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Updated: May 18, 2026

Computed Tomography-guided Time-domain Diffuse Fluorescence Tomography in Small Animals for Localization of Cancer Biomarkers

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Published on: July 17, 2012

TV-based image reconstruction of multiple objects in a fixed source-detector geometry.

Yang Lu¹, Zhenyu Yang, Jun Zhao

¹School of Biomedical Engineering, Shanghai Jiao Tong University, China.

Journal of X-Ray Science and Technology

|September 6, 2012

Summary

This summary is machine-generated.

This study introduces a new scanning method for tomographic reconstruction of multiple objects using X-ray projections. This approach significantly reduces scanning time, enhancing imaging throughput for complex object analysis.

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Area of Science:

Medical Imaging
Computational Imaging
Image Reconstruction

Background:

Tomographic reconstruction of multiple objects from overlapped X-ray projections presents challenges in data acquisition and reconstruction accuracy.
Existing methods may require extensive scanning times, limiting throughput in imaging facilities.

Purpose of the Study:

To develop an efficient tomographic reconstruction method for multiple objects with overlapped X-ray projections.
To reduce data acquisition time while maintaining or improving reconstruction quality.

Main Methods:

A novel rotation-translation scanning mode with a fixed source-detector geometry was proposed.
Objects were individually translated periodically during rotation for data acquisition.
A reconstruction scheme alternating between Simultaneous Algebraic Reconstruction Technique (SART) and Total Variation (TV) minimization was employed.

Main Results:

Numerical experiments demonstrated successful reconstruction of two and four objects.
The proposed method achieved significant reductions in scanning time: approximately 46% for two objects and 67% for four objects.
Improved imaging facility throughput was observed.

Conclusions:

The developed rotation-translation scanning mode and reconstruction scheme offer an effective solution for multi-object tomography.
This approach substantially decreases scanning time, making it a valuable advancement for imaging applications.
The method shows promise for enhancing the efficiency of tomographic imaging systems.