ArticleBrain pathology (Zurich, Switzerland)2026
Comparison of automated and manual approaches for microglial quantification and classification: A focus on the HALO digital pathology platform.
Article in Brain pathology (Zurich, Switzerland), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
1 citing paper in PubMed.
- Comparison of automated and manual approaches for microglial quantification and classification: A focus on the HALO digital pathology platform.Brain pathology (Zurich, Switzerland) · 2026Article
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7 authors.
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Abstract
Phenotypic changes in microglia have been linked to multiple neurological conditions, such as dementia, Parkinson's disease, stroke and traumatic brain injury. Consistent identification and classification of microglia is essential in understanding potential links with neurological diseases. Currently, there are several ways by which the microglial population and morphology are assessed, including manually or using open-source image analysis platforms, such as ImageJ. A microglial classification module for the HALO digital pathology platform has been developed for this purpose but has not yet been validated within the literature. The current study therefore conducted a comparison of the performance of this HALO module to manual microglial analysis and to automated analysis via ImageJ using both human and rat brain tissue. In 5 μm thick human tissue, total and activated microglia/mm
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