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
Electron Microscope Tomography and Single-particle Reconstruction01:07

Electron Microscope Tomography and Single-particle Reconstruction

2.6K
Transmission electron microscopy (TEM) can be used to determine the 3D structure of biological samples with the help of techniques such as electron microscope tomography and single-particle reconstruction. While single-particle reconstruction can examine macromolecules and macromolecular complexes in vitro conditions only, tomography permits the study of cell components or small cells in vivo.
Electron Tomography
Electron tomography can be performed either in TEM or STEM (scanning transmission...
2.6K
Imaging Studies III: Computed Tomography01:27

Imaging Studies III: Computed Tomography

89
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...
89
Imaging Studies I: CT and MRI01:14

Imaging Studies I: CT and MRI

537
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...
537

You might also read

Related Articles

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

Sort by
Same author

Improved L1/L2 minimization algorithm for segmental limited-angle CT reconstruction.

Journal of X-ray science and technology·2026
Same author

Image reconstruction method for incomplete CT projection based on self-guided image filtering.

Medical & biological engineering & computing·2024
Same author

Bilateral Weighted Relative Total Variation for Low-Dose CT Reconstruction.

Journal of digital imaging·2022
Same author

Structure-guided computed tomography reconstruction from limited-angle projections.

Journal of X-ray science and technology·2022
Same author

Segmental limited-angle CT reconstruction based on image structural prior.

Journal of X-ray science and technology·2022
Same author

Exterior computed tomography image reconstruction based on anisotropic relative total variation in polar coordinates.

Journal of X-ray science and technology·2022
Same journal

Semi-supervised YOLO-DEP for high-resolution X-ray component localization and counting.

Journal of X-ray science and technology·2026
Same journal

Attention based multi-scale edge-aware segmentation and convolutional transformer framework for automated glaucoma detection from fundus images.

Journal of X-ray science and technology·2026
Same journal

Improving the robustness of radiomic features to patient size variations in CBCT imaging for radiotherapy.

Journal of X-ray science and technology·2026
Same journal

DH-OOD: A decoupled hybrid framework for robust skin lesion classification via semantic-structural fusion.

Journal of X-ray science and technology·2026
Same journal

Development and evaluation of deep learning models for automatic coronary stenosis segmentation in X-ray angiography.

Journal of X-ray science and technology·2026
Same journal

Projection-domain reconstruction of patient-specific panoramic images from CBCT projection data.

Journal of X-ray science and technology·2026
See all related articles

Related Experiment Video

Updated: Oct 20, 2025

3D Imaging of Soft-Tissue Samples using an X-ray Specific Staining Method and Nanoscopic Computed Tomography
07:01

3D Imaging of Soft-Tissue Samples using an X-ray Specific Staining Method and Nanoscopic Computed Tomography

Published on: October 24, 2019

10.0K

Anisotropic structure property based image reconstruction method for limited-angle computed tomography.

Changcheng Gong1,2, Li Zeng3,4

  • 1College of Mathematics and Statistics, Chongqing Technology and Business University, Chongqing, China.

Journal of X-Ray Science and Technology
|September 13, 2021
PubMed
Summary
This summary is machine-generated.

Limited-angle computed tomography (CT) reconstruction using the adaptive weighted anisotropic total variation (AwATV) method effectively reduces shading artifacts. This novel approach preserves image structures while enhancing overall image quality, outperforming traditional methods.

Keywords:
CT image reconstructionComputed tomography (CT)anisotropic total variationinverse problem

More Related Videos

High Resolution 3D Imaging of Ex-Vivo Biological Samples by Micro CT
08:57

High Resolution 3D Imaging of Ex-Vivo Biological Samples by Micro CT

Published on: June 21, 2011

18.9K
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

482

Related Experiment Videos

Last Updated: Oct 20, 2025

3D Imaging of Soft-Tissue Samples using an X-ray Specific Staining Method and Nanoscopic Computed Tomography
07:01

3D Imaging of Soft-Tissue Samples using an X-ray Specific Staining Method and Nanoscopic Computed Tomography

Published on: October 24, 2019

10.0K
High Resolution 3D Imaging of Ex-Vivo Biological Samples by Micro CT
08:57

High Resolution 3D Imaging of Ex-Vivo Biological Samples by Micro CT

Published on: June 21, 2011

18.9K
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

482

Area of Science:

  • Medical Imaging
  • Image Reconstruction
  • Computational Imaging

Background:

  • Limited-angle computed tomography (CT) scans suffer from incomplete projection data, leading to shading artifacts in reconstructed images.
  • Conventional reconstruction techniques like filtered back-projection (FBP) and algebraic reconstruction technique (ART) are susceptible to these artifacts.
  • The anisotropy of shading artifacts in limited-angle CT presents an opportunity for targeted artifact reduction.

Purpose of the Study:

  • To develop a novel image reconstruction algorithm for limited-angle CT that effectively reduces shading artifacts.
  • To preserve essential image structures during the reconstruction process.
  • To improve the overall quality of reconstructed CT images.

Main Methods:

  • Proposed an adaptive weighted anisotropic total variation (AwATV) method for image reconstruction.
  • Combined the anisotropy property of shading artifacts with the anisotropic structure property of images.
  • Evaluated the AwATV method using simulation data (FORBILD head phantom) and real CT data.

Main Results:

  • The AwATV method demonstrated superior performance in artifact reduction and structure preservation compared to traditional methods.
  • Reconstructed images achieved higher Structural Similarity Index Measure (SSIM) and Peak Signal-to-Noise Ratio (PSNR) values.
  • The Root Mean Square Error (RMSE) was significantly reduced, indicating improved image fidelity.

Conclusions:

  • The proposed AwATV method offers a significant advancement in limited-angle CT image reconstruction.
  • AwATV effectively mitigates shading artifacts while preserving critical image details.
  • This technique leads to higher quality CT images suitable for clinical applications.