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Related Concept Videos

Computed Tomography01:10

Computed Tomography

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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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Calcium-Scoring CT ScanA calcium-scoring CT scan, also known as coronary artery calcium (CAC) scan, detects calcium deposits in the coronary arteries. This test assesses the risk of coronary artery disease (CAD), which can lead to cardiovascular events such as angina, heart failure, and sudden cardiac arrest.A calcium-scoring CT scan is generally recommended for individuals at intermediate risk of CAD without symptoms. It includes:Men aged 40-75 and women aged 50-75: Especially those with a...
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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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Related Experiment Video

Updated: Apr 18, 2026

3D Imaging of Soft-Tissue Samples using an X-ray Specific Staining Method and Nanoscopic Computed Tomography
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Non-local total variation based low-dose Computed Tomography denoising.

SayedMasoud Hashemi, Soosan Beheshti, Richard S C Cobbold

    Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
    |January 9, 2015
    PubMed
    Summary
    This summary is machine-generated.

    This study introduces probabilistic NLTV (PNLTV), a novel method for low-dose CT imaging. PNLTV effectively reduces noise while preserving fine details, improving diagnostic accuracy in medical imaging.

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    Area of Science:

    • Medical Imaging
    • Image Processing
    • Radiology

    Background:

    • Computed Tomography (CT) imaging involves radiation, raising health concerns.
    • Low-dose CT (LDCT) imaging is crucial but suffers from increased noise, degrading image quality.
    • Image denoising is essential for maintaining diagnostic performance in LDCT.

    Purpose of the Study:

    • To address the limitations of traditional Total Variation (TV) denoising in LDCT.
    • To propose a modified nonlocal TV method, probabilistic NLTV (PNLTV), for improved image denoising.
    • To enhance the preservation of fine details and image textures in denoised LDCT images.

    Main Methods:

    • Development of a probabilistic nonlocal Total Variation (PNLTV) denoising algorithm.
    • Utilizing improved weighting strategies within the PNLTV framework.
    • Implementing a novel stopping criterion based on image wavelet coefficient statistics.

    Main Results:

    • PNLTV demonstrates enhanced denoising performance compared to standard methods.
    • The non-local approach effectively preserves image textures and fine structures.
    • The proposed stopping criterion prevents the removal of small, diagnostically important details.

    Conclusions:

    • PNLTV offers a superior solution for denoising in low-dose CT imaging.
    • The method successfully balances noise reduction with the preservation of critical image features.
    • PNLTV has the potential to improve diagnostic accuracy in medical imaging applications.