基于医学影像图像的深度学习在肝脏语义分割和体积测量中的研究进展
Research Progress of Deep Learning in Liver Semantic Segmentation and Volume Measurement Based on Medical Image
DOI: 10.12677/ACM.2023.1371620, PDF,    科研立项经费支持
作者: 秦 勇：重庆医科大学附属儿童医院放射科，重庆；张长彪*：重庆市涪陵区人民医院放射科，重庆
关键词: 深度学习；肝脏；医学影像；综述；Deep Learning； Liver； Medical Imaging； Review
摘要: 肝脏疾病对全球医疗系统构成了重大挑战。肝脏结构的准确分割和测量对于肝脏疾病的诊断和治疗规划至关重要。近年来，深度学习技术已经成为医学影像领域的强大工具，为自动化和准确的肝脏语义分割和体积测量提供了一种具有潜力的工具和方法。通过分析和总结当前的最新技术和挑战，本综述旨在为这个快速发展的领域的进展和未来方向提供有价值的见解。
Abstract: Liver diseases pose significant challenges to the global healthcare system. Accurate segmentation and measurement of liver structures are crucial for the diagnosis and treatment planning of liver diseases. In recent years, deep learning techniques have emerged as powerful tools in the field of medical imaging, offering a potential solution for automated and accurate liver semantic segmenta-tion and volume measurement. By analyzing and summarizing the latest techniques and challenges, this review aims to provide valuable insights into the progress and future directions of this rapidly evolving field.
文章引用：秦勇, 张长彪. 基于医学影像图像的深度学习在肝脏语义分割和体积测量中的研究进展[J]. 临床医学进展, 2023, 13(7): 11581-11587. https://doi.org/10.12677/ACM.2023.1371620

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