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

Applications of Integration to Probability Density Functions01:27

Applications of Integration to Probability Density Functions

99
Continuous probability distributions are used to model random variables that can take on any real value within a specified range. These variables do not take on isolated or countable values but rather exist on a continuum. For example, the height of an individual can be measured with increasing precision—such as 163.5 or 165.25 centimeters—demonstrating that height is a continuous random variable.The behavior of such variables is described using a probability density function (PDF),...
99
Poisson Probability Distribution01:09

Poisson Probability Distribution

12.3K
A Poisson probability distribution is a discrete probability distribution. It gives the probability of a number of events occurring in a fixed interval of time or space if these events happen at a known average rate and independently of the time since the last event. For example, a book editor might be interested in the number of words spelled incorrectly in a particular book. It might be that, on average, there are five words spelled incorrectly in 100 pages. The interval is 100 pages.
The...
12.3K
Poisson's And Laplace's Equation01:25

Poisson's And Laplace's Equation

4.5K
The electric potential of the system can be calculated by relating it to the electric charge densities that give rise to the electric potential. The differential form of Gauss's law expresses the electric field's divergence in terms of the electric charge density.
4.5K

You might also read

Related Articles

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

Sort by
Same author

Depolarization and speckle analysis in turbid materials composed of disk-like and spherical Mie scatterers.

Optics express·2026
Same author

Label-free differentiation of classical and hypermobile Ehlers-Danlos syndromes using Mueller matrix polarimetry.

Biophotonics discovery·2026
Same author

Revealing the bond exchange and network rearrangement mechanism in vitrimers.

Science advances·2026
Same author

Longitudinal investigation of prostate tumor spheroid proliferation with dynamic line-field optical coherence tomography.

Biomedical optics express·2026
Same author

Electrochemical Unzipping of Carbon Nanotubes in a Molten Salt.

Small (Weinheim an der Bergstrasse, Germany)·2026
Same author

Imaging of Tissue and Cell Dynamics: introduction to the feature issue.

Biomedical optics express·2026

Related Experiment Video

Updated: Mar 19, 2026

Confocal Microscopy Reveals Cell Surface Receptor Aggregation Through Image Correlation Spectroscopy
06:51

Confocal Microscopy Reveals Cell Surface Receptor Aggregation Through Image Correlation Spectroscopy

Published on: August 2, 2018

7.6K

Probability density function formalism for optical coherence tomography signal analysis: a controlled phantom study.

Andrew Weatherbee, Mitsuro Sugita, Kostadinka Bizheva

    Optics Letters
    |June 16, 2016
    PubMed
    Summary

    The probability density function (PDF) of scattered light reveals tissue pathology. Optical coherence tomography (OCT) shows K distribution statistics for low scatterer density, independent of flow, aiding biomedical applications.

    More Related Videos

    Retinal Vascular Reactivity as Assessed by Optical Coherence Tomography Angiography
    07:23

    Retinal Vascular Reactivity as Assessed by Optical Coherence Tomography Angiography

    Published on: March 26, 2020

    8.8K
    Quantum State Engineering of Light with Continuous-wave Optical Parametric Oscillators
    09:23

    Quantum State Engineering of Light with Continuous-wave Optical Parametric Oscillators

    Published on: May 30, 2014

    15.1K

    Related Experiment Videos

    Last Updated: Mar 19, 2026

    Confocal Microscopy Reveals Cell Surface Receptor Aggregation Through Image Correlation Spectroscopy
    06:51

    Confocal Microscopy Reveals Cell Surface Receptor Aggregation Through Image Correlation Spectroscopy

    Published on: August 2, 2018

    7.6K
    Retinal Vascular Reactivity as Assessed by Optical Coherence Tomography Angiography
    07:23

    Retinal Vascular Reactivity as Assessed by Optical Coherence Tomography Angiography

    Published on: March 26, 2020

    8.8K
    Quantum State Engineering of Light with Continuous-wave Optical Parametric Oscillators
    09:23

    Quantum State Engineering of Light with Continuous-wave Optical Parametric Oscillators

    Published on: May 30, 2014

    15.1K

    Area of Science:

    • Biomedical Optics
    • Medical Imaging
    • Tissue Optics

    Background:

    • Backscattered light intensity distribution, described by probability density functions (PDFs), offers insights into tissue characteristics and pathology.
    • Optical coherence tomography (OCT) is a non-invasive imaging technique that can probe tissue microstructure.
    • Understanding light scattering statistics is crucial for interpreting OCT signals and developing diagnostic tools.

    Purpose of the Study:

    • To investigate the probability density function (PDF) of light scattering statistics in a well-characterized tissue-like medium.
    • To determine if OCT amplitude and intensity follow specific statistical distributions, particularly at low scatterer densities.
    • To assess the influence of scatterer flow on these statistical descriptions for potential biomedical applications.

    Main Methods:

    • Utilizing optical coherence tomography (OCT) to acquire data from a well-characterized tissue-like particulate medium.
    • Analyzing the probability density function (PDF) of backscattered light intensities (both amplitude and intensity) from OCT signals.
    • Comparing the observed statistical distributions with theoretical models, including Gaussian and K distributions, under varying scatterer densities and flow conditions.

    Main Results:

    • The study found that for low scatterer densities, the governing statistics for OCT amplitude and intensity significantly deviate from a Gaussian model.
    • The observed distributions were well-described by the K distribution for both OCT amplitude and intensity.
    • The PDF formalism demonstrated independence from scatterer flow conditions, aligning with theoretical predictions.

    Conclusions:

    • The K distribution accurately describes light scattering statistics in tissue-like media at low scatterer densities, as observed with OCT.
    • The motion independence of OCT amplitude and intensity PDF metrics suggests their robustness for biomedical applications.
    • PDF analysis of OCT data holds promise for tissue assessment and characterization, potentially aiding in the diagnosis of pathology.