Related Experiment Video
Updated: Sep 9, 2025

Open Source High Content Analysis Utilizing Automated Fluorescence Lifetime Imaging Microscopy
Published on: January 18, 2017
An enhanced mountain climbing search algorithm to enable fast and accurate autofocusing in high resolution
Yuetong Jia1, Edward N Ward1, Francesca Wilhelmina van Tartwijk1,2
1Department of Chemical Engineering and Biotechnology, University of Cambridge, Cambridge, CB3 0AS, United Kingdom.
None:
Accurate and efficient autofocusing is essential for the automation of fluorescence microscopy, but background noise and shallow depth of field at high magnifications make autofocusing particularly challenging. Here, we present a fast and accurate autofocus algorithm to address these challenges. It is highly effective for high-magnification imaging, while performing equally well for low-magnification imaging tasks. The method is based on the mountain climbing search algorithm and yields improvements on autofocusing precision of up to 200-fold over current methods, whilst offering competitive speed and greatly extended search ranges. Our approach is broadly applicable: it demonstrated good stability and reproducibility across magnifications ranging from 20X to 100X, excels in both live cell imaging and high-resolution fixed sample imaging, and it is compatible with various microscopy techniques without the need for fiducial markers or hardware modifications on existing microscopes. To maximise its accessibility, we constructed a user-friendly interface compatible with the widely used Micromanager software. It generalises well across various imaging modalities and hardware platforms, making it particularly suitable for use in high-resolution screening of candidate drugs.
More Related Videos
Related Concept Videos
Super-resolution Fluorescence Microscopy
Confocal Fluorescence Microscopy

