Research progress of deep learning in nuclear myocardial perfusion imaging

VernacularTitle:深度学习在核素心肌灌注显像中的研究进展
Author: Hao SONG ¹ ; Zhifang WU ; Xiangfei CHAI ; Rui XI ; Hao GE ; Sijin LI
Author Information

1. 山西医科大学第一医院核医学科、分子影像精准诊疗省部共建协同创新中心，太原　030001
Keywords: Myocardial perfusion imaging; Deep learning; Trends
From: Chinese Journal of Nuclear Medicine and Molecular Imaging 2024;44(2):116-119
CountryChina
Language:Chinese
Abstract: In recent years, artificial intelligence (AI) technology represented by deep learning (DL) has developed rapidly, and smart medical care has become one of the most important application areas of AI. As the most accurate noninvasive test to assess myocardial blood flow, myocardial perfusion imaging (MPI) has important clinical values. At present, the use of DL algorithms to establish learning models for MPI images is still in the research stage, and more external verification and iterative updates are needed before it can be widely used in real time clinical practice. In this article, the application of DL algorithms in MPI is comprehensively elaborated to provide a basis and direction for further research.