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

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...
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...

You might also read

Related Articles

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

Sort by
Same author

Assessment of hydrological loading displacement from GNSS and GRACE data using deep learning algorithms.

Scientific reports·2025
Same author

Prediction on a Missing Ferroelectric Butterfly Phosphorus Allotrope and Its Energy-Favorable Low-Dimensional Forms.

The journal of physical chemistry letters·2025
Same author

Phylogenetic Relationship and Characterization of the Complete Mitochondrial Genome of the Cuckoo Species <i>Clamator coromandus</i> (Aves: Cuculidae).

International journal of molecular sciences·2025
Same author

A Computational Framework Analysis of Public Attitudes Toward Male Human Papillomavirus Infection and Its Vaccination in China: Based on Weibo Data.

Healthcare (Basel, Switzerland)·2025
Same author

Harnessing near-infrared and Raman spectral sensing and artificial intelligence for real-time monitoring and precision control of bioprocess.

Bioresource technology·2025
Same author

Risk Factors, Microbiology, and Prognosis of Diabetic Foot Osteomyelitis: A Retrospective Cohort Study.

Endocrine practice : official journal of the American College of Endocrinology and the American Association of Clinical Endocrinologists·2025

Related Experiment Video

Updated: May 17, 2026

Four-Dimensional CT Analysis Using Sequential 3D-3D Registration
05:05

Four-Dimensional CT Analysis Using Sequential 3D-3D Registration

Published on: November 23, 2019

4D cone beam CT via spatiotemporal tensor framelet.

Hao Gao, Ruijiang Li, Yuting Lin

    Medical Physics
    |November 7, 2012
    PubMed
    Summary

    A novel spatiotemporal tensor framelet (STF) method enhances four-dimensional cone-beam CT (4DCBCT) imaging. This technique improves image quality, speeds up reconstruction, and reduces radiation dose for image-guided radiation therapy.

    Area of Science:

    • Medical Physics
    • Image Reconstruction
    • Radiotherapy Technology

    Background:

    • On-board four-dimensional cone-beam CT (4DCBCT) is crucial for accurate target localization in image-guided radiation therapy.
    • Current 4DCBCT methods suffer from degraded image quality, long imaging times, and high radiation doses, limiting clinical utility.
    • Developing advanced reconstruction techniques is essential to overcome these limitations.

    Discussion:

    • The study introduces a spatiotemporal tensor framelet (STF) method, a novel approach for 4DCBCT reconstruction.
    • STF leverages multilevel, multibasis sparsifying transforms to exploit spatiotemporal correlations in patient anatomy during respiration.
    • The algorithm is implemented on a GPU for enhanced computational efficiency, enabling faster processing.

    Key Insights:

    More Related Videos

    Three-Dimensional Cephalometric Landmark Annotation Demonstration on Human Cone Beam Computed Tomography Scans
    10:23

    Three-Dimensional Cephalometric Landmark Annotation Demonstration on Human Cone Beam Computed Tomography Scans

    Published on: September 8, 2023

    Reliability of Artificial Intelligence-Based Cone Beam Computed Tomography Integration with Digital Dental Images
    05:49

    Reliability of Artificial Intelligence-Based Cone Beam Computed Tomography Integration with Digital Dental Images

    Published on: February 23, 2024

    Related Experiment Videos

    Last Updated: May 17, 2026

    Four-Dimensional CT Analysis Using Sequential 3D-3D Registration
    05:05

    Four-Dimensional CT Analysis Using Sequential 3D-3D Registration

    Published on: November 23, 2019

    Three-Dimensional Cephalometric Landmark Annotation Demonstration on Human Cone Beam Computed Tomography Scans
    10:23

    Three-Dimensional Cephalometric Landmark Annotation Demonstration on Human Cone Beam Computed Tomography Scans

    Published on: September 8, 2023

    Reliability of Artificial Intelligence-Based Cone Beam Computed Tomography Integration with Digital Dental Images
    05:49

    Reliability of Artificial Intelligence-Based Cone Beam Computed Tomography Integration with Digital Dental Images

    Published on: February 23, 2024

    • The STF-based reconstruction method significantly improves image quality compared to state-of-the-art techniques.
    • Reconstruction of 20 respiratory phases was achieved in under 10 minutes using an NVIDIA Tesla C2070 GPU.
    • The method demonstrates potential for faster, lower-dose 4DCBCT acquisition without compromising image quality.

    Outlook:

    • The STF method holds promise for enabling rapid and low-dose 4DCBCT acquisition.
    • Further integration of STF into clinical workflows could enhance the precision and safety of image-guided radiation therapy.
    • Availability of STF codes facilitates broader research and application in the field.