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Related Experiment Video

Updated: May 31, 2025

Fluorescence Lifetime Macro Imager for Biomedical Applications
06:01

Fluorescence Lifetime Macro Imager for Biomedical Applications

Published on: April 7, 2023

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Fluorescence Lifetime Endoscopy with a Nanosecond Time-Gated CAPS Camera with IRF-Free Deep Learning Method.

Pooria Iranian1, Thomas Lapauw1, Thomas Van den Dries1

  • 1Department of Electronics and Informatics (ETRO), Vrije Universiteit Brussel, 1050 Brussels, Belgium.

Sensors (Basel, Switzerland)
|January 25, 2025
PubMed
Summary
This summary is machine-generated.

This study introduces the tauCAM, a new device for real-time near-infrared fluorescence lifetime imaging. This technology enhances cell differentiation in endoscopy, offering improved precision with fewer data points.

Keywords:
CAPSconvolutional neural networksendoscopyfluorescence imagingfluorescence lifetime imaginggated camera

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Area of Science:

  • Biomedical Optics
  • Medical Imaging
  • Endoscopy

Background:

  • Fluorescence imaging is crucial in preclinical and clinical settings.
  • Advancements in imaging technology and fluorescent labels are driving the adoption of fluorescence lifetime imaging.
  • Distinguishing between malignant and benign cells is vital in medical diagnostics.

Purpose of the Study:

  • To develop and demonstrate an endoscopic fluorescence lifetime imaging system for improved cell differentiation.
  • To achieve real-time fluorescence lifetime imaging in the near-infrared (NIR) region (700-900 nm).
  • To evaluate a novel deep learning-based method for fluorescence lifetime imaging with minimal time points.

Main Methods:

  • Development of the tauCAM system utilizing the Current-Assisted Photonic Sampler.
  • Demonstration using a rigid endoscope with various phantoms.
  • Application of an IRF-free deep learning algorithm requiring only 6 time points.

Main Results:

  • The endoscopic lifetime imaging system successfully demonstrated its capabilities.
  • The deep learning-based method achieved fluorescence lifetime imaging with high precision and uniformity.
  • The system using 6 time points outperformed conventional methods in lifetime uniformity and precision.

Conclusions:

  • Endoscopic fluorescence lifetime imaging holds significant potential for enhanced medical diagnostics.
  • The developed tauCAM system and deep learning approach offer a precise and efficient method for real-time NIR fluorescence lifetime imaging.
  • This technology can improve the differentiation of malignant and benign cells, paving the way for advanced endoscopic procedures.