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Computed Tomography01:10

Computed Tomography

9.2K
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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Imaging Studies III: Computed Tomography01:27

Imaging Studies III: Computed Tomography

514
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...
514
Imaging Studies VII: Vascular Imaging01:19

Imaging Studies VII: Vascular Imaging

430
DefinitionRenal angiography, also known as renal arteriography, is an imaging technique used to obtain a comprehensive view of blood flow and the vascular structure of blood vessels in the kidneys and surrounding areas.PurposeRenal angiography detects blood vessel abnormalities in the kidneys, such as aneurysms, stenosis, thrombosis, vascular tumors, and renal artery stenosis. It evaluates kidney function and guides interventional treatments like angioplasty or stent placement.Pre-Procedure...
430
Radiological Investigation II: MRI and Ventilation Perfusion Scan01:30

Radiological Investigation II: MRI and Ventilation Perfusion Scan

782
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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High Bit-Depth Medical Image Compression With HEVC.

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    This summary is machine-generated.

    High Efficiency Video Coding (HEVC) offers superior medical image compression over JPEG 2000, improving cloud healthcare services. This study establishes HEVC

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    Area of Science:

    • Medical Imaging
    • Image Compression
    • Cloud Healthcare

    Background:

    • Efficient medical image storage and retrieval are crucial for cloud-based healthcare.
    • JPEG 2000 is the standard DICOM compression format, but has limitations for image series and 3D imagery.
    • Newer formats like HEVC offer potential for improved compression efficiency.

    Purpose of the Study:

    • To evaluate High Efficiency Video Coding (HEVC) for diagnostically acceptable medical image compression.
    • To compare HEVC's compression efficiency against JPEG 2000.
    • To establish an acceptable HEVC compression range for medical imaging.

    Main Methods:

    • Investigated diagnostically acceptable lossy compression and complexity for high bit-depth medical images.
    • Established an acceptable HEVC compression range based on JPEG 2000 standards.
    • Developed a method to reduce HEVC encoding complexity for medical images.

    Main Results:

    • HEVC demonstrated over 54% increase in compression performance compared to JPEG 2000.
    • Proposed HEVC intra encoding method reduced complexity by over 55% with minimal file size increase.
    • HEVC supports all medical image types, unlike JPEG 2000.

    Conclusions:

    • HEVC provides a unified, more efficient compression solution for diverse medical imaging needs.
    • HEVC significantly enhances medical image compression performance and reduces computational complexity.
    • The findings support HEVC adoption for improved medical image management in cloud environments.