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Computed Tomography01:10

Computed Tomography

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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...
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Radiological Investigation II: MRI and Ventilation Perfusion Scan01:30

Radiological Investigation II: MRI and Ventilation Perfusion Scan

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Description
Magnetic Resonance Imaging (MRI) and Ventilation Perfusion Scans are two radiological investigations that offer detailed diagnostic images of the body, particularly lung structures.
MRI
MRI uses magnetic fields and radiofrequency signals to distinguish between normal and abnormal tissues. This technology provides a more detailed diagnostic image than CT scans, enabling it to characterize pulmonary nodules, stage bronchogenic carcinoma, and evaluate inflammatory activity in...
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Magnetic Resonance Imaging01:24

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Magnetic resonance imaging (MRI) is a noninvasive medical imaging technique based on a phenomenon of nuclear physics discovered in the 1930s, in which matter exposed to magnetic fields and radio waves was found to emit radio signals. In 1970, a physician and researcher named Raymond Damadian noticed that malignant (cancerous) tissue gave off different signals than normal body tissue. He applied for a patent for the first MRI scanning device in clinical use by the early 1980s. The early MRI...
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Positron Emission Tomography01:29

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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.
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Imaging Studies I: CT and MRI01:14

Imaging Studies I: CT and MRI

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Introduction: MRI and CT scans are crucial advancements in medical imaging techniques, playing a vital role in diagnosing conditions related to the gastrointestinal (GI) system. Each scan serves distinct purposes, targets specific areas, and requires unique nursing duties.
Description of the Procedures
Computed Tomography (CT) scan:
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Imaging Studies III: Computed Tomography01:27

Imaging Studies III: Computed Tomography

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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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Related Experiment Video

Updated: Oct 10, 2025

Whole-brain Segmentation and Change-point Analysis of Anatomical Brain MRI&#8212;Application in Premanifest Huntington's Disease
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XCloud-pFISTA: A Medical Intelligence Cloud for Accelerated MRI.

Yirong Zhou, Chen Qian, Yi Guo

    Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
    |December 11, 2021
    PubMed
    Summary

    We developed XCloud-pFISTA, an accessible cloud platform using machine learning for faster MRI image reconstruction from undersampled data. This accelerates medical imaging and aids future online diagnosis systems.

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    Area of Science:

    • Medical Imaging
    • Cloud Computing
    • Artificial Intelligence

    Background:

    • Machine learning and AI significantly enhance accelerated magnetic resonance imaging (MRI).
    • Cloud computing offers accessible platforms for deploying advanced imaging algorithms.

    Purpose of the Study:

    • To develop an open-access, user-friendly, high-performance medical intelligence cloud platform (XCloud-pFISTA).
    • To reconstruct MRI images efficiently from undersampled k-space data using advanced algorithms.

    Main Methods:

    • Implementation of two state-of-the-art Projected Fast Iterative Soft-Thresholding Algorithm (pFISTA) approaches on a cloud platform.
    • Development of the XCloud-pFISTA system for medical image reconstruction.

    Main Results:

    • Successful implementation of pFISTA algorithms on the cloud computing platform.
    • Demonstration of a high-performance system for MRI image reconstruction from undersampled data.

    Conclusions:

    • The XCloud-pFISTA platform serves as a model for cloud-based medical image reconstruction.
    • This work facilitates future integrated reconstruction and online diagnosis systems.