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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.
The technique was invented in the 1970s and is based on the principle that as X-rays pass through the body, they are absorbed or reflected at different levels. In the technique, a patient lies on a motorized platform while a computerized axial tomography (CAT) scanner rotates...
Imaging Studies III: Computed Tomography01:27

Imaging Studies III: Computed Tomography

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...
Imaging Studies I: CT and MRI01:14

Imaging Studies I: CT and MRI

Introduction: MRI and CT scans are crucial advancements in medical imaging techniques, playing a vital role in diagnosing conditions related to the gastrointestinal (GI) system. Each scan serves distinct purposes, targets specific areas, and requires unique nursing duties.
Description of the Procedures
Computed Tomography (CT) scan:
Computed Tomography (CT) scans use X-ray technology to generate detailed images of bones, organs, and tissues. During the scan, the patient lies on a moving table...
Positron Emission Tomography01:29

Positron Emission Tomography

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.
One of the main requirements of a PET scan is a positron-emitting radioisotope, which is produced in a cyclotron and then attached to a substance used by the part of the body being...

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Related Experiment Video

Updated: Jul 7, 2026

Multimodal Cross-Device and Marker-Free Co-Registration of Preclinical Imaging Modalities
07:13

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Published on: October 27, 2023

Errors in reprojection methods in computenzed tomography.

H J Trussell, H Orun-Ozturk, M R Civanlar

    IEEE Transactions on Medical Imaging
    |January 1, 1987
    PubMed
    Summary
    This summary is machine-generated.

    This study investigates errors in iterative tomographic reconstruction reprojection. Derived error bounds aid in constraint enforcement, convergence determination, and artifact detection for improved imaging.

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    Area of Science:

    • Medical imaging
    • Computational mathematics
    • Image processing

    Background:

    • Iterative tomographic reconstruction methods incorporate physical constraints.
    • Reprojection of reconstructed images is crucial for these methods.
    • Comparing estimated projections to original data guides constraint enforcement.

    Purpose of the Study:

    • To investigate errors inherent in tomographic reconstruction reprojection schemes.
    • To derive bounds for these reprojection errors.
    • To explore the utility of these bounds in iterative reconstruction.

    Main Methods:

    • Analysis of errors generated during the reprojection step in iterative reconstruction.
    • Derivation of error bounds using signal energy and probabilistic discontinuity assumptions.
    • Application of derived bounds for constraint enforcement, convergence assessment, and artifact detection.

    Main Results:

    • Established bounds for errors occurring in tomographic reprojection.
    • Demonstrated the utility of these bounds in guiding iterative reconstruction processes.
    • Provided a framework for assessing convergence and identifying artifacts.

    Conclusions:

    • The derived error bounds offer valuable insights into iterative tomographic reconstruction.
    • These bounds enhance the reliability of constraint enforcement and artifact detection.
    • The findings contribute to the development of more robust and accurate tomographic imaging techniques.