Convolutional neural network in the evaluation of myocardial ischemia from czt spect myocardial perfusion imaging: Comparison to automated quantification

Jui Jen Chen, Ting Yi Su, Wei Shiang Chen, Yen Hsiang Chang*, Henry Horng Shing Lu

*Corresponding author for this work

研究成果: Article同行評審

摘要

This study analyzes CZT SPECT myocardial perfusion images that are collected at Chang Gung Memorial Hospital, Kaohsiung Medical Center in Kaohsiung. This study focuses on the classification of myocardial perfusion images for coronary heart diseases by convolutional neural network techniques. In these gray scale images, heart blood flow distribution contains the most important features. Therefore, data-driven preprocessing is developed to extract the area of interest. After removing the surrounding noise, the three-dimensional convolutional neural network model is utilized to classify whether the patient has coronary heart diseases or not. The prediction accuracy, sensitivity, and specificity are 87.64%, 81.58%, and 92.16%. The prototype system will greatly reduce the time required for physician image interpretation and write reports. It can assist clinical experts in diagnosing coronary heart diseases accurately in practice.

原文English
文章編號514
頁(從 - 到)1-11
頁數11
期刊Applied Sciences (Switzerland)
11
發行號2
DOIs
出版狀態Published - 2 一月 2021

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