基于深度学习的肺结核检测综述
Review on tuberculosis detection using deep learning
谢浩杰 1鲁明丽 2张陈 1周理想 3滕诣迪 4王明明1
作者信息
- 1. 盐城工学院电气工程学院,江苏盐城 221051
- 2. 常熟理工学院电气与自动化工程学院,江苏常熟 215500
- 3. 苏州大学机电工程学院,江苏苏州 215031
- 4. 常熟理工学院电子信息工程学院,江苏常熟 215500
- 折叠
摘要
基于医学影像的肺结核病灶自动检测技术成为医学图像处理领域的研究热点.本研究围绕深度学习在肺结核病灶检测方面的相关研究与应用展开综述,首先阐述用于肺结核检测的实验基准,涵盖肺部医学影像的相关公开数据库和肺结核检测与分类竞赛的相关研究进展,然后提出肺结核检测领域中深度学习方法与应用的发展趋势,最后分析深度学习在肺结核诊断中面临的挑战.本研究从技术特性、性能优势、应用前景等方面对这些技术的研究进展以及面临的挑战进行总结和展望.
Abstract
The automatic detection of tuberculosis lesions based on medical imaging has become a research hotspot in medical image processing.A comprehensive review of relevant researches and applications pertaining to deep learning in tuberculosis lesion detection is provided,which elucidates the experimental benchmarks in tuberculosis analysis,covering public datasets of pulmonary medical images and recent research advancements in tuberculosis detection and classification competitions,introduces emerging trends in deep learning methods and applications in tuberculosis detection,and analyzes the challenges existing in tuberculosis diagnosis using deep learning.The review summarizes and provides insights into the research advances and challenges of these technologies from the aspects of technical characteristics,performance advantages,and application prospects.
关键词
肺结核/医学影像/自动检测/深度学习/综述Key words
pulmonary tuberculosis/medical image/automatic detection/deep learning/review引用本文复制引用
出版年
2024
NETL
NSTL
万方数据