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...
Linear Approximation in Time Domain01:21

Linear Approximation in Time Domain

Nonlinear systems often require sophisticated approaches for accurate modeling and analysis, with state-space representation being particularly effective. This method is especially useful for systems where variables and parameters vary with time or operating conditions, such as in a simple pendulum or a translational mechanical system with nonlinear springs.
For a simple pendulum with a mass evenly distributed along its length and the center of mass located at half the pendulum's length, the...
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...
Calibration Curves: Linear Least Squares01:20

Calibration Curves: Linear Least Squares

A calibration curve is a plot of the instrument's response against a series of known concentrations of a substance. This curve is used to set the instrument response levels, using the substance and its concentrations as standards. Alternatively, or additionally, an equation is fitted to the calibration curve plot and subsequently used to calculate the unknown concentrations of other samples reliably.
For data that follow a straight line, the standard method for fitting is the linear...
Curvilinear Motion: Rectangular Components01:23

Curvilinear Motion: Rectangular Components

Curvilinear motion characterizes the movement of a particle or object along a curved path, notably evident when envisioning a car navigating a winding road. If the car starts at point A, its position vector is established within a fixed frame of reference, where the ratio of the position vector to its magnitude signifies the unit vector pointing in the position vector's direction.
As the car advances, its position evolves over time. Quantifying the car's velocity involves computing the time...

You might also read

Related Articles

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

Sort by
Same author

Post-pandemic modeling of COVID-19: Waning immunity determines recurrence frequency.

Mathematical biosciences·2023
Same author

Modeling surface pH measurements of oocytes.

Biomedical physics & engineering express·2022
Same author

Computational model of electrode-induced microenvironmental effects on pH measurements near a cell membrane.

Multiscale modeling & simulation : a SIAM interdisciplinary journal·2021
Same author

Metabolism plays a central role in the cortical spreading depression: Evidence from a mathematical model.

Journal of theoretical biology·2019
Same author

Brain energetics plays a key role in the coordination of electrophysiology, metabolism and hemodynamics: Evidence from an integrated computational model.

Journal of theoretical biology·2019
Same author

Estimating hemodynamic stimulus and blood vessel compliance from cerebral blood flow data.

Journal of theoretical biology·2018
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 27, 2026

Automated 3D Optical Coherence Tomography to Elucidate Biofilm Morphogenesis Over Large Spatial Scales
09:56

Automated 3D Optical Coherence Tomography to Elucidate Biofilm Morphogenesis Over Large Spatial Scales

Published on: August 21, 2019

An adaptive smoothness regularization algorithm for optical tomography.

P Hiltunen1, D Calvetti, E Somersalo

  • 1Helsinki University of Technology, Espoo, 02150, Finland.

Optics Express
|November 26, 2008
PubMed
Summary
This summary is machine-generated.

This study introduces an adaptive regularization method for diffuse optical tomography (DOT) to improve image reconstruction. The new scheme effectively identifies blocky structures and enhances image quality in near-infrared imaging.

More Related Videos

Near Infrared Optical Projection Tomography for Assessments of β-cell Mass Distribution in Diabetes Research
15:18

Near Infrared Optical Projection Tomography for Assessments of β-cell Mass Distribution in Diabetes Research

Published on: January 12, 2013

Related Experiment Videos

Last Updated: Jun 27, 2026

Automated 3D Optical Coherence Tomography to Elucidate Biofilm Morphogenesis Over Large Spatial Scales
09:56

Automated 3D Optical Coherence Tomography to Elucidate Biofilm Morphogenesis Over Large Spatial Scales

Published on: August 21, 2019

Near Infrared Optical Projection Tomography for Assessments of β-cell Mass Distribution in Diabetes Research
15:18

Near Infrared Optical Projection Tomography for Assessments of β-cell Mass Distribution in Diabetes Research

Published on: January 12, 2013

Area of Science:

  • Biomedical Optics
  • Medical Imaging
  • Computational Imaging

Background:

  • Diffuse Optical Tomography (DOT) reconstructs optical properties from near-infrared light measurements.
  • DOT is an ill-posed problem requiring regularization for accurate results.
  • Existing methods struggle with accurately representing complex object structures.

Purpose of the Study:

  • To develop an adaptive, inhomogenous, anisotropic smoothness regularization scheme for DOT.
  • To leverage prior knowledge of blocky structures for improved reconstruction.
  • To enhance the accuracy and quality of DOT imaging.

Main Methods:

  • An adaptive regularization algorithm that updates estimates and smoothness penalties iteratively.
  • Incorporation of prior information about blocky object structures.
  • Validation using simulated and three-dimensional phantom data.

Main Results:

  • The algorithm successfully located blocky inclusions in simulated data.
  • Improved dynamic range of reconstructed images compared to traditional methods.
  • Reduced crosstalk between absorption and diffusion coefficient images.

Conclusions:

  • The proposed adaptive regularization scheme effectively reconstructs blocky structures in DOT.
  • This method offers superior performance over traditional smoothness regularization.
  • The technique shows promise for enhanced accuracy in near-infrared optical imaging.