Microscope-Cockpit: Python-based bespoke microscopy for bio-medical science
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 navigat...
| Main Authors: | , , , , , , , , , , , , |
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| Format: | Journal article |
| Language: | English |
| Published: |
F1000Research
2021
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| _version_ | 1797110362305200128 |
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| author | Phillips, MA Susano Pinto, DM Hall, N Mateos-Langerak, J Parton, RM Titlow, J Stoychev, DV Parks, T Susano Pinto, T Sedat, JW Booth, MJ Davis, I Dobbie, IM |
| author_facet | Phillips, MA Susano Pinto, DM Hall, N Mateos-Langerak, J Parton, RM Titlow, J Stoychev, DV Parks, T Susano Pinto, T Sedat, JW Booth, MJ Davis, I Dobbie, IM |
| author_sort | Phillips, MA |
| collection | OXFORD |
| description | 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. |
| first_indexed | 2024-03-07T07:53:55Z |
| format | Journal article |
| id | oxford-uuid:0a9eff98-c979-4e36-92f9-52345a5a1756 |
| institution | University of Oxford |
| language | English |
| last_indexed | 2024-03-07T07:53:55Z |
| publishDate | 2021 |
| publisher | F1000Research |
| record_format | dspace |
| spelling | oxford-uuid:0a9eff98-c979-4e36-92f9-52345a5a17562023-08-10T10:12:53ZMicroscope-Cockpit: Python-based bespoke microscopy for bio-medical scienceJournal articlehttp://purl.org/coar/resource_type/c_dcae04bcuuid:0a9eff98-c979-4e36-92f9-52345a5a1756EnglishSymplectic ElementsF1000Research2021Phillips, MASusano Pinto, DMHall, NMateos-Langerak, JParton, RMTitlow, JStoychev, DVParks, TSusano Pinto, TSedat, JWBooth, MJDavis, IDobbie, IMWe 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. |
| spellingShingle | Phillips, MA Susano Pinto, DM Hall, N Mateos-Langerak, J Parton, RM Titlow, J Stoychev, DV Parks, T Susano Pinto, T Sedat, JW Booth, MJ Davis, I Dobbie, IM Microscope-Cockpit: Python-based bespoke microscopy for bio-medical science |
| title | Microscope-Cockpit: Python-based bespoke microscopy for bio-medical science |
| title_full | Microscope-Cockpit: Python-based bespoke microscopy for bio-medical science |
| title_fullStr | Microscope-Cockpit: Python-based bespoke microscopy for bio-medical science |
| title_full_unstemmed | Microscope-Cockpit: Python-based bespoke microscopy for bio-medical science |
| title_short | Microscope-Cockpit: Python-based bespoke microscopy for bio-medical science |
| title_sort | microscope cockpit python based bespoke microscopy for bio medical science |
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