Pollatou, A., Ferrante, D. D. (August 2020) Out-of-focus brain image detection in serial tissue sections. J Neurosci Methods, 345. p. 108852. ISSN 0165-0270
Abstract
BACKGROUND: A large part of image processing workflow in brain imaging is quality control which is typically done visually. One of the most time consuming steps of the quality control process is classifying an image as in-focus or out-of-focus (OOF). NEW METHOD: In this paper we introduce an automated way of identifying OOF brain images from serial tissue sections in large datasets (>1.5 PB). The method utilizes steerable filters (STF) to derive a focus value (FV) for each image. The FV combined with an outlier detection that applies a dynamic threshold allows for the focus classification of the images. RESULTS: The method was tested by comparing the results of our algorithm with a visual inspection of the same images. The results support that the method works extremely well by successfully identifying OOF images within serial tissue sections with a minimal number of false positives. COMPARISON WITH EXISTING METHODS: Our algorithm was also compared to other methods and metrics and successfully tested in different stacks of images consisting solely of simulated OOF images in order to demonstrate the applicability of the method to other large datasets. CONCLUSIONS: We have presented a practical method to distinguish OOF images from large datasets that include serial tissue sections that can be included in an automated pre-processing image analysis pipeline.
| Item Type: | Paper |
|---|---|
| Subjects: | bioinformatics bioinformatics > computational biology > algorithms organs, tissues, organelles, cell types and functions > organs types and functions > brain bioinformatics > computational biology organs, tissues, organelles, cell types and functions > organs types and functions organs, tissues, organelles, cell types and functions |
| CSHL Authors: | |
| Communities: | CSHL labs > Mitra lab |
| Depositing User: | Matthew Dunn |
| Date: | 6 August 2020 |
| Date Deposited: | 14 Dec 2020 17:50 |
| Last Modified: | 01 Feb 2024 16:53 |
| PMCID: | PMC9475563 |
| Related URLs: | |
| URI: | https://repository.cshl.edu/id/eprint/39649 |
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