Results 81 to 90 of about 6,229 (197)
Journal of Biophotonics, Volume 19, Issue 3, March 2026.HyperProbe1.1 enables rapid, label‐free biochemical mapping of freshly resected meningiomas. By quantifying endogenous biomarkers such as cytochrome c oxidase, hemoglobin derivatives, and lipids, the system reveals molecular signatures consistent with tumor grading and generates spatial maps that visualize metabolic and vascular heterogeneity across ...
Pietro Ricci +13 more
wiley +1 more source
Limnology and Oceanography Letters, Volume 11, Issue 2, March 2026.Abstract This study presents a high‐resolution reconstruction of the Antarctic Intermediate Water (AAIW) transport variability on the southeastern Brazilian continental margin over the last 16,000 years BP, based on grain‐size analysis. Variations of sortable silt (SS¯$$ \overline{SS} $$) are interpreted as changes in flow speed of the Intermediate ...
Júlia Sambugaro +2 more
wiley +1 more source
SSF-Net: A Spatial–Spectral Features Integrated Autoencoder Network for Hyperspectral Unmixing
IEEE Journal of Selected Topics in Applied Earth Observations and Remote SensingIn recent years, deep learning has received tremendous attention in the field of hyperspectral unmixing (HU) due to its powerful learning capabilities.
Bin Wang +4 more
doaj +1 more source
Kernel-Based Nonlinear Spectral Unmixing with Dictionary Pruning
Remote Sensing, 2019 Spectral unmixing extracts subpixel information by decomposing observed pixel spectra into a collection of constituent spectra signatures and their associated fractions.
Zeng Li, Jie Chen, Susanto Rahardja
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Noise Effect on Linear Spectral Unmixing
Annals of GIS, 1999 Abstract Using hyperspectral reflectance data collected from six types of surface covers, we synthesized linear mixtures and used them to test the sensitivity of two linear unmixing algorithms to simulated additive noise. We found both algorithms were highly sensitive to noise. This may considerably limit their use in remote sensing.
P. Gong, A. Zhang
openaire +1 more source
Magnetic Resonance in Medicine, Volume 95, Issue 3, Page 1304-1322, March 2026.Abstract Purpose The aim was to improve the sensitivity and robustness against B0 inhomogeneities of deuterium metabolic imaging (DMI) using phase‐cycled balanced SSFP (bSSFP) methods at 9.4 T. Methods We investigated two variants of phase‐cycled bSSFP acquisitions, namely uniformly weighted multi‐echo and acquisition‐weighted chemical shift imaging ...
Praveen Iyyappan Valsala +8 more
wiley +1 more source
DMAE-HU: A novel deep multitasking autoencoder for hybrid hyperspectral unmixing in remote sensing
ICT ExpressHyperspectral unmixing (HU) is crucial for extracting material information from hyperspectral images (HSI) obtained through remote sensing. Although linear unmixing methods are widely used due to their simplicity, they only address linear mixing effects.
Suresh Aala +8 more
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Metabolic FRET sensors in intact organs: Applying spectral unmixing to acquire reliable signals. [PDF]
Biol Open, 2023 Gándara L, Durrieu L, Wappner P.
europepmc +1 more source
Single‐Particle Characterization Reveals Heterogeneous Extracellular Vesicle Fusion with Liposomes
Small Methods, Volume 10, Issue 5, 9 March 2026.This study used five orthogonal single‐particle techniques to compare how common mechanical methods fuse extracellular vesicles with liposomes. By quantifying fused‐particle yield, purity, and vesicle integrity, we found that freeze‐thaw and sonication generated the highest fusion but that all methods introduced membrane perturbation or damage.
Rachel R. Mizenko +6 more
wiley +1 more source
AutoUnmix: an autoencoder-based spectral unmixing method for multi-color fluorescence microscopy imaging. [PDF]
Biomed Opt Express, 2023 Jiang Y, Sha H, Liu S, Qin P, Zhang Y.
europepmc +1 more source