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Author Notes:

Contributor Information Tracy L. Faber, Department of Radiology and Imaging Sciences, Emory University, Atlanta, GA 30322 USA.

Cesar A. Santana, Department of Radiology and Imaging Sciences, Emory University, Atlanta, GA 30322 USA.

Marina Piccinelli, Department of Mathematics and Computer Science, Emory University, Atlanta, GA 30322 USA.

Jonathon A. Nye, Department of Radiology and Imaging Sciences, Emory University, Atlanta, GA 30322 USA.

John R. Votaw, Department of Radiology and Imaging Sciences, Emory University, Atlanta, GA 30322 USA.

Ernest V. Garcia, Department of Radiology and Imaging Sciences, Emory University, Atlanta, GA 30322 USA. Eldad Haber, Emory University, Atlanta, GA 30322 USA. He is now with the Department of Mathematics, University of British Columbia, Vancouver, BC V6T IZ2, Canada.

The terms of this arrangement have been reviewed and approved by Emory University in accordance with its conflict of interest policies.

Subject:

Research Funding:

T. L. Faber and E. V. Garcia receive royalties from the sale of the Emory Cardiac Toolbox and have equity positions in Syntermed, Inc., which markets both ECTb and the Emory Reconstruction Toolbox.

This work was supported in part by NIH Grant R0 I HL085417 and by EMTech Bio. T. L. Faber and E. V. Garcia receive royalties from the sale of the Emory Cardiac Toolbox and have equity positions in Syntermed, Inc., which markets both ECTb and the Emory Reconstruction Toolbox.

Keywords:

  • Computer-aided diagnosis
  • image registration
  • nuclear medicine

Automatic Alignment of Myocardial Perfusion Images With Contrast-Enhanced Cardiac Computed Tomography

Tools:

Journal Title:

IEEE Transactions on Nuclear Science

Volume:

Volume 58, Number 5

Publisher:

, Pages 2296-2302

Type of Work:

Article | Post-print: After Peer Review

Abstract:

Explicit fusion of perfusion data from Positron Emission Tomography (PET) or Single Photon Emission Computed Tomography (SPECT) with coronary artery anatomy from Computed Tomographic Coronary Angiography (CTA) has been shown to improve the diagnostic yield for coronary artery disease (CAD) compared to either modality alone. However, most clinically available methods were developed for multimodal scanners or require interactive alignment prior to display and analysis. A new approach was developed to register the two distributions obtained either from a single multimodal imager or from separate scanners, and a preliminary validation was undertaken to compare the automatic alignment to interactive alignment by two experts.

Copyright information:

©2011 IEEE

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