摘要
颞骨CT成像对诊治耳科疾病十分重要,但低剂量条件下存在图像分辨率不足、伪影强及信噪比低等问题,使其临床应用受限。近年深度学习(DL)已在分类、分割及重建医学图像等方面展现出巨大潜力,为提高颞骨CT图像质量提供了新的思路。本文围绕DL用于颞骨CT成像应用进展进行综述。
Temporal bone CT imaging is particularly important for diagnosis and treatment of ear diseases,but there are some issues such as insufficient resolution,strong artifacts and low signal-to-noise ratio under low radiation doses,which limit its’clinical application.Recent years,deep learning(DL)had shown great potential in classifying,segmenting and reconstructing medical images,providing new ideas for improving imaging quality of temporal bone CT.The application progresses of DL in temporal bone CT imaging were reviewed in this article.
作者
李昊岳
薛智元
陆萍萍
张珂
LI Haoyue;XUE Zhiyuan;LU Pingping;ZHANG Ke(Department of Otorhinolaryngology Head and Neck Surgery,Peking University Third Hospital,Beijing 100191,China;Aerospace Information Research Institute,Chinese Academy of Sciences,Beijing 100094,China)
出处
《中国医学影像技术》
CSCD
北大核心
2024年第9期1432-1435,共4页
Chinese Journal of Medical Imaging Technology
基金
国家自然科学基金(62271008)。