AIMC Topic: Optical Imaging

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Cortical layer multi-parameter analysis of neurovascular impairments in AD/ADRD rodent model with in vivo optical imaging.

Translational neurodegeneration
BACKGROUND: Neurovascular biomarkers have the potential to enhance early diagnosis of Alzheimer's disease (AD) and AD-related dementias (ADRD), as cerebrovascular alterations often precede neurodegeneration. However, their clinical application remain...

Machine Learning Accelerates Discovery of High-Performance Corrole Photosensitizers for Optical Imaging Diagnosis and Photodynamic Therapeutics of Nasopharyngeal Carcinoma.

The journal of physical chemistry letters
This study centers on corrole, an emerging photosensitizer with great application potential, and innovatively develops an intelligent machine learning-based screening strategy. Through integrating molecular descriptor generation, feature engineering,...

RSR-MSI: Reference-Based Super-Resolution for Mass Spectrometry Imaging of Tissues and Single Cells.

Analytical chemistry
High-spatial-resolution mass spectrometry imaging (MSI) visualizes molecular distributions in tissues and cells. However, achieving higher spatial resolution typically necessitates smaller pixel dimensions and an increased number of pixels, leading t...

Smartphone-based biosensing: a review of optical imaging, microfluidic integration, and AI-enhanced analysis.

Mikrochimica acta
Recently, the integration of smartphone-based platforms into biomedical sensing has provided portable, low-cost, and scalable alternatives to conventional laboratory diagnostics. According to the advances in mobile imaging, embedded sensors, microflu...

Real-time self-supervised denoising for high-speed fluorescence neural imaging.

Nature communications
Self-supervised denoising methods significantly enhance the signal-to-noise ratio in fluorescence neural imaging, yet real-time solutions remain scarce in high-speed applications. Here, we present the FrAme-multiplexed SpatioTemporal learning strateg...

Clinical validation of a deep learning based application for quantitative assessment of dental plaque in fluorescence imaging.

Clinical oral investigations
AIM: Evaluating dental plaque is a fundamental task for periodontal health care, but it is subjective, time-consuming, and cumbersome. Therefore, this study aimed to develop and validate a web-based deep learning application capable of objectively qu...

Recent advances in organic molecule fluorescent probes for microbial imaging.

Journal of materials chemistry. B
Microorganisms play a crucial role in human life and production. However, certain pathogenic microorganisms, such as bacteria, viruses, and fungi, can cause diseases like pneumonia, meningitis, and influenza, potentially leading to global public heal...

Analysis of the carotenoid cycle during microbial growth by combining fluorescence imaging and deep learning.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
Detection and real-time tracking of changes in the relative carotenoid content during microbial growth can be extremely challenging. Additionally, analyzing its content cycling time can also be highly difficult. In this study, Raman tweezers were emp...

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

Analytical chemistry
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...

Optical Resolution of the Morphological Change of Single Nanoparticles at Native Conditions: A Nonsuper-Resolution Approach.

ACS sensors
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...