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Related Concept Videos

Imaging Studies for Cardiovascular System V: CT01:28

Imaging Studies for Cardiovascular System V: CT

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Cardiac computed tomography (CT) scanning is an advanced cardiac imaging technique that utilizes CT technology, with or without intravenous (IV) contrast, to produce accurate cross-sectional virtual slices of specific areas of the heart, coronary circulation, and major blood vessels such as the aorta, pulmonary veins, and arteries. The computer processes these slices to generate three-dimensional images. Multidetector CT (MDCT) is a rapid form of CT scanning that captures multiple slices...
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Imaging Studies for Cardiovascular System I:Echocardiography01:17

Imaging Studies for Cardiovascular System I:Echocardiography

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Cardiac imaging studies encompass a wide range of noninvasive and minimally invasive techniques designed to visualize the heart's structure and function in detail. One such technique is echocardiography, which uses high-frequency ultrasound waves to produce detailed images of the heart, known as echocardiograms.
Indications: Echocardiography is utilized to diagnose heart failure, valve disorders, and myocardial infarction. It also assesses cardiac structures' size, shape, and motion,...
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Imaging Studies for Cardiovascular System III: X-Ray01:20

Imaging Studies for Cardiovascular System III: X-Ray

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The most common cardiovascular diagnostic test is an X-ray. It produces images of the heart, blood vessels, and adjacent structures.
Definition and Purpose
An X-ray, or radiograph, is a non-invasive method that uses ionizing radiation to take images of internal structures. It is mainly used in cardiac imaging to examine the heart, lungs, and major blood vessels, aiming to identify abnormalities in the heart's size, shape, and position, such as heart failure, congenital defects, and vascular...
553
Imaging Studies for Cardiovascular System VI: Calcium -Scoring CT01:25

Imaging Studies for Cardiovascular System VI: Calcium -Scoring CT

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Calcium-Scoring CT ScanA calcium-scoring CT scan, also known as coronary artery calcium (CAC) scan, detects calcium deposits in the coronary arteries. This test assesses the risk of coronary artery disease (CAD), which can lead to cardiovascular events such as angina, heart failure, and sudden cardiac arrest.A calcium-scoring CT scan is generally recommended for individuals at intermediate risk of CAD without symptoms. It includes:Men aged 40-75 and women aged 50-75: Especially those with a...
639
Imaging Studies for Cardiovascular System IV: CMRI01:21

Imaging Studies for Cardiovascular System IV: CMRI

450
Cardiovascular magnetic resonance imaging, or CMRI, is a non-invasive diagnostic test that employs a magnetic field and radiofrequency waves to create precise images of the heart and arteries. It provides comprehensive information about cardiac anatomy, function, perfusion, and tissue characterization without ionizing radiation.IndicationsCMRI diagnoses various heart conditions, including tissue damage from heart attacks, ischemic heart disease, myocarditis, aortic issues (tears, aneurysms,...
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Cardiac imaging: working towards fully-automated machine analysis & interpretation.

Piotr J Slomka1, Damini Dey2, Arkadiusz Sitek3

  • 1a Department of Imaging (Division of Nuclear Medicine) and Medicine , Cedars-Sinai Medical Center , Los Angeles , CA , USA.

Expert Review of Medical Devices
|March 10, 2017
PubMed
Summary
This summary is machine-generated.

Automated cardiac imaging analysis using machine learning offers objective insights for cardiovascular disease management. These advanced tools enhance physician capabilities for accurate diagnosis and personalized treatment, moving towards greater automation.

Keywords:
Artificial intelligencecardiac imagingdeep learningimage segmentationmachine learning

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Area of Science:

  • Cardiology
  • Medical Imaging
  • Artificial Intelligence

Background:

  • Non-invasive imaging is crucial for cardiovascular disease management.
  • Quantitative analysis provides objective, evidence-based insights beyond subjective interpretation.
  • Advancements in computing and machine learning (ML) are transforming cardiac imaging analysis.

Purpose of the Study:

  • To review recent advancements in automated quantitative cardiac imaging.
  • To describe ML techniques integrated into cardiac imaging analysis.
  • To discuss challenges for clinical adoption of these technologies.

Main Methods:

  • Focus on widely used clinical cardiac imaging techniques.
  • Review of automated image processing and quantitative analysis tools.
  • Integration of machine learning principles with imaging data.

Main Results:

  • Fully automated processing and interpretation of cardiac imaging are emerging.
  • ML facilitates personalized patient conclusions by integrating quantitative and clinical data.
  • These tools enhance, rather than replace, physician expertise in disease detection and risk stratification.

Conclusions:

  • Automated cardiac imaging and ML are enhancing clinical decision-making.
  • The trend is towards more patient-specific interpretations and increased automation.
  • Overcoming implementation obstacles is key for mainstream clinical practice.