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...
Electron Microscope Tomography and Single-particle Reconstruction01:07

Electron Microscope Tomography and Single-particle Reconstruction

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...
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...
Positron Emission Tomography01:29

Positron Emission Tomography

Positron emission tomography (PET) is a medical imaging technique involving radiopharmaceuticals — substances that emit short-lived radiation. Although the first PET scanner was introduced in 1961, it took 15 more years before radiopharmaceuticals were combined with the technique and revolutionized its potential.
One of the main requirements of a PET scan is a positron-emitting radioisotope, which is produced in a cyclotron and then attached to a substance used by the part of the body being...

You might also read

Related Articles

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

Sort by
Same author

Task-Based Sampling of Patient Data for Rigorous Machine Learning/AI Performance Assessment.

Journal of imaging informatics in medicine·2026
Same author

Artificial intelligence-assisted multiscale lung modeling to predict alveolar septal wall stress.

Acta biomaterialia·2025
Same author

Machine learning evaluation of pneumonia severity: subgroup performance in the Medical Imaging and Data Resource Center modified radiographic assessment of lung edema mastermind challenge.

Journal of medical imaging (Bellingham, Wash.)·2025
Same author

Physics-Informed In-Silico Dynamic Computed Tomography of Human Lungs: Generation, Evaluation, and Refinement.

Journal of biomechanical engineering·2025
Same author

Complete spatiotemporal quantification of cardiac motion in mice through multi-view magnetic resonance imaging and super-resolution reconstruction.

Scientific reports·2025
Same author

Dissecting contributions of pulmonary arterial remodeling to right ventricular afterload in pulmonary hypertension.

Bioengineering & translational medicine·2025
Same journal

Denoising algorithm of Φ-OTDR systems based on adaptive fractional wavelet transform denoising.

Optics express·2026
Same journal

Millisecond photon-to-photon latency and high-speed volumetric projection system for optogenetics.

Optics express·2026
Same journal

Polarization-encoded coaxial structured light for high-precision 3D surface profilometry.

Optics express·2026
Same journal

Discrete freeform optical design based on collaborative optimization of point cloud and local normals.

Optics express·2026
Same journal

Ultrafast ghost imaging with 25 GHz speckle switching and wavelength-division multiplexing.

Optics express·2026
Same journal

Atomic vapor cells fabricated by femtosecond laser welding of standard-optical-quality glass.

Optics express·2026
See all related articles

Related Experiment Video

Updated: Jun 8, 2026

Simultaneous Brightfield, Fluorescence, and Optical Coherence Tomographic Imaging of Contracting Cardiac Trabeculae Ex Vivo
12:54

Simultaneous Brightfield, Fluorescence, and Optical Coherence Tomographic Imaging of Contracting Cardiac Trabeculae Ex Vivo

Published on: October 2, 2021

Singular-value decomposition of a tomosynthesis system.

Anna Burvall1, Harrison H Barrett, Kyle J Myers

  • 1Biomedical and X-Ray Physics, Royal Institute of Technology, AlbaNova University Center, SE-10691 Stockholm, Sweden. anna.burvall@biox.kth.se

Optics Express
|October 14, 2010
PubMed
Summary
This summary is machine-generated.

Tomosynthesis offers 3D imaging potential, replacing mammography with minimal dose and cost increases. This study introduces a singular-value decomposition method for analyzing tomosynthesis systems and reconstructing object data.

More Related Videos

Label-free, High-Resolution 3D Imaging and Machine Learning Analysis of Intestinal Organoids via Low-Coherence Holotomography
10:40

Label-free, High-Resolution 3D Imaging and Machine Learning Analysis of Intestinal Organoids via Low-Coherence Holotomography

Published on: August 12, 2025

Cryo-Electron Tomography Remote Data Collection and Subtomogram Averaging
08:55

Cryo-Electron Tomography Remote Data Collection and Subtomogram Averaging

Published on: July 12, 2022

Related Experiment Videos

Last Updated: Jun 8, 2026

Simultaneous Brightfield, Fluorescence, and Optical Coherence Tomographic Imaging of Contracting Cardiac Trabeculae Ex Vivo
12:54

Simultaneous Brightfield, Fluorescence, and Optical Coherence Tomographic Imaging of Contracting Cardiac Trabeculae Ex Vivo

Published on: October 2, 2021

Label-free, High-Resolution 3D Imaging and Machine Learning Analysis of Intestinal Organoids via Low-Coherence Holotomography
10:40

Label-free, High-Resolution 3D Imaging and Machine Learning Analysis of Intestinal Organoids via Low-Coherence Holotomography

Published on: August 12, 2025

Cryo-Electron Tomography Remote Data Collection and Subtomogram Averaging
08:55

Cryo-Electron Tomography Remote Data Collection and Subtomogram Averaging

Published on: July 12, 2022

Area of Science:

  • Medical imaging
  • Radiology
  • Digital signal processing

Background:

  • Tomosynthesis is an emerging 3D imaging technique.
  • It has the potential to replace traditional mammography.
  • It offers 3D information with only a small increase in radiation dose and cost.

Purpose of the Study:

  • To present an analytical singular-value decomposition (SVD) of a tomosynthesis system.
  • To provide a method for determining the measurement component of any object within the system.
  • To demonstrate the utility of this method on an example object.

Main Methods:

  • Analytical singular-value decomposition (SVD) was applied to a tomosynthesis system.
  • The SVD method was used to derive the measurement component of an object.
  • The method was demonstrated using a specific example object.

Main Results:

  • The analytical SVD successfully characterized the tomosynthesis system's measurement component.
  • The derived measurement component represents a reconstruction of the object.
  • This component is suitable for use in observer studies evaluating tomosynthesis image quality.

Conclusions:

  • The presented analytical SVD method provides a framework for understanding tomosynthesis system measurements.
  • The measurement component derived from SVD can serve as an object reconstruction.
  • This approach facilitates future studies on tomosynthesis image quality assessment.