Microscopy
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Magnon momentum microscopy: A new window into nanoscale spin-wave physics
Magnon momentum microscopy: A new window into nanoscale spin-wave physics Sadie Harley Scientific Editor Robert Egan Associate Editor An international team led by the Max Born Institute has developed a new type of momentum microscopy to image magnons—the quanta of collectively excited spins—directly in two-dimensional reciprocal space using soft X-rays. Owing to its remarkable sensitivity, simplicity, and access to nanometer-scale wavelengths, this novel technique establishes a powerful and...
Compact Optical-Resolution Photoacoustic Microscopy System with Reflective Objective-Based Transducer Integration
Announce Type: new Abstract: We present an optical-resolution photoacoustic microscopy (OR-PAM) system designed to overcome key limitations in conventional transducer integration within a compact microscopy configuration, while preserving high optical performance and improving acoustic detection efficiency. The system uses a reflective objective that reduces spatial constraints within the optical pathway, enabling the integration of a large-area PVDF transducer within the optical obscuration...
{\lambda}Split: Self-Supervised Content-Aware Spectral Unmixing for Fluorescence Microscopy
arXiv:2603.23647v2 Announce Type: replace Abstract: In fluorescence microscopy, spectral unmixing aims to recover individual fluorophore concentrations from spectral images that capture mixed fluorophore emissions. Since classical methods operate pixel-wise and rely on least-squares fitting, their performance degrades with increasingly overlapping emission spectra and higher levels of noise, suggesting that a data-driven approach that can learn and utilize a structural prior might lead to...
iSBEM: An Open-Source Workflow for Automated ROI Targeting in Volume Electron Microscopy
Serial Block Face - Scanning Electron Microscopy (SBF-SEM) is a volume EM method suited to investigate the 3D architecture of tissues and even entire organisms at high resolution. However, imaging large volumes in their entirety is time-consuming and not always necessary. Many research projects have a focused interest in well-defined sub-regions of the samples.
CiliAI: Automated segmentation and compartment specific fluorescence quantification of primary cilia in confocal microscopy images
Primary cilia regulate essential signalling pathways controlling cell proliferation, differentiation, and tissue homeostasis. Quantitative analysis of ciliary morphology and compartment-specific protein localization by confocal microscopy is labor-intensive, user-dependent, and difficult to scale, particularly for multiplexed 3D image datasets. Here, we present CiliAI, a web-based deep-learning workflow for automated detection, substructure segmentation, and quantitative analysis of primary...
Topology-aware reconstruction of cellular state landscapes from microscopy using self-supervised learning
Morphology and spatial organisation provide complementary readouts of cellular state. However, reconstructing continuous cellular state landscapes from imaging data remains challenging, particularly in dense biological cultures. Here we present SI-SimCLR, a spatially informed self-supervised learning framework that learns biologically informative representations directly from fluorescence microscopy images without requiring segmentation or manual annotation.
Instant Prior-Free Resolution Enhancement for Cross-Modality Microscopy
The resolving power of optical microscopy is fundamentally constrained by the diffraction of light, limiting our ability to visualize subcellular structures. Computational methods, particularly deconvolution, can restore blurred images but critically depend on an accurate point spread function (PSF), whose estimation is often impractical and error-prone, leading to artifacts. Here, we introduce Nonlinear Fourier Re-weighting (NFR), a rapid algorithm that operates without any prior knowledge...
Self-Tuning Regularization for Image Scanning Microscopy
Announce Type: cross Abstract: Image Scanning Microscopy (ISM) is a fluorescence imaging technique that combines detector-array acquisition and computational reconstruction to achieve the theoretical resolution of an ideal confocal microscope, i.e., one operating with an infinitesimally small pinhole, while maintaining high signal-to-noise ratio. Among the reconstruction methods for obtaining the super-resolved image, multi-image deconvolution (MID) and its extension aimed at preserving the...
SPM-Bench: Benchmarking Large Language Models for Scanning Probe Microscopy
arXiv:2602.22971v2 Announce Type: replace Abstract: As LLMs achieved breakthroughs in general reasoning, their proficiency in specialized scientific domains reveals pronounced gaps in existing benchmarks due to data contamination, insufficient complexity, and prohibitive human labor costs. Here we present SPM-Bench, an original, PhD-level multimodal benchmark specifically designed for scanning probe microscopy (SPM). We propose a fully automated data synthesis pipeline that ensures both high...
Axial encoding unlocks up to eightfold faster 3D microscopy with less light
A research team from HKU Engineering has pioneered a fundamentally new imaging strategy known as AIMED (Arbitrary illumination microscopy with encoded depth), which utilizes a sub-sampling approach. By integrating innovations in axial optical encoding with advanced computational image reconstruction, the AIMED technology enables a substantial increase in 3D imaging speed while enhancing photon safety, all with minimal additional system complexity. This breakthrough demonstrates significant...