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Tomography refers to imaging by sections. Computed tomography (CT) is a non-invasive imaging technique that uses computers to analyze several cross-sectional X-rays to reveal minute details about structures in the body.
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German physicist Wilhelm Röntgen (1845–1923) was experimenting with electrical current when he discovered that a mysterious and invisible "ray" would pass through his flesh but leave an outline of his bones on a screen coated with a metal compound. In 1895, Röntgen made the first durable record of the internal parts of a living human: an "X-ray" image (as it came to be called) of his wife’s hand. Scientists worldwide quickly began their own experiments with...
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Related Experiment Video

Updated: Oct 28, 2025

3D Imaging of Soft-Tissue Samples using an X-ray Specific Staining Method and Nanoscopic Computed Tomography
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Three-term conjugate gradient method for X-ray luminescence computed tomography.

Yuqing Hou, Zijian Tang, Huangjian Yi

    Journal of the Optical Society of America. A, Optics, Image Science, and Vision
    |July 15, 2021
    PubMed
    Summary
    This summary is machine-generated.

    A new three-term conjugate gradient (TTCG) algorithm accelerates X-ray luminescence computed tomography (XLCT) reconstruction. This method improves speed for the emerging molecular imaging technology without compromising results.

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    Area of Science:

    • Medical Imaging
    • Molecular Imaging
    • Biomedical Engineering

    Background:

    • X-ray luminescence computed tomography (XLCT) is an emerging hybrid molecular imaging technology.
    • XLCT offers high detection sensitivity and low cost.
    • Reconstruction in XLCT faces challenges due to the ill-posed nature of the inverse problem.

    Purpose of the Study:

    • To address the time-consuming nature of XLCT reconstruction algorithms.
    • To propose a faster and effective algorithm for XLCT image reconstruction.
    • To improve the efficiency of XLCT by reducing computational time.

    Main Methods:

    • A novel three-term conjugate gradient (TTCG) algorithm was developed for XLCT.
    • The TTCG algorithm incorporates useful truncation information into the descent direction.
    • Numerical simulations and real experimental data were used to validate the algorithm's performance.

    Main Results:

    • The proposed TTCG algorithm significantly reduces the time required for XLCT reconstruction.
    • The algorithm effectively speeds up the image reconstruction process.
    • Experimental results confirm the algorithm's ability to accelerate XLCT.

    Conclusions:

    • The three-term conjugate gradient (TTCG) algorithm offers an efficient solution for XLCT reconstruction.
    • This advancement can lower the cost and increase the accessibility of XLCT imaging.
    • The TTCG algorithm is a promising development for accelerating hybrid molecular imaging techniques.