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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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Optimization for customized trajectories in cone beam computed tomography.

Sepideh Hatamikia1,2, Ander Biguri3, Gernot Kronreif1

  • 1Austrian Center for Medical Innovation and Technology, Wiener Neustadt, Austria.

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|July 18, 2020
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Summary
This summary is machine-generated.

Optimized cone beam computed tomography (CBCT) trajectories reduce projection numbers by 75% while maintaining image quality. This enables efficient, targeted imaging for interventions with spatial constraints.

Keywords:
cone beam computed tomography (CBCT)image-guided therapy (IGT)limited angle noncircular scan orbitssource-detector trajectory optimizationtomographic reconstruction

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Area of Science:

  • Medical Imaging
  • Image Reconstruction
  • Cone Beam Computed Tomography (CBCT)

Background:

  • Standard CBCT utilizes circular trajectories, requiring numerous projections.
  • Kinematic constraints in patient positioning can limit traditional CBCT scanning.
  • Prior image information can guide trajectory optimization for targeted imaging.

Purpose of the Study:

  • To develop a target-based framework for optimizing 3D CBCT source-detector trajectories.
  • To enable topical information acquisition using limited-angle, noncircular orbits with minimal projections.
  • To reconstruct specific volumes of interest (VOI) under kinematic constraints.

Main Methods:

  • Utilized patient-specific CT data as a digital phantom for trajectory simulations.
  • Optimized projection views by maximizing an objective function based on imaging quality.
  • Evaluated performance using phantoms and quantified image quality with FWHMavg, FSIM, UQI, and CNR.

Main Results:

  • Optimized trajectories achieved comparable image quality to standard CBCT using ~25% of projections.
  • Relative deviations in image quality metrics (FWHMavg, FSIM, UQI, CNR) were below 9%.
  • Optimized trajectories outperformed partial circular trajectories, typically using 116°-152° angular range.

Conclusions:

  • Limited-angle, noncircular CBCT trajectories with optimized orientations provide suitable image quality.
  • This approach has potential for limited-angle, low-dose CBCT interventions under spatial constraints.