Synchronization-based clustering algorithm for reconstruction of multiple reconstructed targets in fluorescence...

Area of Science:

• Biomedical Imaging
• Optical Imaging
• Preclinical Research

Background:

• Fluorescence molecular tomography (FMT) is crucial for in vivo molecular imaging in preclinical studies.
• Reconstructing multiple fluorescent targets in FMT is challenging due to the ill-posed nature of the inverse problem.
• Existing methods often struggle with accuracy when dealing with multiple targets.

Purpose of the Study:

• To introduce and develop novel postprocessing algorithms for improved multiple target reconstruction in FMT.
• To enhance the accuracy of locating multiple fluorescent targets using fluorescence molecular tomography.
• To enable automatic identification of the number of targets without human intervention or prior knowledge.

Main Methods:

• Introduction of the original synchronization-inspired clustering (OSC) algorithm into FMT.
• Development of a synchronization-based clustering algorithm for FMT (SC-FMT) building upon OSC.
• Utilization of minimum spanning tree within both algorithms for automatic target number identification.

Main Results:

• Both OSC and SC-FMT algorithms demonstrate robust and automatic resolution of multiple fluorescent targets.
• Numerical simulations confirm the effectiveness of the proposed postprocessing algorithms in FMT reconstruction.
• SC-FMT shows potential for further improvement in location accuracy for multiple targets.

Conclusions:

• The developed SC-FMT and OSC algorithms offer robust solutions for reconstructing multiple targets in FMT.
• These methods automate target number identification, reducing the need for human intervention.
• The findings highlight the potential of these postprocessing techniques to advance FMT applications in preclinical research.