Department of Computer Science, University of California, Irvine, Irvine, CA, United States.
Department of Anatomy and Neurobiology, School of Medicine, University of California, Irvine, Irvine, CA, United States.
Front Neural Circuits. 2024 Jul 10;18:1398884. doi: 10.3389/fncir.2024.1398884. eCollection 2024.
In the realm of neuroscience, mapping the three-dimensional (3D) neural circuitry and architecture of the brain is important for advancing our understanding of neural circuit organization and function. This study presents a novel pipeline that transforms mouse brain samples into detailed 3D brain models using a collaborative data analytics platform called "Texera." The user-friendly Texera platform allows for effective interdisciplinary collaboration between team members in neuroscience, computer vision, and data processing. Our pipeline utilizes the tile images from a serial two-photon tomography/TissueCyte system, then stitches tile images into brain section images, and constructs 3D whole-brain image datasets. The resulting 3D data supports downstream analyses, including 3D whole-brain registration, atlas-based segmentation, cell counting, and high-resolution volumetric visualization. Using this platform, we implemented specialized optimization methods and obtained significant performance enhancement in workflow operations. We expect the neuroscience community can adopt our approach for large-scale image-based data processing and analysis.
在神经科学领域,绘制三维(3D)神经回路和大脑结构对于深入了解神经回路组织和功能至关重要。本研究提出了一种新颖的管道,使用名为“Texera”的协作数据分析平台将小鼠脑组织样本转化为详细的 3D 大脑模型。用户友好的 Texera 平台允许神经科学、计算机视觉和数据处理领域的团队成员之间进行有效的跨学科合作。我们的管道利用来自串行双光子断层扫描/组织细胞系统的平铺图像,然后将平铺图像拼接成脑切片图像,并构建 3D 全脑图像数据集。生成的 3D 数据支持下游分析,包括 3D 全脑配准、基于图谱的分割、细胞计数和高分辨率体积可视化。我们使用这个平台实现了专门的优化方法,并在工作流程操作中获得了显著的性能提升。我们希望神经科学界可以采用我们的方法进行大规模的基于图像的数据处理和分析。