AIMC Topic: Optical Imaging

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Rapid Fluorescence Lifetime Imaging through One-Dimensional Deep Learning Optimization.

Analytical chemistry Jul 10, 2025
Traditional fluorescence lifetime imaging (FLIM) provides valuable quantitative insights for biomedical and molecular biology research, but often relies on computationally intensive datafitting methods to extract meaningful metrics. To address this l...
Humans Brain Mice Alzheimer Disease Optical Imaging Animals Deep Learning
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Optical Resolution of the Morphological Change of Single Nanoparticles at Native Conditions: A Nonsuper-Resolution Approach.

ACS sensors Jul 8, 2025
Label-free optical imaging of the morphology of single nanoparticles under native conditions remains a challenging task despite its importance in the synthesis, properties, and applications of nanomaterials. Here, we developed an angular scanning dar...
Optical Imaging Metal Nanoparticles Microscopy Nanoparticles Machine Learning Particle Size
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Multimodal Optical Imaging Combined with Radiomic Analysis for Fibrotic Cardiac Tissue Investigation.

Analytical chemistry Jul 5, 2025
Understanding the process of fibrotic scarring of the myocardium is critical for the diagnosis and risk stratification of life-threatening cardiac dysfunction. Complex changes in structure, composition, and conductivity occurring at different stages ...
Radiomics Animals Rats Optical Imaging Microscopy, Fluorescence, Multiphoton Tomography, Optical Coherence Myocardium Fibrosis Spectrum Analysis, Raman Multimodal Imaging
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Dynamic mode decomposition for analysis and prediction of metabolic oscillations from time-lapse imaging of cellular autofluorescence.

Scientific reports Jul 2, 2025
Oscillations are a common phenomenon in cell biology. They are based on non-linear coupling of biochemical reactions and can show rich dynamic behavior as found in, for example, glycolysis of yeast cells. Here, we show that dynamic mode decomposition...
Glucose Saccharomyces cerevisiae Optical Imaging Algorithms Glycolysis NAD Time-Lapse Imaging Humans Machine Learning
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Chemical imaging for biological systems: techniques, AI-driven processing, and applications.

Journal of materials chemistry. B Jun 18, 2025
Visualizing the chemical compositions of biological samples is pivotal to advancing biological sciences, with the past two decades witnessing the emergence of innovative chemical imaging platforms such as single-molecule imaging, coherent Raman scatt...
Machine Learning Animals Optical Imaging Humans Artificial Intelligence
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Deep-learning-enabled spatial frequency domain imaging of the spatiotemporal dynamics of skin physiology.

Journal of biomedical optics Apr 20, 2025
SIGNIFICANCE: Spatial frequency domain imaging (SFDI) is an emerging optical imaging modality for visualizing tissue absorption and scattering properties. This approach is promising for noninvasive wide field-of-view (FOV) monitoring of biophysiologi...
Optical Imaging Humans Hemoglobins Image Processing, Computer-Assisted Neural Networks, Computer Melanins Deep Learning Skin Physiological Phenomena Skin
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Biophysical modeling and artificial intelligence for quantitative assessment of anastomotic blood supply in laparoscopic low anterior rectal resection.

Surgical endoscopy Apr 14, 2025
PURPOSE: Fluorescence imaging is critical for intraoperative intestinal perfusion assessment in colorectal surgery, yet its clinical adoption remains limited by subjective interpretation and lack of quantitative standards. This study introduces an in...
Optical Imaging Rectum Rectal Neoplasms Humans Anastomosis, Surgical Female Middle Aged Laparoscopy Aged Artificial Intelligence Male Machine Learning
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Automated spectral decomposition and reconstruction of optical properties using a mixed autoencoder approach.

Journal of biomedical optics Apr 9, 2025
SIGNIFICANCE: Investigating optical properties (OPs) is crucial in the field of biophotonics, as it has a broad impact on understanding light-tissue interactions. However, current techniques, such as inverse Monte Carlo simulations (IMCS), have limit...
Neural Networks, Computer Image Processing, Computer-Assisted Phospholipids Algorithms Monte Carlo Method Autoencoder Scattering, Radiation Optical Imaging
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Machine Learning-Assisted Multiplexed Fluorescence-Labeled miRNAs Imaging Decoding for Combined Mycotoxins Toxicity Assessment.

Analytical chemistry Apr 3, 2025
Mycotoxins, particularly deoxynivalenol (DON) and zearalenone (ZEN), are common food contaminants that frequently co-occur in grains, posing significant health risks. This study proposed a multiplexed detection platform for simultaneous quantificatio...
Machine Learning Optical Imaging MicroRNAs Mycotoxins Fluorescent Dyes Trichothecenes Zearalenone Limit of Detection Humans
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Deep learning-assisted cellular imaging for evaluating acrylamide toxicity through phenotypic changes.

Food and chemical toxicology : an international journal published for the British Industrial Biological Research Association Mar 19, 2025
Acrylamide (AA), a food hazard generated during thermal processing, poses significant safety risks due to its toxicity. Conventional methods for AA toxicology are time-consuming and inadequate for analyzing cellular morphology. This study developed a...
Deep Learning Humans Acrylamide Phenotype Optical Imaging
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