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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...
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 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...
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...
X-ray Crystallography02:18

X-ray Crystallography

The size of the unit cell and the arrangement of atoms in a crystal may be determined from measurements of the diffraction of X-rays by the crystal, termed X-ray crystallography.
Diffraction
Diffraction is the change in the direction of travel experienced by an electromagnetic wave when it encounters a physical barrier whose dimensions are comparable to those of the wavelength of the light. X-rays are electromagnetic radiation with wavelengths about as long as the distance between neighboring...
Vector Algebra: Method of Components01:08

Vector Algebra: Method of Components

It is cumbersome to find the magnitudes of vectors using the parallelogram rule or using the graphical method to perform mathematical operations like addition, subtraction, and multiplication. There are two ways to circumvent this algebraic complexity. One way is to draw the vectors to scale, as in navigation, and read approximate vector lengths and angles (directions) from the graphs. The other way is to use the method of components.
In many applications, the magnitudes and directions of...

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Tree Core Analysis with X-ray Computed Tomography
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Eigenvector decomposition of full-spectrum x-ray computed tomography.

Brian J Gonzales1, David S Lalush

  • 1Joint Department of Biomedical Engineering, North Carolina State University and The University of North Carolina at Chapel Hill, Campus Box 7115, Raleigh, NC 27695-7115, USA. gonzalib@gmail.com

Physics in Medicine and Biology
|February 21, 2012
PubMed
Summary
This summary is machine-generated.

This study introduces a novel method using eigenvalue decomposition basis functions to reduce noise in energy-discriminated x-ray computed tomography (CT) scans. This technique significantly improves signal-to-noise ratio (SNR) for better medical imaging.

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Area of Science:

  • Medical Imaging
  • Photon-Counting X-ray Detectors
  • Image Reconstruction

Background:

  • Traditional filtered back-projection (FBP) in x-ray CT is prone to noise.
  • Energy-discriminated CT requires effective noise suppression for accurate spectral data.
  • Novel x-ray systems with photon-counting detectors offer spectral information per projection ray.

Purpose of the Study:

  • To develop and evaluate a noise suppression technique for energy-discriminated x-ray CT.
  • To improve the signal-to-noise ratio (SNR) along the energy axis in CT reconstructions.
  • To leverage eigenvalue decomposition for enhanced image segmentation and data preservation.

Main Methods:

  • Acquired energy-discriminated x-ray CT data using a novel photon-counting detector system.
  • Decomposed material spectral response matrix using eigenvalue decomposition to create basis functions.
  • Projected filtered back-projection (FBP) reconstructions onto these basis functions.

Main Results:

  • Achieved significant noise suppression in CT reconstructions.
  • Preserved crucial energy-axis data, enhancing diagnostic information.
  • Demonstrated marked improvement in SNR along the energy axis for regions of interest.
  • Observed improved SNR even with coarsely sampled energy axes.

Conclusions:

  • Eigenvalue decomposition basis functions effectively suppress noise in energy-discriminated x-ray CT.
  • The method significantly improves the noise-resolution trade-off along the energy axis.
  • This approach enhances the utility of spectral information in CT imaging.