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Related Concept Videos

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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Brain Imaging01:14

Brain Imaging

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Brain imaging technologies provide critical insights into both the structure and function of the human brain, enabling medical professionals and researchers to diagnose, study, and treat neurological disorders or psychiatric disorders more effectively.
These technologies include computerized axial tomography (CAT or CT scans), positron-emission tomography (PET scans),  magnetic resonance imaging (MRI),  functional magnetic resonance imaging (fMRI), and Transcranial Magnetic...
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Imaging Studies I: CT and MRI01:14

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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:
Computed Tomography (CT) scans use X-ray technology to generate detailed images of bones, organs, and tissues. During the scan, the patient lies on a moving table...
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Author Spotlight: Advancing CBCT and Digital Dental Image Integration with AI-Assisted Digitization
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Artificial Intelligence in Head and Neck Imaging: A Glimpse into the Future.

Kyle Werth1, Luke Ledbetter2

  • 1Department of Radiology, University of Kansas Medical Center, 3901 Rainbow Boulevard, Mailstop 4032, Kansas City, KS 66160, USA.

Neuroimaging Clinics of North America
|July 1, 2020
PubMed
Summary

Artificial intelligence (AI) in medical imaging offers significant potential to enhance radiologist efficiency and patient care. While AI applications are advancing, challenges remain for widespread clinical integration.

Failed At:

2026-06-19T13:38:37.914474+00:00

Keywords:
Artificial intelligenceAutomationDeep learningHead and neck imagingMachine learning

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