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CONFIRMS: A Toolkit for Scalable, Black Box Connectome Assessment and Investigation

The nanoscale connectomics community has recently generated automated and semi-automated “wiring diagrams” of brain subregions from terabytes and petabytes of dense 3D neuroimagery. This process involves many challenging and imperfect technical steps, including dense 3D image segmentation, anisotrop...

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Detalles Bibliográficos
Autores principales: Bishop, Caitlyn, Matelsky, Jordan, Wilt, Miller, Downs, Joseph, Rivlin, Patricia, Plaza, Stephen, Wester, Brock, Gray-Roncal, William
Formato: Online Artículo Texto
Lenguaje:English
Publicado: 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9073849/
https://www.ncbi.nlm.nih.gov/pubmed/34891774
http://dx.doi.org/10.1109/EMBC46164.2021.9630109
Descripción
Sumario:The nanoscale connectomics community has recently generated automated and semi-automated “wiring diagrams” of brain subregions from terabytes and petabytes of dense 3D neuroimagery. This process involves many challenging and imperfect technical steps, including dense 3D image segmentation, anisotropic nonrigid image alignment and coregistration, and pixel classification of each neuron and their individual synaptic connections. As data volumes continue to grow in size, and connectome generation becomes increasingly commonplace, it is important that the scientific community is able to rapidly assess the quality and accuracy of a connectome product to promote dataset analysis and reuse. In this work, we share our scalable toolkit for assessing the quality of a connectome reconstruction via targeted inquiry and large-scale graph analysis, and to provide insights into how such connectome proofreading processes may be improved and optimized in the future. We illustrate the applications and ecosystem on a recent reference dataset.