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Related Concept Videos

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...
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...
Electron Microscope Tomography and Single-particle Reconstruction01:07

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
Electron tomography can be performed either in TEM or STEM (scanning transmission...
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...

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Using Tomoauto: A Protocol for High-throughput Automated Cryo-electron Tomography
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Application of optimum coding sequences to computerized classical tomography.

H Stark, R Naab

    Applied Optics
    |March 6, 2010
    PubMed
    Summary
    This summary is machine-generated.

    This study introduces a new matched filtering technique using 1-D code sequences for tomographic image reconstruction. This method enhances signal-to-noise ratio (SNR) and eliminates artifacts, improving image quality.

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    Area of Science:

    • Medical Imaging
    • Signal Processing
    • Tomography

    Background:

    • Conventional matched filtering in tomographic imaging can produce noise and secondary images.
    • Non-negative functions or sequences in traditional methods lead to autocorrelation sidelobes, degrading image quality.

    Purpose of the Study:

    • To improve tomographic image reconstruction using a novel matched filtering approach.
    • To enhance the signal-to-noise ratio (SNR) in coded-source or coded-scan imagery.
    • To eliminate image artifacts caused by sidelobes in conventional methods.

    Main Methods:

    • A variation of matched filtering employing 1-D code sequences with optimal correlation properties was utilized.
    • The technique was applied to the reconstruction of coded-source and coded-scan tomographic imagery.

    Main Results:

    • The reconstructed tomographic imagery exhibited a significantly higher SNR compared to conventional matched filtering.
    • The use of code sequences effectively eliminated noise and secondary images originating from autocorrelation sidelobes.

    Conclusions:

    • The proposed 1-D code sequence-based matched filtering offers superior performance for tomographic image reconstruction.
    • This advanced technique provides clearer, artifact-free images with improved diagnostic potential.