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Related Concept Videos

Imaging Studies for Cardiovascular System III: X-Ray01:20

Imaging Studies for Cardiovascular System III: X-Ray

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...
X-ray Imaging01:24

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German physicist Wilhelm Röntgen (1845–1923) was experimenting with electrical current when he discovered that a mysterious and invisible "ray" would pass through his flesh but leave an outline of his bones on a screen coated with a metal compound. In 1895, Röntgen made the first durable record of the internal parts of a living human: an "X-ray" image (as it came to be called) of his wife’s hand. Scientists worldwide quickly began their own experiments with X-rays, and by 1900, X-ray was widely...
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Computed Tomography

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.
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X-ray Dose Reduction through Adaptive Exposure in Fluoroscopic Imaging
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Published on: September 11, 2011

Robust and fast contrast inflow detection for 2D X-ray fluoroscopy.

Terrence Chen1, Gareth Funka-Lea, Dorin Comaniciu

  • 1Siemens Corporation, Corporate Research, 755 College Road East, Princeton, NJ, USA.

Medical Image Computing and Computer-Assisted Intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention
|October 19, 2011
PubMed
Summary

A new algorithm automatically detects contrast inflow in X-ray fluoroscopy, improving cardiac interventions. This efficient tool streamlines workflows by processing 100 frames per second, enhancing real-time image guidance.

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Area of Science:

  • Medical Imaging
  • Interventional Cardiology
  • Computational Imaging

Background:

  • 2D X-ray fluoroscopy provides real-time guidance crucial for computer-assisted and image-guided interventions.
  • Angiography in cardiac interventions visualizes structures, guides devices, and assesses blood flow, but requires differentiating frames with and without contrast medium.
  • Current computational processing often needs manual adjustments for frames based on contrast presence, hindering workflow efficiency.

Purpose of the Study:

  • To develop and validate a fully automatic algorithm for contrast inflow detection in 2D X-ray fluoroscopy.
  • To enhance the automation of image processing in cardiac interventions.
  • To streamline clinical workflows by eliminating manual frame differentiation.

Main Methods:

  • Development of a novel, fully automatic contrast inflow detection algorithm.
  • Validation of the algorithm's robustness using a dataset of over 1300 real fluoroscopic scenes.
  • Assessment of the algorithm's computational efficiency.

Main Results:

  • The proposed algorithm successfully detects contrast inflow automatically in 2D X-ray fluoroscopy.
  • Robustness was confirmed across more than 1300 diverse fluoroscopic scenes.
  • The algorithm demonstrates high computational efficiency, processing 100 frames within one second.

Conclusions:

  • The automatic contrast inflow detection algorithm is robust and efficient for X-ray fluoroscopy.
  • This automation significantly streamlines clinical workflows in image-guided cardiac interventions.
  • The algorithm holds potential for improving real-time image guidance and analysis in interventional procedures.