Brightness demixing for simultaneous multi-target imaging in 3D single-molecule localization microscopy Le, L., S. K. Sreenivas, E. Fort, and S. Lévêque-Fort Nature Methods (2026)
Résumé: Single-molecule localization microscopy has enabled high-resolution imaging, but the simultaneous detection of multiple fluorophores traditionally relies on spectral-based separation, which is inherently constrained by spectral overlap. Here we introduce brightness demixing, a method for fluorophore discrimination that exploits brightness, which directly depends on the fluorophore extinction coefficient and quantum yield. By oversampling blinking events, we precisely quantify photon flux as a proxy for brightness, enabling robust differentiation of fluorophores independent of their spectral properties, without requiring additional spectral separation. Brightness demixing operates within a single detection channel, eliminating the need for additional spectral filters or cameras. We demonstrate this approach with simultaneous two- and three-target imaging in both two- and three-dimensional configurations. By maintaining single-wavelength excitation and minimizing chromatic aberrations, this method notably enhances multiplexing in single-molecule localization microscopy while remaining fully compatible with existing setups. Brightness Demixing thus offers a simple yet powerful approach for expanding multi-target imaging capabilities in super-resolution microscopy.
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Lightweight Food Localization and Recognition via Multi-Branch Feature Learning and Enhanced Aggregation Zhu, X., Y. Yang, P. Cao, G. Sheng, and B. Denby IEEE Journal of Biomedical and Health Informatics, 1-14 (2026)
Résumé: Food image localization and recognition on edge devices is a core task in food computing, enabling convenient dietary monitoring and efficient health management. However, food localization and recognition presents significant challenges due to inherent intra-class variability, inter-class similarity, and non-rigid characteristics. To address these challenges, we propose YOLO-Multi Feature Fusion, a novel multi-feature fusion model for food image localization and recognition. Building upon the YOLOv5 framework, YOLO-Multi Feature Fusion integrates several key components: the Ghost Bottleneck from the lightweight GhostNet, a newly designed Multi-Scale Feature Bottleneck, a Bidirectional Vision Transformer, and an Information Cross-Exchange module. These modules enable the model to comprehensively capture and fuse complex feature information from food images while simultaneously reducing both model parameters and computational load. Extensive evaluations on benchmark datasets (UEC Food100, UEC Food256, and ZSFooD) demonstrate that YOLO-Multi Feature Fusion outperforms existing lightweight detectors. Compared to YOLOv5, YOLO-Multi Feature Fusion achieves mAP improvements of 3.0%, 3.0%, and 0.3% on these datasets, respectively, with parameter reductions of 5.7M, 4.7M, and 4.9M, and computational load reductions of 44.6 GFLOPs, 42.0 GFLOPs, and 42.0 GFLOPs. The source code will be released upon the formal publication of the paper.
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Repeatability and reliability of retinal arterial hemodynamics measurement using Doppler holography Martinache, O. R., R. L. Draham, V. C. Snyder, J. Chhablani, J. A. Sahel, E. A. Rossi, and M. Atlan Journal of Biomedical Optics 31, no. 4, 046001 (2026)
Résumé: Significance: Reliable quantification of retinal arterial blood flow is important for diagnosing and monitoring ocular and systemic diseases. Existing techniques are limited by invasiveness, motion artifacts, or a lack of quantitative flow estimation. Aim: The aim is to assess the repeatability, reproducibility, and robustness of laser Doppler holography (LDH) for measuring retinal arterial hemodynamics. Approach: We acquired LDH data at 67 kHz in healthy volunteers (14 eyes intra-day and 4 eyes inter-day) and quantified blood volume rate, resistivity index (RI), and vessel diameter. Additional measurements evaluated sensitivity to axial displacement and gaze lateral positioning. Results: LDH successfully measured retinal arterial blood volume rate in all eyes, with a coefficient of variation (CoV) of 18.5% for the mean arterial blood volume rate and a CoV of 11% for RI. Inter-day reproducibility remained acceptable ( formula presented ). The mean arterial diameter estimation showed a CoV of formula presented . Moderate axial or lateral shifts introduced small changes in hemodynamic values ( formula presented CoV) compared with inter- or intra-day tests. Conclusions: LDH provides reliable and robust measurements of retinal arterial hemodynamics and maintains performance under typical imaging variations (axial or gaze position). These findings support its potential for longitudinal studies and future clinical translation.
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Metabolic imaging of Fragilariopsis cylindrus in polar night conditions using full-field optical transmission tomography (FFOTT) Joli, N., C. Boccara, B. Bailleul, C. Bowler, and M. Boccara Biomedical Optics Express 17, no. 3, 1540-1549 (2026)
Résumé: FFOTT is a non-invasive, non-destructive method of imaging that was found promising for a broad range of applications. We applied FFOTT to compare intracellular dynamic signals, a proxy for cellular metabolic activity. We investigated the metabolic changes associated with the transition from and towards polar night in the polar diatom Fragilariopsis cylindrus, grown under continuous illumination or kept in darkness for six weeks. Our results revealed a tenfold signal decrease in darkness and a rapid signal recovery upon re-illumination. Photosynthetic performance was assessed in parallel. Biovolume determinations allowed the computation of the metabolic rates of F. cylindrus grown under both light and dark conditions, which were compared to the optical signal variations.
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