基于深度学习的结核病检测方法综述

Ding Zeyu, R. Yaakob, A. Azman
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引用次数: 1

摘要

结核病导致极高的死亡率,早期发现结核病是拯救患者的关键。深度学习技术已被证明是帮助放射科医生检测异常和多种疾病的重要工具。本研究对基于深度学习的结核病诊断技术进行了分类和分析。提供了可用的公共数据集,并对每种方法的性能进行了全面比较,以供未来的研究人员使用。最后,我们探讨了使用深度学习算法检测结核病的挑战以及该领域未来的研究前景。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Review of Deep Learning-Based Detection Methods for Tuberculosis
Tuberculosis (TB) causes exceptionally high mortality rates, and early identification of TB is the key to saving patients. Deep learning techniques have proven to be an essential tool to assist radiologists in detecting abnormalities and multiple diseases. This study categorizes and analyzes deep learning-based techniques for TB diagnosis. Available public datasets are presented, and each method’s performance is compared comprehensively for the use of future researchers. Finally, we explore the challenges of detecting TB using deep learning algorithms and the future research prospects in this field.
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