An autofocus algorithm for microscopic hyperspectral imaging system with adaptive wavelength variation

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Scopus citations

Abstract

Microscopic hyperspectral imaging techniques have been widely used to analyze information from digital pathology sections. Real-time autofocusing is one of the important techniques to acquire high-quality images efficiently; however, there are few autofocusing algorithms are proposed in this field. Therefore, this article proposes an autofocus algorithm for a self-developed microscopic hyperspectral imaging system. This method can finish autofocus with a single field of view in 0.9 seconds. In addition, to reduce the focusing time, we fit a wavelength as a function of focal length. We applied the above method on our own dataset and the experimental results show that this method can acquire large-scale microscopic hyperspectral images quickly and accurately.

Original languageEnglish
Title of host publicationICBBT 2022 - Proceedings of 2022 14th International Conference on Bioinformatics and Biomedical Technology
PublisherAssociation for Computing Machinery
Pages15-19
Number of pages5
ISBN (Electronic)9781450396387
DOIs
StatePublished - 27 May 2022
Event14th International Conference on Bioinformatics and Biomedical Technology, ICBBT 2022 - Xi'an, China
Duration: 27 May 202229 May 2022

Publication series

NameACM International Conference Proceeding Series

Conference

Conference14th International Conference on Bioinformatics and Biomedical Technology, ICBBT 2022
Country/TerritoryChina
CityXi'an
Period27/05/2229/05/22

Keywords

  • Autofocus
  • Large scale imaging
  • Microscopic hyperspectral imaging
  • Pathology
  • Self-adaptive focusing

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