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Computed Tomography01:10

Computed Tomography

9.7K
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...
9.7K
Imaging Studies III: Computed Tomography01:27

Imaging Studies III: Computed Tomography

825
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...
825
Electron Microscope Tomography and Single-particle Reconstruction01:07

Electron Microscope Tomography and Single-particle Reconstruction

3.1K
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...
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Related Experiment Video

Updated: Apr 18, 2026

Lensfree On-chip Tomographic Microscopy Employing Multi-angle Illumination and Pixel Super-resolution
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Lensfree On-chip Tomographic Microscopy Employing Multi-angle Illumination and Pixel Super-resolution

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A non-linear iterative method for multi-layer DOT sub-surface imaging system.

Hsiang-Wen Hou, Shih-Yang Wu, Hao-Jan Sun

    Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
    |January 9, 2015
    PubMed
    Summary
    This summary is machine-generated.

    This study introduces a novel multiple-input and multiple-output (MIMO) algorithm for functional near-infrared (FNIR) imaging. The method enhances image resolution, improving spatial and depth resolution for better non-invasive diagnostics.

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    Area of Science:

    • Medical Imaging
    • Biomedical Optics
    • Computational Imaging

    Background:

    • Diffuse Optical Tomography (DOT) is a non-invasive imaging technology widely used in clinical diagnosis.
    • Functional Near-Infrared (FNIR) spectroscopy, an application of DOT, typically reconstructs 2D images.
    • Current FNIR methods face limitations in achieving optimal spatial and temporal resolution.

    Purpose of the Study:

    • To propose a novel Multiple-Input and Multiple-Output (MIMO) based data extraction algorithm for FNIR.
    • To enhance both spatial and temporal resolution in FNIR imaging.
    • To improve the layer-by-layer image reconstruction for better diagnostic accuracy.

    Main Methods:

    • A Multiple-Input and Multiple-Output (MIMO) data extraction algorithm was developed.
    • A non-linear iterative method was employed for image reconstruction.
    • The algorithm reconstructs images layer by layer to improve resolution.

    Main Results:

    • Simulation results closely matched original images, indicating high fidelity.
    • The proposed method demonstrated good spatial resolution.
    • The reconstruction method achieved a depth resolution capacity of three layers.

    Conclusions:

    • The MIMO-based algorithm significantly enhances spatial and temporal resolution in FNIR imaging.
    • The non-linear iterative reconstruction method provides accurate, layer-by-layer imaging.
    • This advancement offers improved capabilities for non-invasive clinical diagnosis using FNIR.