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

Guang Hui Han; Xia Bi Liu; Guang Yuan Zheng

doi:10.16383/j.aas.2017.c160850

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

Guang Hui Han, Xia Bi Liu^*, Guang Yuan Zheng

^*Corresponding author for this work

School of Computer Science and Technology

Beijing Institute of Technology

Research output: Contribution to journal › Review article › peer-review

4 Citations (Scopus)

Abstract

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.

Original language	English
Pages (from-to)	2071-2090
Number of pages	20
Journal	Zidonghua Xuebao/Acta Automatica Sinica
Volume	43
Issue number	12
DOIs	https://doi.org/10.16383/j.aas.2017.c160850
Publication status	Published - 1 Dec 2017

Keywords

Computer aided detection
Lung CT
Lung nodule
Lung vessel
Lymph node

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title = "Automated Detection of Lesion Regions in Lung Computed Tomography Images: A Review",

abstract = "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.",

keywords = "Computer aided detection, Lung CT, Lung nodule, Lung vessel, Lymph node",

author = "Han, {Guang Hui} and Liu, {Xia Bi} and Zheng, {Guang Yuan}",

year = "2017",

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doi = "10.16383/j.aas.2017.c160850",

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T1 - Automated Detection of Lesion Regions in Lung Computed Tomography Images

T2 - A Review

AU - Han, Guang Hui

AU - Liu, Xia Bi

AU - Zheng, Guang Yuan

PY - 2017/12/1

Y1 - 2017/12/1

N2 - 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.

AB - 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.

KW - Computer aided detection

KW - Lung CT

KW - Lung nodule

KW - Lung vessel

KW - Lymph node

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M3 - Review article

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SN - 0254-4156

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JF - Zidonghua Xuebao/Acta Automatica Sinica

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ER -

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

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