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Related Concept Videos

Imaging Studies IV: Magnetic Resonance Imaging01:27

Imaging Studies IV: Magnetic Resonance Imaging

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Introduction:Magnetic Resonance Imaging, or MRI, can include a specialized imaging technique of the urinary system known as Magnetic Resonance Urography (MRU). This radiation-free technique uses strong magnetic fields and radio waves to produce detailed images with the help of a computer. MRU is particularly effective for visualizing fluid-filled structures like the kidneys, ureters, and bladder.Applications of MRI in the Genitourinary SystemKidneys and Ureters: MRI detects tumors, cysts,...
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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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Imaging Studies I: Kidney, Ureter, and Bladder Studies01:28

Imaging Studies I: Kidney, Ureter, and Bladder Studies

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Kidney, Ureter, and Bladder (KUB) StudiesKidney, Ureter, and Bladder (KUB) studies are standard diagnostic imaging procedures used to assess the anatomy of the urinary system. They are commonly utilized for patients experiencing abdominal pain or urinary symptoms. By using a simple X-ray of the abdomen, KUB studies can reveal structural and pathological abnormalities within the kidneys, ureters, and bladder. These studies are particularly valuable in diagnosing kidney stones, urinary...
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Ultrasound I: Abdominal Ultrasonography01:20

Ultrasound I: Abdominal Ultrasonography

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Introduction:
Abdominal ultrasonography, commonly known as abdominal ultrasound, is a vital, non-invasive medical imaging technique widely used in healthcare.
Procedure:
This diagnostic tool allows the clinician to visually inspect internal structures within the abdomen, including vital organs such as the liver, gallbladder, pancreas, kidneys, and spleen.
The abdominal ultrasound process begins with applying a special gel to the patient's skin over the abdomen. This gel enhances the...
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Introduction of an Integrated Pathology Image Management, Artificial Intelligence, and Reporting System
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Current and emerging artificial intelligence applications for pediatric abdominal imaging.

Jonathan R Dillman1,2, Elan Somasundaram3,4, Samuel L Brady3,4

  • 1Department of Radiology, Cincinnati Children's Hospital Medical Center, 3333 Burnet Ave., Cincinnati, OH, 45229, USA. jonathan.dillman@cchmc.org.

Pediatric Radiology
|April 12, 2021
PubMed
Summary

Artificial intelligence (AI) enhances medical imaging analysis by mimicking human cognitive functions for data interpretation. This review explores AI applications in abdominal imaging, focusing on pediatric uses.

Keywords:
AbdomenArtificial intelligenceChildrenComputed tomographyDeep learningMachine learningMagnetic resonance imaging

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Area of Science:

  • Medical imaging analysis
  • Artificial intelligence in medicine
  • Radiology and diagnostic imaging

Background:

  • Artificial intelligence (AI) leverages computational power to simulate human cognitive functions, enabling complex inferences from large datasets.
  • Machine learning and deep learning are prominent AI methodologies utilized in medical applications.
  • AI techniques are instrumental in medical image analysis, including detection, segmentation, classification, and reconstruction.

Purpose of the Study:

  • To review current and emerging artificial intelligence methods applied to abdominal imaging.
  • To highlight the application of AI in medical image analysis, including computed tomography (CT), magnetic resonance imaging (MRI), and ultrasound (US).
  • To explore potential future applications of AI in pediatric abdominal imaging.

Main Methods:

  • Review of recent literature on AI applications in abdominal imaging.
  • Focus on traditional machine learning and deep learning techniques.
  • Analysis of AI's role in image evaluation tasks such as detection, segmentation, classification, and reconstruction.

Main Results:

  • AI, encompassing machine learning and deep learning, is increasingly applied to abdominal imaging modalities (CT, MRI, US).
  • AI facilitates automated detection, segmentation, classification (diagnosis, characterization, prediction), and image reconstruction.
  • The review highlights current advancements and emerging trends in AI for abdominal imaging.

Conclusions:

  • Artificial intelligence offers significant potential for advancing abdominal imaging analysis.
  • Future applications of AI in pediatric abdominal imaging warrant further investigation.
  • AI integration promises to enhance diagnostic accuracy and efficiency in medical imaging.