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

Three-Dimensional Microscopy in Microbiology01:28

Three-Dimensional Microscopy in Microbiology

Three-dimensional imaging techniques are essential in cell biology, allowing researchers to visualize intricate cellular structures with high resolution. Two prominent methods, Differential Interference Contrast Microscopy (DIC) and Confocal Scanning Laser Microscopy (CSLM), provide distinct advantages for imaging live and thick specimens, respectively.Differential Interference Contrast MicroscopyDIC microscopy enhances contrast in transparent, unstained samples by converting phase...
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...

You might also read

Related Articles

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

Sort by
Same author

AI-driven digital holographic microscopy for label-free quantitative cellular analysis: toward low-cost and field-deployable platforms.

Biomedical optics express·2026
Same author

Morphological investigation of astrocyte brain cells using quantitative phase imaging.

Biomedical optics express·2026
Same author

Security authentication and tracking of unmanned moving vehicles with optical ID tags.

Optics express·2026
Same author

3D profilometric object detection in turbid water using integral imaging and deep neural networks.

Optics express·2026
Same author

Underwater multidimensional metrology in degraded environments with augmented reality devices.

Optics express·2026
Same author

Dynamic vision-based underwater optical signal detection system in a degraded environment using multi-dimensional integral imaging and deep learning.

Optics express·2026

Related Experiment Video

Updated: Jun 12, 2026

Three-Dimensional Imaging of Tumor-Bearing Tissue Using the Iterative Bleaching Extends Multiplexity Approach
07:16

Three-Dimensional Imaging of Tumor-Bearing Tissue Using the Iterative Bleaching Extends Multiplexity Approach

Published on: April 25, 2025

Three-dimensional photon counting integral imaging using Bayesian estimation.

Jinhyouk Jung1, Myungjin Cho, Dipak K Dey

  • 1Department of Statistics, University of Connecticut, 215 Glenbrook Road, U-4120 Storrs, Connecticut 06269, USA.

Optics Letters
|June 3, 2010
PubMed
Summary

We introduce a novel Bayesian method for 3D object reconstruction using photon-counting integral imaging. This approach offers improved performance over traditional maximum likelihood estimation (MLE), demonstrated by lower mean square error (MSE).

More Related Videos

Photoelectron Imaging of Anions Illustrated by 310 Nm Detachment of F−
06:53

Photoelectron Imaging of Anions Illustrated by 310 Nm Detachment of F−

Published on: July 27, 2018

Determining 3D Flow Fields via Multi-camera Light Field Imaging
14:25

Determining 3D Flow Fields via Multi-camera Light Field Imaging

Published on: March 6, 2013

Related Experiment Videos

Last Updated: Jun 12, 2026

Three-Dimensional Imaging of Tumor-Bearing Tissue Using the Iterative Bleaching Extends Multiplexity Approach
07:16

Three-Dimensional Imaging of Tumor-Bearing Tissue Using the Iterative Bleaching Extends Multiplexity Approach

Published on: April 25, 2025

Photoelectron Imaging of Anions Illustrated by 310 Nm Detachment of F−
06:53

Photoelectron Imaging of Anions Illustrated by 310 Nm Detachment of F−

Published on: July 27, 2018

Determining 3D Flow Fields via Multi-camera Light Field Imaging
14:25

Determining 3D Flow Fields via Multi-camera Light Field Imaging

Published on: March 6, 2013

Area of Science:

  • Photon-counting integral imaging
  • 3D reconstruction
  • Statistical estimation

Background:

  • Traditional 3D reconstruction from photon-counting elemental images often relies on Maximum Likelihood Estimation (MLE).
  • MLE, while classical, may not always provide optimal performance in terms of reconstruction accuracy.
  • There is a need for more flexible and potentially more accurate statistical methods in this field.

Purpose of the Study:

  • To propose and evaluate a novel Bayesian estimation method for 3D object reconstruction.
  • To compare the performance of the proposed Bayesian method against the conventional MLE method.
  • To demonstrate the advantages of the Bayesian approach in photon-counting integral imaging.

Main Methods:

  • Utilized a Bayesian statistical framework as an alternative to MLE.
  • Applied the Bayesian method to reconstruct 3D objects from photon-counting elemental images.
  • Quantitatively assessed reconstruction performance using the Mean Square Error (MSE) metric.

Main Results:

  • The Bayesian method demonstrated potentially better performance compared to MLE.
  • The Mean Square Error (MSE) was used to illustrate and quantify the performance differences.
  • This study represents the first application of the Bayesian method for 3D reconstruction in photon-counting integral imaging.

Conclusions:

  • The Bayesian method is a viable and potentially superior alternative for 3D reconstruction in photon-counting integral imaging.
  • The proposed method offers enhanced flexibility and improved accuracy (lower MSE) over MLE.
  • This work opens new avenues for advanced 3D imaging techniques using photon-counting detectors.