Deep learning-based attenuation map generation for myocardial perfusion SPECT.

Journal: European journal of nuclear medicine and molecular imaging
Published Date:

Abstract

PURPOSE: Attenuation correction using CT transmission scanning increases the accuracy of single-photon emission computed tomography (SPECT) and enables quantitative analysis. Current existing SPECT-only systems normally do not support transmission scanning and therefore scans on these systems are susceptible to attenuation artifacts. Moreover, the use of CT scans also increases radiation dose to patients and significant artifacts can occur due to the misregistration between the SPECT and CT scans as a result of patient motion. The purpose of this study is to develop an approach to estimate attenuation maps directly from SPECT emission data using deep learning methods.

Authors

  • Luyao Shi
  • John A Onofrey
  • Hui Liu
    Institute of Urology and Nephrology, The First Affiliated Hospital of Guangxi Medical University, Nanning, China.
  • Yi-Hwa Liu
    Department of Internal Medicine (Cardiology), Yale University, New Haven, CT, USA.
  • Chi Liu