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Related Experiment Video

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A Microscope Setup and Methodology for Capturing Hyperspectral and RGB Histopathological Imaging Databases.

Gonzalo Rosa-Olmeda1, Manuel Villa1, Sara Hiller-Vallina2,3

  • 1Research Center on Software Technologies and Multimedia Systems, Universidad Politécnica de Madrid, 28031 Madrid, Spain.

Sensors (Basel, Switzerland)
|September 14, 2024
PubMed
Summary

This study introduces an automated system combining RGB and hyperspectral imaging for digitizing histopathological samples. This advanced approach significantly reduces sample capture and processing time compared to manual methods.

Keywords:
RGB imagingbiomedical imagingdigital histologydigital microscopydigital pathologyhyperspectral biomedicalhyperspectral imagingmicroscopywhole slide imaging

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Area of Science:

  • Digital Pathology
  • Medical Imaging
  • Histopathology

Background:

  • Hospital pathology departments are increasingly digitizing operations.
  • Current commercial solutions use RGB cameras, capturing limited spectral information.
  • There is a need for advanced imaging techniques to enhance histopathological sample analysis.

Purpose of the Study:

  • To present an automated system integrating RGB and hyperspectral technology for histopathological sample digitization.
  • To describe the hardware, software, and methodology of the developed system.
  • To evaluate the efficiency of the proposed system in terms of sample capture and processing time.

Main Methods:

  • Development of an automated system combining RGB and hyperspectral imaging.
  • Integration of microscope control software with autofocus and whole slide scanning.
  • Implementation of a hyperspectral scanning functionality.
  • Validation of a working methodology for correct sample capture.

Main Results:

  • The system successfully integrates RGB and hyperspectral imaging capabilities.
  • The automated software includes autofocus, stitching algorithms for whole slide scanning, and hyperspectral scanning.
  • Sample capture and processing time for 20 regions of interest is a maximum of 79 minutes.
  • The proposed method reduces processing time by at least three times compared to manual operators.

Conclusions:

  • The developed automated system offers enhanced information capture for histopathological samples.
  • The system demonstrates significant time efficiency, reducing manual operator time.
  • Both hardware and software components are adaptable to other systems utilizing hyperspectral technology.