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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 Biological Samples with Optical Microscopy01:18

Imaging Biological Samples with Optical Microscopy

Optical microscopy uses optic principles to provide detailed images of samples. Antonie van Leeuwenhoek designed the first compound optical microscope in the 17th century to visualize blood cells, bacteria, and yeast cells. In 1830, Joseph Jackson Lister created an essentially modern light microscope. The 20th century saw the development of microscopes with enhanced magnification and resolution.
In optical microscopy, the specimen to be viewed is placed on a glass slide and clipped on the stage...
Total Internal Reflection Fluorescence Microscopy01:05

Total Internal Reflection Fluorescence Microscopy

Total internal reflection fluorescence microscopy or TIRF is an advanced microscopic technique used to visualize fluorophores in samples close to a solid surface with a higher refractive index, such as a glass coverslip. TIRF only allows fluorophores in proximity to the solid surface to be excited. When light from a medium with a lower refractive index (such as air) hits the glass coverslip at a critical angle, the light undergoes total internal reflection stead of passing through the glass.
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...

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Optical Coherence Tomography Based Biomechanical Fluid-Structure Interaction Analysis of Coronary Atherosclerosis Progression
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Particle-fixed Monte Carlo model for optical coherence tomography.

Guanglei Xiong, Ping Xue, Jigang Wu

    Optics Express
    |June 5, 2009
    PubMed
    Summary

    A new Particle-Fixed Monte Carlo (PFMC) simulation models Optical Coherence Tomography (OCT) signals. This method explains the exponential decay observed in OCT experimental measurements, improving biomedical imaging simulations.

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    Area of Science:

    • Biomedical Optics
    • Computational Imaging
    • Medical Physics

    Background:

    • Optical Coherence Tomography (OCT) is a vital non-invasive imaging modality in biomedicine.
    • Accurate simulation of OCT signals is crucial for understanding image formation and improving resolution.
    • Existing simulation methods may face computational challenges for complex scattering scenarios.

    Purpose of the Study:

    • To develop a novel Particle-Fixed Monte Carlo (PFMC) simulation model for Optical Coherence Tomography (OCT) signals.
    • To enhance the efficiency of OCT signal simulation through an optimized partitioning scheme.
    • To validate the PFMC model by explaining experimentally observed signal behaviors in OCT.

    Main Methods:

    • Implementation of a Particle-Fixed Monte Carlo (PFMC) simulation approach.
    • Modeling light scattering from temporarily fixed and randomly distributed particles within the sample.
    • Development and application of an efficient partitioning scheme to accelerate the simulation.

    Main Results:

    • The PFMC model successfully simulates OCT signals, considering particle scattering.
    • The proposed partitioning scheme significantly speeds up the simulation process.
    • The model accurately explains the exponential decay of OCT signals at interfaces between different media layers.

    Conclusions:

    • The PFMC simulation provides a robust and efficient method for modeling OCT signals.
    • This simulation approach enhances the understanding of light-tissue interaction in OCT.
    • The PFMC model offers a valuable tool for advancing OCT technology and applications in biomedical imaging.