Image Division Technique in Automated Fluorescence Microscopy
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| Year of publication | 2010 |
| Type | Appeared in Conference without Proceedings |
| MU Faculty or unit | |
| Citation | |
| Description | This contribution shows how to modify classical autofocusing in optical microscopy to perform automated analysis of information content in image data generated by the instrument, even if dealing with thick specimen or working in confocal mode. The new approach is useful for finding 3D regions of interest prior to image acquisition, which enables the user to record precisely those places in space that contain useful image data. This results in shorter acquisition time and less memory consumption as compared to the acquisition of classical large rectangular volumes containing more background regions than object regions (especially for a sparse specimen and camera-based systems). |
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