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Computed Tomography01:10

Computed Tomography

5.7K
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...
5.7K
Imaging Studies III: Computed Tomography01:27

Imaging Studies III: Computed Tomography

44
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...
44
Positron Emission Tomography01:29

Positron Emission Tomography

5.1K
Positron emission tomography (PET) is a medical imaging technique involving radiopharmaceuticals — substances that emit short-lived radiation. Although the first PET scanner was introduced in 1961, it took 15 more years before radiopharmaceuticals were combined with the technique and revolutionized its potential.
One of the main requirements of a PET scan is a positron-emitting radioisotope, which is produced in a cyclotron and then attached to a substance used by the part of the body...
5.1K
Electron Microscope Tomography and Single-particle Reconstruction01:07

Electron Microscope Tomography and Single-particle Reconstruction

2.5K
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...
2.5K
Imaging Studies II: Positron Emission Tomography and Scintigraphy01:25

Imaging Studies II: Positron Emission Tomography and Scintigraphy

230
Positron Emission Tomography (PET) is a medical imaging technique that provides crucial insights into the body's physiological functions at a molecular level. It is an indispensable resource for diagnosing, staging, and monitoring various illnesses, notably cancer, neurological disorders, and cardiovascular conditions.
Fundamental Principles of PET
230
Phase Contrast and Differential Interference Contrast Microscopy01:26

Phase Contrast and Differential Interference Contrast Microscopy

8.6K
Phase-Contrast Microscopes
In-phase-contrast microscopes, interference between light directly passing through a cell and light refracted by cellular components is used to create high-contrast, high-resolution images without staining. It is the oldest and simplest type of microscope that creates an image by altering the wavelengths of light rays passing through the specimen. Altered wavelength paths are created using an annular stop in the condenser. The annular stop produces a hollow cone of...
8.6K

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Related Experiment Video

Updated: Sep 2, 2025

Near Infrared Optical Projection Tomography for Assessments of β-cell Mass Distribution in Diabetes Research
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Variable Imaging Projection Cloud Scattering Tomography.

Roi Ronen, Vadim Holodovsky, Yoav Y Schechner

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    This summary is machine-generated.

    We developed a fast, flexible deep-neural network (DNN) for scattering-based computed tomography (CT) of clouds. This variable imaging projection computed tomography of clouds (VIP-CT) offers superior quality and real-time performance for climate studies.

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    Area of Science:

    • Atmospheric science and remote sensing.
    • Computational imaging and inverse problems.

    Background:

    • Scattering-based computed tomography (CT) reconstructs volumetric scattering media from multi-directional images.
    • Traditional physics-based optimization methods for CT are slow, difficult to scale, and lack flexibility for variable imaging conditions.

    Purpose of the Study:

    • To develop a fast and flexible deep-neural network (DNN) solution for variable imaging projection scattering tomography of clouds (VIP-CT).
    • To enable efficient and high-quality volumetric recovery of large cloud fields for climate studies.

    Main Methods:

    • A deep-neural network (DNN) was trained on a large, physics-based labeled volumetric dataset.
    • The DNN architecture is scale-oblivious, allowing application to arbitrarily large domains.
    • The method was validated by demonstrating CT of a real cloud using empirical data.

    Main Results:

    • VIP-CT significantly outperforms state-of-the-art methods in image quality.
    • The DNN achieves much faster inference speeds, enabling near real-time processing for spaceborne observations.
    • The approach demonstrates flexibility in handling variable viewing geometries and resolutions.

    Conclusions:

    • VIP-CT provides a high-quality, fast, and flexible solution for scattering-based CT of clouds.
    • This learning-based approach offers a potential model for nonlinear CT problems in other scientific domains.
    • The developed code is publicly available for further research and application.