Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Computed Tomography01:10

Computed Tomography

7.1K
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...
7.1K
Imaging Studies for Cardiovascular System V: CT01:28

Imaging Studies for Cardiovascular System V: CT

102
Cardiac computed tomography (CT) scanning is an advanced cardiac imaging technique that utilizes CT technology, with or without intravenous (IV) contrast, to produce accurate cross-sectional virtual slices of specific areas of the heart, coronary circulation, and major blood vessels such as the aorta, pulmonary veins, and arteries. The computer processes these slices to generate three-dimensional images. Multidetector CT (MDCT) is a rapid form of CT scanning that captures multiple slices...
102
Imaging Studies III: Computed Tomography01:27

Imaging Studies III: Computed Tomography

91
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...
91
Imaging Studies I: CT and MRI01:14

Imaging Studies I: CT and MRI

538
Introduction: MRI and CT scans are crucial advancements in medical imaging techniques, playing a vital role in diagnosing conditions related to the gastrointestinal (GI) system. Each scan serves distinct purposes, targets specific areas, and requires unique nursing duties.
Description of the Procedures
Computed Tomography (CT) scan:
Computed Tomography (CT) scans use X-ray technology to generate detailed images of bones, organs, and tissues. During the scan, the patient lies on a moving table...
538

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Proton therapy range uncertainty reduction using vendor-agnostic tissue characterization on a virtual photon-counting CT head scan.

Medical physics·2026
Same author

Green Synthesis of ZrO<sub>2</sub> Nanoparticles from Cynodon dactylon: Structural Characterization, Antioxidant Performance, and Corrosion Inhibition of Mild Steel.

ChemPlusChem·2026
Same author

Optimizing energy settings in CdTe, CZT, and Si photon-counting CT for material separation and detection.

Physics in medicine and biology·2026
Same author

Precise Lung Density Quantification with a Physics-based CT Harmonizer.

Radiology. Cardiothoracic imaging·2026
Same author

Demographic distribution matching between real-world and virtual phantom population.

Medical physics·2026
Same author

Utility of the virtual imaging trials methodology for objective characterization of AI systems and training data.

Journal of medical imaging (Bellingham, Wash.)·2026
Same journal

Effective contrast-enhanced preprocessing for intracranial artery segmentation in digital subtraction angiography.

Physics in medicine and biology·2026
Same journal

Improving Plan Quality in Adaptive Proton Therapy Using an Interactive Dose Modification Tool.

Physics in medicine and biology·2026
Same journal

Technical Note: Real-Time MLC Control and Latency Measurement Optimization with External Verification.

Physics in medicine and biology·2026
Same journal

Fetus-Specific Hematopoietic Stem Cell Dosimetry Framework for Leukemia-Relevant Target Cells During Prenatal Development.

Physics in medicine and biology·2026
Same journal

Deep learning-based dose prediction to enhance planning efficiency in cervical brachytherapy with hybrid applicators.

Physics in medicine and biology·2026
Same journal

Corrigendum: Referenceless MR thermometry-a comparison of five methods (2017<i>Phys. Med. Biol</i>.<b>62</b>1-16).

Physics in medicine and biology·2026
See all related articles

Related Experiment Video

Updated: Oct 22, 2025

Author Spotlight: Advancing Human Brain Modulation &#8211; Optimized Protocols for Transcranial Ultrasound Stimulation Experiments
07:52

Author Spotlight: Advancing Human Brain Modulation – Optimized Protocols for Transcranial Ultrasound Stimulation Experiments

Published on: June 28, 2024

1.5K

A scanner-specific framework for simulating CT images with tube current modulation.

Giavanna Jadick1, Ehsan Abadi1,2,3, Brian Harrawood1

  • 1Center for Virtual Imaging Trials, Carl E. Ravin Advanced Imaging Laboratories, Department of Radiology, Duke University School of Medicine, NC, United States of America.

Physics in Medicine and Biology
|August 31, 2021
PubMed
Summary
This summary is machine-generated.

This study developed a computed tomography (CT) simulation framework with tube current modulation (TCM) to create realistic patient-specific images. The tool optimizes TCM for virtual imaging trials, improving image quality and radiation dose efficiency.

Keywords:
DukeSimcomputed tomography (CT)simulationtube current modulation (TCM)virtual imaging trial (VIT)

More Related Videos

Author Spotlight: An Efficient and Robust Software for Automated Fusion of Multiple Preclinical Imaging Modalities
07:13

Author Spotlight: An Efficient and Robust Software for Automated Fusion of Multiple Preclinical Imaging Modalities

Published on: October 27, 2023

1.4K
Retrospective Cardiac Gating with A Prototype Small-Animal X-ray Computed Tomograph
05:32

Retrospective Cardiac Gating with A Prototype Small-Animal X-ray Computed Tomograph

Published on: February 21, 2025

483

Related Experiment Videos

Last Updated: Oct 22, 2025

Author Spotlight: Advancing Human Brain Modulation &#8211; Optimized Protocols for Transcranial Ultrasound Stimulation Experiments
07:52

Author Spotlight: Advancing Human Brain Modulation – Optimized Protocols for Transcranial Ultrasound Stimulation Experiments

Published on: June 28, 2024

1.5K
Author Spotlight: An Efficient and Robust Software for Automated Fusion of Multiple Preclinical Imaging Modalities
07:13

Author Spotlight: An Efficient and Robust Software for Automated Fusion of Multiple Preclinical Imaging Modalities

Published on: October 27, 2023

1.4K
Retrospective Cardiac Gating with A Prototype Small-Animal X-ray Computed Tomograph
05:32

Retrospective Cardiac Gating with A Prototype Small-Animal X-ray Computed Tomograph

Published on: February 21, 2025

483

Area of Science:

  • Medical Imaging
  • Computational Imaging
  • Radiological Physics

Background:

  • Tube current modulation (TCM) is standard in computed tomography (CT) but current simulators lack realistic TCM implementation.
  • This limits patient-specific optimization and realistic virtual imaging trials (VITs).

Purpose of the Study:

  • To develop a CT simulation framework capable of generating realistic images with TCM.
  • To enable patient-specific TCM optimization and enhance VITs with accurate image quality and radiation dose simulation.

Main Methods:

  • Integrated a novel TCM module with the DukeSim CT simulator.
  • Utilized scanner-calibrated TCM parameters and localizer radiographs to compute projection mAs.
  • Validated the framework using physical and computational phantoms, comparing simulated and real scanner data.

Main Results:

  • The simulation pipeline accurately reproduced image noise, texture, spatial resolution, and contrast.
  • The TCM module demonstrated realism in projection mAs and noise magnitude simulation.
  • Pilot VITs showed TCM's impact on image quality varied with patient BMI, demonstrating framework utility.

Conclusions:

  • The developed framework provides realistic CT image simulation with TCM.
  • It supports patient-specific TCM optimization and advanced VITs for improved CT imaging.
  • This tool advances the development of personalized radiation dose reduction strategies in CT.