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显微镜驾驶舱:基于Python的生物医学定制显微镜。

Microscope-Cockpit: Python-based bespoke microscopy for bio-medical science.

作者信息

Phillips Mick A, Susano Pinto David Miguel, Hall Nicholas, Mateos-Langerak Julio, Parton Richard M, Titlow Josh, Stoychev Danail V, Parks Thomas, Susano Pinto Tiago, Sedat John W, Booth Martin J, Davis Ilan, Dobbie Ian M

机构信息

Micron Advanced Bioimaging Unit, Department of Biochemistry, University of Oxford, South Parks Road, Oxford, OX1 3QU, UK.

Diamond Light Source, Harwell Science and Innovation Campus, Didcot, OX11 0DE, UK.

出版信息

Wellcome Open Res. 2022 Jan 17;6:76. doi: 10.12688/wellcomeopenres.16610.1. eCollection 2021.

DOI:10.12688/wellcomeopenres.16610.1
PMID:37283605
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10240544/
Abstract

We have developed "Microscope-Cockpit" (Cockpit), a highly adaptable open source user-friendly Python-based Graphical User Interface (GUI) environment for precision control of both simple and elaborate bespoke microscope systems. The user environment allows next-generation near instantaneous navigation of the entire slide landscape for efficient selection of specimens of interest and automated acquisition without the use of eyepieces. Cockpit uses "Python-Microscope" (Microscope) for high-performance coordinated control of a wide range of hardware devices using open source software. Microscope also controls complex hardware devices such as deformable mirrors for aberration correction and spatial light modulators for structured illumination via abstracted device models. We demonstrate the advantages of the Cockpit platform using several bespoke microscopes, including a simple widefield system and a complex system with adaptive optics and structured illumination. A key strength of Cockpit is its use of Python, which means that any microscope built with Cockpit is ready for future customisation by simply adding new libraries, for example machine learning algorithms to enable automated microscopy decision making while imaging.

摘要

我们开发了“显微镜驾驶舱”(驾驶舱),这是一个高度适应性强的基于Python的开源用户友好型图形用户界面(GUI)环境,用于精确控制简单和复杂的定制显微镜系统。该用户环境允许下一代几乎即时地浏览整个载玻片视野,以便高效选择感兴趣的标本并在不使用目镜的情况下进行自动采集。“驾驶舱”使用“Python显微镜”(显微镜)通过开源软件对各种硬件设备进行高性能协调控制。“显微镜”还通过抽象设备模型控制复杂硬件设备,如用于像差校正的可变形镜和用于结构照明的空间光调制器。我们使用几种定制显微镜展示了“驾驶舱”平台的优势,包括一个简单的宽视场系统和一个具有自适应光学和结构照明的复杂系统。“驾驶舱”的一个关键优势是其使用Python,这意味着任何使用“驾驶舱”构建的显微镜只需简单添加新库(例如机器学习算法,以便在成像时实现自动显微镜决策)就可随时进行未来定制。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e08e/10285330/e1ef5dfc5544/wellcomeopenres-6-19384-g0006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e08e/10285330/229ee0227719/wellcomeopenres-6-19384-g0000.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e08e/10285330/82079ad192ee/wellcomeopenres-6-19384-g0001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e08e/10285330/6bf75d450c20/wellcomeopenres-6-19384-g0002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e08e/10285330/f6baec67b1ff/wellcomeopenres-6-19384-g0003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e08e/10285330/17993e168a7b/wellcomeopenres-6-19384-g0004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e08e/10285330/9e16b93e4676/wellcomeopenres-6-19384-g0005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e08e/10285330/e1ef5dfc5544/wellcomeopenres-6-19384-g0006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e08e/10285330/229ee0227719/wellcomeopenres-6-19384-g0000.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e08e/10285330/82079ad192ee/wellcomeopenres-6-19384-g0001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e08e/10285330/6bf75d450c20/wellcomeopenres-6-19384-g0002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e08e/10285330/f6baec67b1ff/wellcomeopenres-6-19384-g0003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e08e/10285330/17993e168a7b/wellcomeopenres-6-19384-g0004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e08e/10285330/9e16b93e4676/wellcomeopenres-6-19384-g0005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e08e/10285330/e1ef5dfc5544/wellcomeopenres-6-19384-g0006.jpg

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