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脑正电子发射断层扫描与脑血管疾病

Brain PET and Cerebrovascular Disease.

作者信息

Chiam Katarina, Lee Louis, Kuo Phillip H, Gaudet Vincent C, Black Sandra E, Zukotynski Katherine A

机构信息

Division of Engineering Science, University of Toronto, 40 St. George St., Toronto, ON M5S 2E4, Canada.

Department of Electrical and Computer Engineering, University of Waterloo, 200 University Avenue West, Waterloo, ON N2L 3G1, Canada.

出版信息

PET Clin. 2023 Jan;18(1):115-122. doi: 10.1016/j.cpet.2022.09.007. Epub 2022 Oct 28.

Abstract

Cerebrovascular disease encompasses a broad spectrum of diseases such as stroke, hemorrhage, and cognitive decline associated with vascular narrowing, obstruction, rupture, and inflammation, among other issues. Recent advances in hardware and software have led to improvements in brain PET. Although still in its infancy, machine learning using convolutional neural networks is gaining traction in this area, often with a focus on providing high-quality images with reduced noise using a shorter acquisition time or less radiation exposure for the patient.

摘要

脑血管疾病涵盖了广泛的疾病,如中风、出血以及与血管狭窄、阻塞、破裂和炎症等相关的认知衰退等问题。硬件和软件方面的最新进展已使脑部正电子发射断层扫描(PET)得到改进。尽管仍处于起步阶段,但使用卷积神经网络的机器学习在这一领域正越来越受到关注,其重点通常是在更短的采集时间内为患者提供高质量且噪声降低的图像,或减少辐射暴露。

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