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Related Concept Videos

Computed Tomography01:10

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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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Imaging Studies III: Computed Tomography01:27

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DefinitionComputed Tomography (CT) of the genitourinary (GU) tract is a non-invasive imaging modality that utilizes X-rays and computer processing to generate detailed cross-sectional images of the urinary system, encompassing the kidneys, ureters, bladder, and adjacent structures such as the adrenal glands.PurposeCT scans of the GU tract serve several diagnostic and therapeutic purposes, including:Diagnosis of Urinary Tract Diseases: Detects kidney stones, tumors, cysts, and congenital...
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Deformation of a Beam under Transverse Loading01:15

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Understanding beam deflection, particularly for indeterminate beams with overhanging segments and multiple concentrated loads, is crucial for ensuring structural integrity and functionality. The process begins with constructing an accurate free-body diagram, which helps identify the forces and moments acting on the beam. This diagram is vital for visualizing how bending moments vary along the beam's length, influencing its curvature.
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Data-Driven Affine Deformation Estimation and Correction in Cone Beam Computed Tomography.

Vincent Van Nieuwenhove, Jan De Beenhouwer, Thomas De Schryver

    IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society
    |January 20, 2017
    PubMed
    Summary
    This summary is machine-generated.

    This study presents a new algorithm to correct motion artefacts in cone beam CT scans. The data-driven method estimates and corrects global affine deformations on projections, significantly reducing image blurring and streak artefacts.

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    Area of Science:

    • Medical Imaging
    • Image Reconstruction
    • Computational Imaging

    Background:

    • Motion and deformation during computed tomography (CT) acquisition cause streak artefacts and blurring in reconstructed images.
    • Existing methods often require markers or tracking systems, adding complexity.
    • Artefacts degrade image quality, hindering accurate diagnosis and analysis.

    Purpose of the Study:

    • To introduce an efficient, data-driven algorithm for estimating and correcting global affine deformations in cone beam CT projections.
    • To eliminate the need for external markers or tracking systems.
    • To reduce motion artefacts in cone beam CT images.

    Main Methods:

    • Developed a novel algorithm to estimate global affine deformations directly on cone beam projections.
    • Proved a relationship between affine transformations and the cone beam transform for correction.
    • Estimated deformation parameters by minimizing a plane-based inconsistency criterion comparing main and reference scans.

    Main Results:

    • The proposed algorithm effectively estimates and corrects global affine deformations.
    • Substantial reduction in motion artefacts observed in both simulated and experimental cone beam CT data.
    • The data-driven approach successfully removed the need for markers or tracking systems.

    Conclusions:

    • The developed algorithm offers an efficient and markerless solution for correcting motion artefacts in cone beam CT.
    • This technique significantly improves image quality by reducing blurring and streak artefacts.
    • The method holds promise for enhancing diagnostic accuracy in various CT applications.