ArticleLab on a chip2025
OpenLM: an open-source pixel super-resolution platform for lens-free microscopy with applications in bacterial growth monitoring and deep learning-based bacterial detection.
Article in Lab on a chip, 2025. 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.
- Overcoming resolution constraints in automated colony counting via a high-performance deep learning framework using SAHI.Scientific reports · 2026Article
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Authors and funding
8 authors.
Funding
Abstract
Monitoring bacterial growth and detecting early-stage colony formation are essential tasks in biomedical research, clinical diagnostics, and food and water safety. However, conventional imaging systems for bacterial monitoring often require bulky optics, skilled operation, and high costs, making them unsuitable for scalable or field-deployable applications. Lens-free microscopy (LM) provides a promising alternative by enabling compact, low-cost imaging systems using only a light source and an image sensor, replacing the need for bulky objective lenses with computational algorithm. Still, a key limitation of LM is its resolution, which is fundamentally constrained by the sensor's pixel size. Pixel super-resolution techniques-especially when combined with multi-angle illumination using LED arrays-can significantly enhance resolution while maintaining a large field of view (FOV). We present OpenLM, an open-source lens-free microscopy platform integrated with a pixel super-resolution algorithm. The system is built from four affordable, off-the-shelf components: a Raspberry Pi camera, an optical filter, an LED array, and a Raspberry Pi board. Its 3D-printed housing enables easy replication and customization. User-friendly graphical interfaces for both Raspberry Pi OS and Windows provide camera control, real-time preview, image acquisition, and reconstruction-without requiring prior experience in lens-free imaging. To demonstrate its utility, we applied OpenLM to two bacterial imaging tasks: (1) long-term, time-lapse imaging of
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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.