Automated Detection of Lesion Regions in Lung Computed Tomography Images: A Review

被引：0
|
作者：
Han G.-H. [1 ]
Liu X.-B. [1 ]
Zheng G.-Y. [1 ]
机构：
[1] Beijing Laboratory of Intelligent Information, School of Computer Science, Beijing Institute of Technology, Beijing
来源：
Zidonghua Xuebao/Acta Automatica Sinica | 2017年 / 43卷 / 12期
基金：
中国国家自然科学基金;
关键词：
Computer aided detection; Lung CT; Lung nodule; Lung vessel; Lymph node;
D O I：
10.16383/j.aas.2017.c160850
中图分类号：
学科分类号：
摘要：
Automatic detection of lesion regions in lung CT images is an important research topic in computer aided diagnosis of lung diseases. The system can automatically analyze CT images, output the locations and sizes of lesion regions to help radiologists make decisions, and promote early detection and therapy of lung diseases. In this paper we review the achieved progress of automatic detection methods of lesion regions in lung CT image, and introduce a generic structure for expressing and describing existing detection methods. Furthermore, we provide a systematic analysis and comprehensive performance summary of the latest detection algorithms from 2012. Finally, we point out the challenges ahead, and discuss the future direction of computer aided detection of lung lesions. Copyright © 2017 Acta Automatica Sinica. All rights reserved.
引用
收藏
页码：2071 / 2090
页数：19
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