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探索光片图像分析软件领域:从数据采集到分析的驱动一致性概念

Navigating the Light-Sheet Image Analysis Software Landscape: Concepts for Driving Cohesion From Data Acquisition to Analysis.

作者信息

Gibbs Holly C, Mota Sakina M, Hart Nathan A, Min Sun Won, Vernino Alex O, Pritchard Anna L, Sen Anindito, Vitha Stan, Sarasamma Sreeja, McIntosh Avery L, Yeh Alvin T, Lekven Arne C, McCreedy Dylan A, Maitland Kristen C, Perez Lisa M

机构信息

Department of Biomedical Engineering, Texas A&M University, College Station, TX, United States.

Microscopy and Imaging Center, Texas A&M University, College Station, TX, United States.

出版信息

Front Cell Dev Biol. 2021 Nov 1;9:739079. doi: 10.3389/fcell.2021.739079. eCollection 2021.

Abstract

From the combined perspective of biologists, microscope instrumentation developers, imaging core facility scientists, and high performance computing experts, we discuss the challenges faced when selecting imaging and analysis tools in the field of light-sheet microscopy. Our goal is to provide a contextual framework of basic computing concepts that cell and developmental biologists can refer to when mapping the peculiarities of different light-sheet data to specific existing computing environments and image analysis pipelines. We provide our perspective on efficient processes for tool selection and review current hardware and software commonly used in light-sheet image analysis, as well as discuss what ideal tools for the future may look like.

摘要

从生物学家、显微镜仪器开发者、成像核心设施科学家和高性能计算专家的综合视角出发,我们探讨了在光片显微镜领域选择成像和分析工具时所面临的挑战。我们的目标是提供一个基本计算概念的背景框架,细胞和发育生物学家在将不同光片数据的特性映射到特定的现有计算环境和图像分析流程时可以参考。我们阐述了工具选择的高效流程,并回顾了光片图像分析中常用的当前硬件和软件,还讨论了未来理想工具可能是什么样的。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1916/8631767/ff91e31ffe4e/fcell-09-739079-g001.jpg

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