Information content analysis in automated microscopy imaging using modified autofocusing approach
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| Year of publication | 2010 |
| Type | Conference abstract |
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| 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). The standard process of image focusing assumes unimodal behaviour of the focus function. In real world, however, this assumption is often not fulfilled and the objects normally do not lie in one plane. There may be interesting planes of focus present in the focus function plot, which are suppressed by other, more distinctive, planes that prevent the autofocus algorithm from detecting them. Therefore, our goal was to find all the interesting z-planes with rich in-focus information content (even those that are hard to detect by the human eye) for a given lateral region. A new technique is employed based on dividing the field of view into several sub-fields and applying the focus function to each of them independently. The separated results are then merged in order to gain a global view of the 3D regions of interest. We actually reduce the problem of finding more z-planes in one image to the problem of finding one z-plane in multiple images. In such a way, one can make use of automated focusing to obtain more accurate and reliable results as compared to those of manual focusing or standard unimodal autofocusing. |
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