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

Michael A PhillipsDavid Miguel Susano PintoNicholas HallJulio Mateos-LangerakRichard M PartonJosh TitlowDanail V StoychevThomas ParksTiago Susano PintoJohn W SedatMartin J BoothIlan DavisIan M Dobbie
Published in: Wellcome open research (2021)
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.
Keyphrases
  • machine learning
  • high throughput
  • high resolution
  • deep learning
  • healthcare
  • decision making
  • public health
  • artificial intelligence
  • optical coherence tomography
  • current status
  • high speed