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Updated: Apr 26, 2026

Low-energy Cathodoluminescence for OxyNitride Phosphors

Low-energy Cathodoluminescence for OxyNitride Phosphors

Published on: November 15, 2016

Probability method for Cerenkov luminescence tomography based on conformance error minimization.

Xintao Ding¹, Kun Wang², Biao Jie³

¹School of Territorial Resources and Tourism, Anhui Normal University, Wuhu, Anhui 241003, China ; School of Mathematics and Computer Science, Anhui Normal University, Wuhu, Anhui 241003, China.

Biomedical Optics Express

|July 30, 2014

Summary

This summary is machine-generated.

This study introduces a novel probability method for Cerenkov luminescence tomography (CLT) to improve 3D radioactive probe distribution reconstruction in vivo. The new method offers more robust and biologically relevant imaging results compared to existing techniques.

Keywords:

(100.3190) Inverse problems (110.6960) Tomography (170.3010) Image reconstruction techniques (170.3660) Light propagation in tissues (170.3880) Medical and biological imaging (170.6280) Spectroscopy, fluorescence and luminescence

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High-resolution Thermal Micro-imaging Using Europium Chelate Luminescent Coatings

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Area of Science:

Biomedical Imaging
Medical Physics
Radiochemistry

Background:

Cerenkov luminescence tomography (CLT) enables 3D reconstruction of radioactive probe distribution in vivo.
Existing CLT reconstruction methods are often non-robust due to the ill-posed nature of the inverse problem.
Current methods can lead to loss of biological significance due to large variations in reconstructed radiotracer uptake.

Purpose of the Study:

To develop a more robust and biologically meaningful reconstruction method for CLT.
To address the limitations of existing inverse problem solutions in CLT.
To improve the accuracy and reliability of 3D radioactive probe distribution imaging.

Main Methods:

A probability method based on minimizing conformance error was proposed, featuring qualitative and quantitative modules.
The method first identifies the organ containing the light source.
A 0-1 linear optimization with a region growing approach was employed to transform the inverse problem into a forward problem.

Main Results:

The proposed probability method successfully pinpointed the organ containing the light source.
A source sequence was generated, and the probability of each node being a light source was reconstructed.
Numerical and in vivo experiments demonstrated that the probability method is more robust and reasonable than the hp-finite element method (hp-FEM).

Conclusions:

The developed probability method significantly enhances the robustness and biological relevance of CLT reconstructions.
This approach offers a more reliable solution for accurately determining 3D distributions of radioactive probes.
The findings suggest a promising advancement in preclinical molecular imaging using CLT.