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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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Imaging Studies III: Computed Tomography01:27

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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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Related Experiment Video

Updated: Jan 15, 2026

Neutron Radiography and Computed Tomography of Biological Systems at the Oak Ridge National Laboratory's High Flux Isotope Reactor
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An end-to-end CT simulation framework with graphical user interface and sample scanner models.

Amar Kavuri1, Milo Fryling1, Nicholas Felice1,2

  • 1Center for virtual imaging trials, Carl E. Ravin Advanced Imaging Laboratories, Department of Radiology, Duke University, Durham, North Carolina, USA.

Medical Physics
|October 8, 2025
PubMed
Summary
This summary is machine-generated.

A new virtual imaging trials framework enhances medical imaging research with a validated, user-friendly CT simulation tool. This robust software supports diverse computing environments and accurately models various CT scanners for advanced development.

Keywords:
CT simulationDukeSimGraphical User Interfacevirtual imaging trials

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Area of Science:

  • Medical Imaging
  • Computational Modeling
  • Virtual Imaging Trials

Background:

  • Virtual imaging trials (VIT) are crucial for medical imaging experimentation using computational models.
  • Widespread adoption of VIT tools requires accuracy, robustness, and user-friendliness.

Purpose of the Study:

  • Develop a validated, end-to-end computed tomography (CT) simulation framework.
  • Incorporate script-based and graphical user interfaces (GUIs) for accessibility.
  • Ensure simple installation and robust performance across diverse computing environments.

Main Methods:

  • Integrated a validated CT simulator (DukeSim) into an end-to-end framework.
  • Developed a web-based GUI using NodeJS and Express for protocol and scanner configuration.
  • Implemented a Python wrapper script for flexible access and a physics-based CT projector.
  • Included a vendor-neutral reconstruction module (MCR Toolkit) supporting multiple reconstruction techniques.
  • Packaged the software with rigorous version control and testing processes.
  • Demonstrated capabilities by modeling legacy CT scanners.

Main Results:

  • Successfully developed and validated an integrated CT simulation framework.
  • The framework enables seamless adoption and broad applicability in virtual imaging trials.
  • Accurate representation of various clinically relevant scanners was achieved through legacy scanner modeling.

Conclusions:

  • This advancement provides a validated, end-to-end, and robust solution for CT simulation in virtual imaging trials.
  • The framework's flexibility in modeling diverse CT technologies enhances its value.
  • User-friendly interface and validated accuracy position the tool for CT research and optimization.