate | 2022-11-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Neural Circuits |
| spelling | doaj.art-67106399db1f4c819fa84e17870aa5272022-12-22T02:54:51ZengFrontiers Media S.A.Frontiers in Neural Circuits1662-51102022-11-011610.3389/fncir.2022.977700977700Igneous: Distributed dense 3D segmentation meshing, neuron skeletonization, and hierarchical downsamplingWilliam Silversmith0Aleksandar Zlateski1Aleksandar Zlateski2J. Alexander Bae3J. Alexander Bae4Ignacio Tartavull5Nico Kemnitz6Jingpeng Wu7H. Sebastian Seung8H. Sebastian Seung9Princeton Neuroscience Institute, Princeton University, Princeton, NJ, United StatesPrinceton Neuroscience Institute, Princeton University, Princeton, NJ, United StatesDepartment of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, MA, United StatesPrinceton Neuroscience Institute, Princeton University, Princeton, NJ, United StatesDepartment of Electrical and Computer Engineering, Princeton University, Princeton, NJ, United StatesPrinceton Neuroscience Institute, Princeton University, Princeton, NJ, United StatesPrinceton Neuroscience Institute, Princeton University, Princeton, NJ, United StatesPrinceton Neuroscience Institute, Princeton University, Princeton, NJ, United StatesPrinceton Neuroscience Institute, Princeton University, Princeton, NJ, United StatesDepartment of Computer Science, Princeton University, Princeton, NJ, United StatesThree-dimensional electron microscopy images of brain tissue and their dense segmentations are now petascale and growing. These volumes require the mass production of dense segmentation-derived neuron skeletons, multi-resolution meshes, image hierarchies (for both modalities) for visualization and analysis, and tools to manage the large amount of data. However, open tools for large-scale meshing, skeletonization, and data management have been missing. Igneous is a Python-based distributed computing framework that enables economical meshing, skeletonization, image hierarchy creation, and data management using cloud or cluster computing that has been proven to scale horizontally. We sketch Igneous's computing framework, show how to use it, and characterize its performance and data storage.https://www.frontiersin.org/articles/10.3389/fncir.2022.977700/fullmeshingskeletonizationneuroscienceconnectomicsimage processingcloud computing |
| spellingShingle | William Silversmith Aleksandar Zlateski Aleksandar Zlateski J. Alexander Bae J. Alexander Bae Ignacio Tartavull Nico Kemnitz Jingpeng Wu H. Sebastian Seung H. Sebastian Seung Igneous: Distributed dense 3D segmentation meshing, neuron skeletonization, and hierarchical downsampling Frontiers in Neural Circuits meshing skeletonization neuroscience connectomics image processing cloud computing |
| title | Igneous: Distributed dense 3D segmentation meshing, neuron skeletonization, and hierarchical downsampling |
| title_full | Igneous: Distributed dense 3D segmentation meshing, neuron skeletonization, and hierarchical downsampling |
| title_fullStr | Igneous: Distributed dense 3D segmentation meshing, neuron skeletonization, and hierarchical downsampling |
| title_full_unstemmed | Igneous: Distributed dense 3D segmentation meshing, neuron skeletonization, and hierarchical downsampling |
| title_short | Igneous: Distributed dense 3D segmentation meshing, neuron skeletonization, and hierarchical downsampling |
| title_sort | igneous distributed dense 3d segmentation meshing neuron skeletonization and hierarchical downsampling |
| topic | meshing skeletonization neuroscience connectomics image processing cloud computing |
| url | https://www.frontiersin.org/articles/10.3389/fncir.2022.977700/full |
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