AIMC Topic: Microscopy, Fluorescence
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Non-invasive screening of bladder cancer using digital microfluidics and FLIM technology combined with deep learning.
Journal of biophotonics
Jun 28, 2024
Non-invasive screening for bladder cancer is crucial for treatment and postoperative follow-up. This study combines digital microfluidics (DMF) technology with fluorescence lifetime imaging microscopy (FLIM) for urine analysis and introduces a novel ...
Deep learning-based localization algorithms on fluorescence human brain 3D reconstruction: a comparative study using stereology as a reference.
Scientific reports
Jun 25, 2024
3D reconstruction of human brain volumes at high resolution is now possible thanks to advancements in tissue clearing methods and fluorescence microscopy techniques. Analyzing the massive data produced with these approaches requires automatic methods...
A machine learning based method for tracking of simultaneously imaged neural activity and body posture of freely moving maggot.
Biochemical and biophysical research communications
Jun 24, 2024
To understand neural basis of animal behavior, it is necessary to monitor neural activity and behavior in freely moving animal before building relationship between them. Here we use light sheet fluorescence microscope (LSFM) combined with microfluidi...
AI analysis of super-resolution microscopy: Biological discovery in the absence of ground truth.
The Journal of cell biology
Jun 12, 2024
Super-resolution microscopy, or nanoscopy, enables the use of fluorescent-based molecular localization tools to study molecular structure at the nanoscale level in the intact cell, bridging the mesoscale gap to classical structural biology methodolog...
Deep learning-based spectroscopic single-molecule localization microscopy.
Journal of biomedical optics
May 24, 2024
SIGNIFICANCE: Spectroscopic single-molecule localization microscopy (sSMLM) takes advantage of nanoscopy and spectroscopy, enabling sub-10 nm resolution as well as simultaneous multicolor imaging of multi-labeled samples. Reconstruction of raw sSMLM ...
In Vivo Intelligent Fluorescence Endo-Microscopy by Varifocal Meta-Device and Deep Learning.
Advanced science (Weinheim, Baden-Wurttemberg, Germany)
Mar 15, 2024
Endo-microscopy is crucial for real-time 3D visualization of internal tissues and subcellular structures. Conventional methods rely on axial movement of optical components for precise focus adjustment, limiting miniaturization and complicating proced...
Fluorescent Neuronal Cells v2: multi-task, multi-format annotations for deep learning in microscopy.
Scientific data
Feb 10, 2024
Fluorescent Neuronal Cells v2 is a collection of fluorescence microscopy images and the corresponding ground-truth annotations, designed to foster innovative research in the domains of Life Sciences and Deep Learning. This dataset encompasses three i...
Applications of machine learning in time-domain fluorescence lifetime imaging: a review.
Methods and applications in fluorescence
Feb 8, 2024
Many medical imaging modalities have benefited from recent advances in Machine Learning (ML), specifically in deep learning, such as neural networks. Computers can be trained to investigate and enhance medical imaging methods without using valuable h...
Harnessing artificial intelligence to reduce phototoxicity in live imaging.
Journal of cell science
Feb 7, 2024
Fluorescence microscopy is essential for studying living cells, tissues and organisms. However, the fluorescent light that switches on fluorescent molecules also harms the samples, jeopardizing the validity of results - particularly in techniques suc...
Retrospective validation of MetaSystems' deep-learning-based digital microscopy platform with assistance compared to manual fluorescence microscopy for detection of mycobacteria.
Journal of clinical microbiology
Feb 1, 2024
UNLABELLED: This study aimed to validate Metasystems' automated acid-fast bacilli (AFB) smear microscopy scanning and deep-learning-based image analysis module (Neon Metafer) with assistance on respiratory and pleural samples, compared to conventiona...
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