ArticleJournal of microscopy2012
Automatic section thickness determination using an absolute gradient focus function.
Article in Journal of microscopy, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed, 8 citations in OpenAlex.
- Technical Note: Measuring the thickness of histological sections by detecting fluorescence intensity of embedding foam.Journal of pathology informatics · 2022Article
- Basic quantitative morphological methods applied to the central nervous system.The Journal of comparative neurology · 2021Review
- Practicable methods for histological section thickness measurement in quantitative stereological analyses.PloS one · 2018Article
- Unbiased estimation of cell number using the automatic optical fractionator.Journal of chemical neuroanatomy · 2017Article
- Early Expression of Parkinson's Disease-Related Mitochondrial Abnormalities in PINK1 Knockout Rats.Molecular neurobiology · 2016Article
Corrections and comments
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Authors and funding
7 authors at 1 institution in 1 country.
Funding
Abstract
Quantitative analysis of microstructures using computerized stereology systems is an essential tool in many disciplines of bioscience research. Section thickness determination in current nonautomated approaches requires manual location of upper and lower surfaces of tissue sections. In contrast to conventional autofocus functions that locate the optimally focused optical plane using the global maximum on a focus curve, this study identified by two sharp 'knees' on the focus curve as the transition from unfocused to focused optical planes. Analysis of 14 grey-scale focus functions showed, the thresholded absolute gradient function, was best for finding detectable bends that closely correspond to the bounding optical planes at the upper and lower tissue surfaces. Modifications to this function generated four novel functions that outperformed the original. The 'modified absolute gradient count' function outperformed all others with an average error of 0.56 μm on a test set of images similar to the training set; and, an average error of 0.39 μm on a test set comprised of images captured from a different case, that is, different staining methods on a different brain region from a different subject rat. We describe a novel algorithm that allows for automatic section thickness determination based on just out-of-focus planes, a prerequisite for fully automatic computerized stereology.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.