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Computed Tomography01:10

Computed Tomography

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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Imaging Studies III: Computed Tomography

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Electron Microscope Tomography and Single-particle Reconstruction

Transmission electron microscopy (TEM) can be used to determine the 3D structure of biological samples with the help of techniques such as electron microscope tomography and single-particle reconstruction. While single-particle reconstruction can examine macromolecules and macromolecular complexes in vitro conditions only, tomography permits the study of cell components or small cells in vivo.
Electron Tomography
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Imaging Studies II: Ultrasonography

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Positron Emission Tomography01:29

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Positron emission tomography (PET) is a medical imaging technique involving radiopharmaceuticals — substances that emit short-lived radiation. Although the first PET scanner was introduced in 1961, it took 15 more years before radiopharmaceuticals were combined with the technique and revolutionized its potential.
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Tomographical imaging using uniformly redundant arrays.

T M Cannon, E E Fenimore

    Applied Optics
    |March 9, 2010
    PubMed
    Summary
    This summary is machine-generated.

    Uniformly redundant arrays (URAs) using m-sequences outperform quadratic residue URAs in close-up tomographic imaging. M-sequence URAs reduce artifacts and maintain depth resolution, offering superior performance over random arrays.

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    Area of Science:

    • Medical Imaging
    • Nuclear Medicine
    • Applied Physics

    Background:

    • Uniformly redundant arrays (URAs) are known for artifact-free imaging of distant radioactive sources.
    • Previous studies suggest random arrays offer better tomographical properties than Fresnel zone plates and nonredundant arrays.

    Purpose of the Study:

    • To evaluate the performance of two URA apertures in a close-up tomographic imaging system.
    • To compare the efficacy of m-sequence-based URAs versus quadratic residue-based URAs for tomographic imaging.

    Main Methods:

    • Investigated two types of URAs: one based on m sequences and another based on quadratic residues.
    • Assessed performance in a close-up tomographic imaging setup.
    • Evaluated image quality, artifact levels, and depth resolution.

    Main Results:

    • M-sequence URAs demonstrated superiority over quadratic residue URAs in close-up tomographic imaging.
    • M-sequence arrays produced fewer defocus artifacts and showed greater resilience to close-up imaging effects.
    • The URA system, particularly with m-sequence arrays, maintained tomographic depth resolution even with sources close to the detector.
    • M-sequence URAs yielded better images compared to random arrays.

    Conclusions:

    • M-sequence-based URAs are more effective than quadratic residue URAs for close-up tomographic imaging applications.
    • URA systems, especially those employing m-sequences, offer robust performance and maintain image quality under challenging close-up conditions.
    • These findings enhance the understanding of URA performance in tomographic systems and suggest m-sequence URAs as a preferred choice.