Automated selection of myocardial inversion time with a convolutional neural network: Spatial temporal ensemble myocardium inversion network (STEMI-NET).

Journal: Magnetic resonance in medicine
Published Date: Feb 3, 2019

Abstract

PURPOSE: Delayed enhancement imaging is an essential component of cardiac MRI, which is used widely for the evaluation of myocardial scar and viability. The selection of an optimal inversion time (TI) or null point (TI ) to suppress the background myocardial signal is required. The purpose of this study was to assess the feasibility of automated selection of TI using a convolutional neural network (CNN). We hypothesized that a CNN may use spatial and temporal imaging characteristics from an inversion-recovery scout to select TI , without the aid of a human observer.

Authors

  • Naeim Bahrami
    Department of Radiology, University of California, San Diego, California.
  • Tara Retson
    Department of Radiology, University of California, San Diego, California.
  • Kevin Blansit
    Department of Biomedical Informatics, University of California, San Diego, California.
  • Kang Wang
    Department of Orthopedics, Third Hospital of Changsha, Changsha 410015.
  • Albert Hsiao
    Department of Radiology, University of California, San Diego, 9452 Medical Center Dr, 4th Floor, La Jolla, CA 92037 (T.A.R., S.J.K., K.E.J., A.C.Y., S.S.B., L.D.H., A.H.); and Department of Mathematics and Statistics, San Diego State University, San Diego, Calif (K.A.H.).

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