ArticleBiomedical optics express2022
Content aware multi-focus image fusion for high-magnification blood film microscopy.
Article in Biomedical optics express, 2022. 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.
- Cross-Domain Benchmarking of Focus Measures for Smear-Microscopy Autofocus Under a Consensus-Audited Reference.Journal of imaging · 2026Article
- Next-generation morphology, a novel multilayer morphometric digital analysis, reveals both the basic topology and new trends of myelodysplasia of peripheral blood specimens.British journal of haematology · 2025Article
- A large multi-focus dataset for white blood cell classification.Scientific data · 2024Article
- Noise insensitive volumetric fusion method for enhanced photoacoustic microscopy.Journal of biomedical optics · 2023Article
- Content aware multi-focus image fusion for high-magnification blood film microscopy.Biomedical optics express · 2022Article
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Authors and funding
8 authors.
Funding
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Abstract
Automated digital high-magnification optical microscopy is key to accelerating biology research and improving pathology clinical pathways. High magnification objectives with large numerical apertures are usually preferred to resolve the fine structural details of biological samples, but they have a very limited depth-of-field. Depending on the thickness of the sample, analysis of specimens typically requires the acquisition of multiple images at different focal planes for each field-of-view, followed by the fusion of these planes into an extended depth-of-field image. This translates into low scanning speeds, increased storage space, and processing time not suitable for high-throughput clinical use. We introduce a novel content-aware multi-focus image fusion approach based on deep learning which extends the depth-of-field of high magnification objectives effectively. We demonstrate the method with three examples, showing that highly accurate, detailed, extended depth of field images can be obtained at a lower axial sampling rate, using 2-fold fewer focal planes than normally required.
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Registered trials
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