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Imaging Studies III: Computed Tomography01:27

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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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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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Medical Image Processing in an Era of High-Performance Computing.

C A Kulikowski, L Gong

    Yearbook of Medical Informatics
    |September 27, 2016
    PubMed
    Summary

    Advanced computing enhances medical imaging with 3D visualization and data integration. Future research focuses on electronic atlases and visual knowledge representation for better biomedical understanding.

    Area of Science:

    • Medical Informatics
    • Radiology
    • Computer Science

    Background:

    • Medical imaging practices are advancing rapidly due to cost-effective computing and networking.
    • Significant improvements in medical image processing over five years include 3D display, visualization, and analysis.
    • Picture Archiving and Communication Systems (PACS) facilitate image transmission and retrieval.

    Purpose of the Study:

    • To review advancements in medical image processing and computing.
    • To identify emerging trends such as teleradiology, telesurgery, and virtual reality applications.
    • To highlight ongoing challenges in image segmentation, registration, and multimodal fusion.

    Main Methods:

    • Integration of multiple imaging modalities.
    • Development of sophisticated 3D display and visualization techniques.

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  • Utilizing flexible environments for imaging analysis and PACS.

    • Main Results:

    • Enhanced capabilities for image analysis, transmission, and retrieval.
    • Emerging applications in teleradiology, telesurgery, and virtual reality.
    • Progress in building large visual databases like the Visible Human Project.

    Conclusions:

    • Dynamic electronic atlases require new visual knowledge representation techniques and standardization.
    • Linking visual information to medical records, research, and education is crucial.
    • Reasoning with visual information in multimedia systems presents a key challenge for medical informatics researchers.