Deep learning for myocardial ischemia auxiliary diagnosis using CZT SPECT myocardial perfusion imaging.

ABSTRACT:

Background

The World Health Organization reported that cardiovascular disease is the most common cause of death worldwide. On average, one person dies of heart disease every 26 min worldwide. Deep learning approaches are characterized by the appropriate combination of abnormal features based on numerous annotated images. The constructed convolutional neural network (CNN) model can identify normal states of reversible and irreversible myocardial defects and alert physicians for further diagnosis.

Methods

Cadmium zinc telluride single-photon emission computed tomography myocardial perfusion resting-state images were collected at Chang Gung Memorial Hospital, Kaohsiung Medical Center, Kaohsiung, Taiwan, and were analyzed with a deep learning convolutional neural network to clas

SUBMITTER: Su TY 

PROVIDER: S-EPMC12755539 | biostudies-literature | 2023 Jan

REPOSITORIES: biostudies-literature