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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...
Radiological Investigation I: X-ray and CT01:30

Radiological Investigation I: X-ray and CT

Radiological investigations, including X-rays and computed tomography (CT) scans, are critical for diagnosing and evaluating various medical conditions. These imaging techniques provide valuable insights into the body's internal structures, aiding in the detection of abnormalities, assessment of disease progression, and development of treatment strategies. This article delves into two primary radiological investigations, chest X-rays and CT scans, outlining their purpose, procedures, and the...
X-ray Imaging01:24

X-ray Imaging

German physicist Wilhelm Röntgen (1845–1923) was experimenting with electrical current when he discovered that a mysterious and invisible "ray" would pass through his flesh but leave an outline of his bones on a screen coated with a metal compound. In 1895, Röntgen made the first durable record of the internal parts of a living human: an "X-ray" image (as it came to be called) of his wife’s hand. Scientists worldwide quickly began their own experiments with X-rays, and by 1900, X-ray was widely...
Imaging Studies for Cardiovascular System III: X-Ray01:20

Imaging Studies for Cardiovascular System III: X-Ray

The most common cardiovascular diagnostic test is an X-ray. It produces images of the heart, blood vessels, and adjacent structures.
Definition and Purpose
An X-ray, or radiograph, is a non-invasive method that uses ionizing radiation to take images of internal structures. It is mainly used in cardiac imaging to examine the heart, lungs, and major blood vessels, aiming to identify abnormalities in the heart's size, shape, and position, such as heart failure, congenital defects, and vascular...

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Updated: Jun 8, 2026

Tree Core Analysis with X-ray Computed Tomography
06:56

Tree Core Analysis with X-ray Computed Tomography

Published on: September 22, 2023

Developments with maximum-likelihood x-ray computed tomography: initial testing with real data.

J A Browne, T J Holmes

    Applied Optics
    |October 2, 2010
    PubMed
    Summary
    This summary is machine-generated.

    Maximum-likelihood (ML) computed tomography shows advantages in reducing noise and improving detail for low-count data. Further development is needed to address artifacts and optimize spatial resolution.

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    3D Printing of Preclinical X-ray Computed Tomographic Data Sets
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    3D Printing of Preclinical X-ray Computed Tomographic Data Sets

    Published on: March 22, 2013

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    Last Updated: Jun 8, 2026

    Tree Core Analysis with X-ray Computed Tomography
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    3D Printing of Preclinical X-ray Computed Tomographic Data Sets
    11:06

    3D Printing of Preclinical X-ray Computed Tomographic Data Sets

    Published on: March 22, 2013

    Area of Science:

    • Medical Imaging
    • Image Reconstruction
    • Computational Science

    Background:

    • X-ray computed tomography (CT) is crucial for non-invasive imaging.
    • Traditional filtered backprojection (FBP) methods can struggle with low-count data, leading to artifacts.
    • Maximum-likelihood (ML) approaches offer a promising alternative for image reconstruction.

    Purpose of the Study:

    • To investigate the potential and limitations of a maximum-likelihood (ML) approach for x-ray computed tomography.
    • To compare ML reconstruction with filtered backprojection (FBP) using low-count industrial CT data.
    • To evaluate the impact of Poisson modeling and iterative algorithms on image quality.

    Main Methods:

    • Utilized a maximum-likelihood (ML) approach with Poisson modeling and an iterative gradient-based algorithm.
    • Incorporated finite x-ray beam width into the ML model, extending previous work.
    • Applied ML and FBP to reconstruct images from low-count industrial CT data of a concrete cube with metal bars.

    Main Results:

    • ML reconstruction demonstrated significantly reduced noise and streak artifacts compared to FBP.
    • Structural details were more apparent in the ML reconstructed images.
    • ML images showed a closer quantitative fit to the observed low-count data.
    • ML approach indicated potential for finer spatial resolution than FBP.

    Conclusions:

    • The ML approach shows significant advantages for low-count CT data, offering improved image quality and detail.
    • Current limitations include peripheral smoothing artifacts and noise/edge artifacts at higher resolutions.
    • Future work should focus on algorithm acceleration and advanced ML/maximum a posteriori methods to overcome limitations.