Two-step reconstruction framework of fluorescence molecular tomography based on energy statistical probability

Area of Science:

• Biomedical Imaging
• Medical Physics
• Optical Imaging

Background:

• Fluorescence Molecular Tomography (FMT) offers non-invasive 3D visualization of fluorescent probes for early tumor detection.
• FMT reconstruction is an ill-posed problem, hindering its widespread clinical adoption.
• Accurate and efficient reconstruction is crucial for advancing FMT applications.

Purpose of the Study:

• To develop and evaluate a novel two-step reconstruction framework for Fluorescence Molecular Tomography (FMT).
• To improve the accuracy and speed of FMT source reconstruction.
• To address the ill-posed nature of FMT reconstruction using integrated tissue information.

Main Methods:

• A two-step reconstruction framework based on energy statistical probability was proposed.
• Computed tomography (CT) structural information was used to associate tissue optical parameters for initial global reconstruction.
• Region of interest delineation based on probability calculation for accurate and fast source reconstruction.

Main Results:

• The proposed framework demonstrated significant effectiveness in numerical simulations.
• In vivo experiments confirmed the framework's capability for accurate and fast FMT source reconstruction.
• The method successfully addressed the challenges associated with FMT reconstruction.

Conclusions:

• The novel two-step reconstruction framework shows significant potential for practical FMT applications.
• This approach enhances the accuracy and speed of 3D fluorescent probe distribution visualization.
• The method offers a promising solution for overcoming limitations in early tumor detection using FMT.