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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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IntroductionUltrasonography, or renal ultrasound, is a noninvasive medical imaging technique that uses high-frequency sound waves to visualize the kidneys, ureters, bladder, and surrounding tissues.Indications for Urinary System UltrasonographyUrinary system ultrasonography is indicated in various clinical scenarios, such as:Kidney Stones (Urolithiasis): To detect and monitor the size and presence of kidney or urinary tract stones.Hydronephrosis: To assess the dilation of the renal pelvis and...
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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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Uniform depth channel flow keeps fluid depth consistent along channels such as irrigation canals. In natural channels, such as rivers, approximate uniform flow is often assumed. This condition occurs when the channel’s bottom slope matches the energy slope, balancing potential energy lost from gravity with head loss due to shear stress. This balance prevents depth changes along the channel length, resulting in a steady, uniform flow.Uniform flow in open channels with a constant cross-section...
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To calculate the flow rate for a trapezoidal channel, first, identify the bottom width, side slope, and flow depth of the channel. The cross-sectional area (A) corresponding to the depth of flow (y), channel bottom width (B), and side slope (θ) is determined by:Next, calculate the wetted perimeter, which includes the bottom width and the sloped side lengths in contact with the water. Using the values of the cross-sectional area and the wetted perimeter, determine the hydraulic radius by...
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Measuring the Structure, Composition, and Change of Underwater Environments with Large-area Imaging
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Underwater compressive computational ghost imaging with wavelet enhancement.

Tao Wang, Meiyun Chen, Heng Wu

    Applied Optics
    |October 6, 2021
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    Summary
    This summary is machine-generated.

    We developed a new computational ghost imaging method for clearer underwater images. This technique achieves high-quality imaging even with limited data, improving visibility in aquatic environments.

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    Area of Science:

    • Optics and Photonics
    • Image Processing
    • Oceanography

    Background:

    • Underwater imaging is challenging due to light scattering and absorption.
    • Traditional imaging methods struggle to capture clear details in turbid water.
    • Computational ghost imaging (CGI) offers a potential solution for enhanced underwater visibility.

    Purpose of the Study:

    • To develop an effective computational ghost imaging method for underwater object restoration.
    • To improve image quality and clarity in challenging underwater conditions.
    • To demonstrate the feasibility of sub-Nyquist sampling for underwater CGI.

    Main Methods:

    • A compressive Hadamard computational ghost imaging (CGI) system model was constructed.
    • A compressed-sensing algorithm utilizing total variation regularization was developed for image reconstruction.
    • A wavelet enhancement algorithm was employed for denoising and quality improvement.

    Main Results:

    • The proposed CGI method successfully restored clear images of underwater objects.
    • High-quality imaging was achieved even at a sub-Nyquist sampling ratio.
    • Experimental results validated the effectiveness and advantages of the developed technique.

    Conclusions:

    • The compressive Hadamard CGI method significantly enhances underwater image quality.
    • This approach provides a viable solution for clear imaging in challenging aquatic environments.
    • The method holds promise for various underwater applications requiring high-resolution imaging.