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Dynamic Layer Separation for Coronary DSA and Enhancement in Fluoroscopic Sequences

  • Ying Zhu
  • Simone Prummer
  • Peng Wang
  • Terrence Chen
  • Dorin Comaniciu
  • Martin Ostermeier
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5762)

Abstract

This paper presents a new technique of coronary digital subtraction angiography which separates layers of moving background structures from dynamic fluoroscopic sequences of the heart and obtains moving layers of coronary arteries. A Bayeisan framework combines dense motion estimation, uncertainty propagation and statistical fusion to achieve reliable background layer estimation and motion compensation for coronary sequences. Encouraging results have been achieved on clinically acquired coronary sequences, where the proposed method considerably improves the visibility and perceptibility of coronary arteries undergoing breathing and cardiac movements. Perceptibility improvement is significant especially for very thin vessels. Clinical benefit is expected in the context of obese patients and deep angulation, as well as in the reduction of contrast dose in normal size patients.

Keywords

Mean Square Error Motion Estimation Uncertainty Propagation Background Pixel Background Structure 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Ying Zhu
    • 1
  • Simone Prummer
    • 2
  • Peng Wang
    • 1
  • Terrence Chen
    • 1
  • Dorin Comaniciu
    • 1
  • Martin Ostermeier
    • 2
  1. 1.Siemens Corporate Research Inc.PrincetonUSA
  2. 2.Siemens AG, Health Care, MED AX PLM-IForchheimGermany

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