Review of ground glass opacity detection methods in lung CT images

Lv Linying; Liu Xiabi; Zhou Chunwu; Zhao Xinming; Zhao Yanfeng

doi:10.2174/1573405612666160606104405

Review of ground glass opacity detection methods in lung CT images

Lv Linying^*, Liu Xiabi, Zhou Chunwu, Zhao Xinming, Zhao Yanfeng

^*此作品的通讯作者

计算机学院

科研成果: 期刊稿件 › 文献综述 › 同行评审

3 引用（Scopus）

摘要

The automatic detection of Ground-Glass Opacity (GGO) in lung CT images is very useful for early diagnosis of lung cancers. In this paper, we present a study of previous GGO detection methods and summarize a common algorithm framework, which includes three components: preprocessing, candidate extraction and GGO identification. For each component, we discuss the main methods. Also we further describe the evaluation criterion and provide a comparison of the performance of the existing approaches.

源语言	英语
页（从-至）	20-31
页数	12
期刊	Current Medical Imaging
卷	13
期	1
DOI	https://doi.org/10.2174/1573405612666160606104405
出版状态	已出版 - 1 2月 2017

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title = "Review of ground glass opacity detection methods in lung CT images",

abstract = "The automatic detection of Ground-Glass Opacity (GGO) in lung CT images is very useful for early diagnosis of lung cancers. In this paper, we present a study of previous GGO detection methods and summarize a common algorithm framework, which includes three components: preprocessing, candidate extraction and GGO identification. For each component, we discuss the main methods. Also we further describe the evaluation criterion and provide a comparison of the performance of the existing approaches.",

keywords = "Computer aided detection (CAD), GGO detection, GGO nodule, Imaging signs, Lung CT images, Medical imaging",

author = "Lv Linying and Liu Xiabi and Zhou Chunwu and Zhao Xinming and Zhao Yanfeng",

note = "Publisher Copyright: {\textcopyright} 2017 Bentham Science Publishers.",

year = "2017",

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doi = "10.2174/1573405612666160606104405",

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TY - JOUR

T1 - Review of ground glass opacity detection methods in lung CT images

AU - Linying, Lv

AU - Xiabi, Liu

AU - Chunwu, Zhou

AU - Xinming, Zhao

AU - Yanfeng, Zhao

PY - 2017/2/1

Y1 - 2017/2/1

N2 - The automatic detection of Ground-Glass Opacity (GGO) in lung CT images is very useful for early diagnosis of lung cancers. In this paper, we present a study of previous GGO detection methods and summarize a common algorithm framework, which includes three components: preprocessing, candidate extraction and GGO identification. For each component, we discuss the main methods. Also we further describe the evaluation criterion and provide a comparison of the performance of the existing approaches.

AB - The automatic detection of Ground-Glass Opacity (GGO) in lung CT images is very useful for early diagnosis of lung cancers. In this paper, we present a study of previous GGO detection methods and summarize a common algorithm framework, which includes three components: preprocessing, candidate extraction and GGO identification. For each component, we discuss the main methods. Also we further describe the evaluation criterion and provide a comparison of the performance of the existing approaches.

KW - Computer aided detection (CAD)

KW - GGO detection

KW - GGO nodule

KW - Imaging signs

KW - Lung CT images

KW - Medical imaging

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U2 - 10.2174/1573405612666160606104405

DO - 10.2174/1573405612666160606104405

M3 - Review article

AN - SCOPUS:85012054584

SN - 1573-4056

VL - 13

SP - 20

EP - 31

JO - Current Medical Imaging

JF - Current Medical Imaging

IS - 1

ER -

Review of ground glass opacity detection methods in lung CT images

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