Reduction of photobleaching effects in photoacoustic imaging using noise agnostic, platform-flexible deep-learning methods.

Journal: Journal of biomedical optics

Published Date: May 28, 2025

Abstract

SIGNIFICANCE: Molecular photoacoustic (PA) imaging with exogenous dyes faces a significant challenge due to the photobleaching of the dye that can compromise tissue visualization, particularly in 3D imaging. Addressing this limitation can revolutionize the field by enabling safer, more reliable imaging and improve real-time visualization, quantitative analysis, and clinical decision-making in various molecular PA imaging applications such as image-guided surgeries.

Authors

Avijit Paul

Biomedical Engineering, Tufts University, Medford, MA, USA avijit.paul@tufts.edu.
Christopher Nguyen

Cardiovascular Research Center, Massachusetts General Hospital, Charlestown, MA 02129, USA Caroline.Burns@childrens.harvard.edu Geoff.Burns@childrens.harvard.edu Christopher.nguyen@mgh.harvard.edu.
Tayyaba Hasan

Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, United States.
Srivalleesha Mallidi

Tufts University, Department of Biomedical Engineering, Medford, Massachusetts, United States.

Keywords

Animals Deep Learning Humans Image Processing, Computer-Assisted Imaging, Three-Dimensional Mice Photoacoustic Techniques Photobleaching Signal-To-Noise Ratio

External Resources

View on PubMed Access via DOI PubMed (40443946)

Reduction of photobleaching effects in photoacoustic imaging using noise agnostic, platform-flexible deep-learning methods.

Abstract

Authors

Keywords

External Resources

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