CAVE: Connectome Annotation Versioning Engine.
CAVE: Connectome Annotation Versioning Engine.
复制标题
CAVE：连接体注释版本控制引擎。
DOI：
10.1101/2023.07.26.550598
复制
发表时间：
2023
期刊：
影响因子：
--
通讯作者：
Bae,JA
中科院分区：
文献类型：
--
作者：
Dorkenwald,Sven;Schneider-Mizell,CaseyM;Brittain,Derrick;Halageri,Akhilesh;Jordan,Chris;Kemnitz,Nico;Castro,ManualA;Silversmith,William;Maitin-Shephard,Jeremy;Troidl,Jakob;Pfister,Hanspeter;Gillet,Valentin;Xenes,Daniel;Bae,JA
电子显微镜、图像分割和计算基础设施的进步产生了大规模且注释丰富的连接组数据集，这些数据集越来越多地在社区之间共享。为了实现协作，用户需要能够同时创建注释并通过校对纠正自动分割中的错误。在大型数据集中，每次校对编辑都会重新标记数百万体素和数千个注释（如突触）的细胞身份。为了进行分析，用户需要立即和可重复地访问这个不断变化和扩展的数据环境。在这里，我们提出了Connectome Annotation Versioning Engine（CAVE），这是一种计算基础设施，可为校对提供可扩展的解决方案，并为任意时间点的快速分析查询提供灵活的注释支持。作为一套Web服务部署，CAVE使分布式社区能够在高达千万亿次数据集（约1 mm3）中执行可重复的连接组分析，同时进行校对和注释。
Advances in electron microscopy, image segmentation and computational infrastructure have given rise to large-scale and richly annotated connectomic datasets, which are increasingly shared across communities. To enable collaboration, users need to be able to concurrently create annotations and correct errors in the automated segmentation by proofreading. In large datasets, every proofreading edit relabels cell identities of millions of voxels and thousands of annotations like synapses. For analysis, users require immediate and reproducible access to this changing and expanding data landscape. Here we present the Connectome Annotation Versioning Engine (CAVE), a computational infrastructure that provides scalable solutions for proofreading and flexible annotation support for fast analysis queries at arbitrary time points. Deployed as a suite of web services, CAVE empowers distributed communities to perform reproducible connectome analysis in up to petascale datasets (~1 mm3) while proofreading and annotating is ongoing.