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医学图像处理中的注意力机制研究综述
引用本文:陈朝一,许波,吴英,吴凯文.医学图像处理中的注意力机制研究综述[J].计算机工程与应用,2022,58(5):23-33.
作者姓名:陈朝一  许波  吴英  吴凯文
作者单位:1.广东财经大学 信息学院,广州 510320 2.暨南大学附属第一医院 超声科,广州 510630
基金项目:潮州市卫生健康局科研项目
摘    要:注意力机制通过对深度学习模型判断的可视化,有望成为将深度学习应用于临床实践的安全支撑.通过结合注意力机制,不仅可以验证深度学习模型的判断依据,而且可以让深度学习模型更多地关注重要特征,以提升深度学习模型性能.在未来,这将有助于提高人工智能可解释性、辅助医生诊断以及运用注意力机制发现新诊断方法.介绍并分析医学图像处理常用...

关 键 词:注意力机制  医学图像处理  计算机辅助诊断

Overview of Research on Attention Mechanism in Medical Image Processing
CHEN Chaoyi,XU Bo,WU Ying,WU Kaiwen.Overview of Research on Attention Mechanism in Medical Image Processing[J].Computer Engineering and Applications,2022,58(5):23-33.
Authors:CHEN Chaoyi  XU Bo  WU Ying  WU Kaiwen
Affiliation:1.School of Information Science, Guangdong University of Finance and Economics, Guangzhou 510320, China 2.Ultrasound Department, The First Affiliated Hospital of Jinan University, Guangzhou 510630, China
Abstract:The attention mechanism is expected to be a safe support for applying deep learning to clinical practice by visualizing the judgments of deep learning models.By incorporating the attention mechanism,not only can the judgment basis of deep learning models be verified,but also deep learning models can be made to focus more on important features to improve deep learning model performance.In the future,this will help to improve AI interpretability,assist physicians in diagnosis,and discover new diagnostic methods using attention mechanisms.It introduces and analyzes common datasets and evaluation metrics for medical image processing,states the types of attention mechanisms in medical image processing,presents examples from different types of attention mechanisms that can be effectively used in medical image analysis and diagnosis,and then discusses future prospects and development directions based on the latest trends in their application to medical image processing.
Keywords:attention mechanism  medical image processing  computer-aided diagnosis
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