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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.
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...
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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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Reconstruction of 3-Dimensional Histology Volume and its Application to Study Mouse Mammary Glands
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Multigrid reconstruction with block-iterative updates for breast tomosynthesis.

Koen Michielsen1, Johan Nuyts1

  • 1Department of Imaging and Pathology, Division of Nuclear Medicine and Molecular Imaging, KU Leuven, Leuven 3000, Belgium and Medical Imaging Research Center, KU Leuven, Leuven 3000, Belgium.

Medical Physics
|November 2, 2015
PubMed
Summary
This summary is machine-generated.

Multigrid reconstruction significantly enhances digital breast tomosynthesis image quality by improving convergence and reducing artifacts compared to single-grid methods at the same computational cost. Both plane-by-plane and ordered subsets updates offer similar performance benefits in multigrid approaches.

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Area of Science:

  • Medical Physics
  • Image Reconstruction
  • Radiology

Background:

  • Digital breast tomosynthesis (DBT) is an advanced imaging technique for breast cancer detection.
  • Maximum-a-posteriori (MAP) reconstruction algorithms are crucial for image quality in DBT.
  • Block-iterative updates, including plane-by-plane and ordered subsets, are used to accelerate convergence.

Purpose of the Study:

  • To evaluate the advantages of a multigrid approach for maximum-a-posteriori reconstruction in DBT.
  • To compare multigrid reconstruction with plane-by-plane and ordered subsets updates.
  • To assess the impact on convergence speed and artifact reduction.

Main Methods:

  • A previously developed penalized maximum likelihood reconstruction algorithm for DBT was extended.
  • The algorithm was enhanced with multigrid and block-iterative (plane-by-plane or ordered subsets) updates.
  • Evaluations were conducted on a mathematical phantom and patient data at equivalent computational costs, assessing parameters like posterior likelihood, residuals, and signal-to-noise ratio.

Main Results:

  • Multigrid reconstructions showed improved convergence and reduced artifacts compared to single-grid methods.
  • Performance gains diminished with an increasing number of subsets.
  • The chosen multigrid sequences performed well across evaluated parameters, with some trade-offs noted for subset-based reconstructions.

Conclusions:

  • Multigrid reconstruction offers significant advantages over fixed-grid methods in DBT, particularly at comparable computational costs.
  • Both plane-by-plane and ordered subsets update strategies yield similar performance benefits within the multigrid framework.
  • The findings support the use of multigrid approaches for enhanced DBT image reconstruction.