An Automated Segmentation Method for Lung Parenchyma Image Sequences Based on Fractal Geometry and Convex Hull Algorithm

Xiao, Xiaojiao; Zhao, Juanjuan; Qiang, Yan; Wang, Hua; Xiao, Yingze; Zhang, Xiaolong; Zhang, Yudong

doi:10.3390/app8050832

Open AccessArticle

An Automated Segmentation Method for Lung Parenchyma Image Sequences Based on Fractal Geometry and Convex Hull Algorithm

by

Xiaojiao Xiao

¹,

Juanjuan Zhao

^1,*,

Yan Qiang

¹,

Hua Wang

¹,

Yingze Xiao

¹,

Xiaolong Zhang

² and

Yudong Zhang

^3,*

¹

College of Computer Science and Technology, Taiyuan University of Technology, Taiyuan 030000, China

²

College of Information Sciences and Technology, Pennsylvania State University, State College, PA 16802, USA

³

Department of Informatics, University of Leicester, Leicester LE1 7RH, UK

^*

Authors to whom correspondence should be addressed.

Appl. Sci. 2018, 8(5), 832; https://doi.org/10.3390/app8050832

Submission received: 26 March 2018 / Revised: 17 May 2018 / Accepted: 18 May 2018 / Published: 21 May 2018

(This article belongs to the Special Issue Fractal Based Information Processing and Recognition)

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Abstract

Statistically solitary pulmonary nodules are about 6% to 17% of juxtapleural nodules. The accurate segmentation of lung parenchyma sequences of juxtapleural nodules is the basis of subsequent pulmonary nodule segmentation and detection. In order to solve the problem of incomplete segmentation of the juxtapleural nodules and segmentation inefficiency, this paper proposes an automated framework to combine the threshold iteration method to segment the lung parenchyma images and the fractal geometry method to detect the depression boundary. The framework includes an improved convex hull repair to complete the accurate segmentation of the lung parenchyma. The evaluation results confirm that the proposed method can segment juxtapleural lung parenchymal images accurately and efficiently.

Keywords: fractal geometry; convex hull method; juxtapleural nodules; lung parenchymal segmentation

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MDPI and ACS Style

Xiao, X.; Zhao, J.; Qiang, Y.; Wang, H.; Xiao, Y.; Zhang, X.; Zhang, Y. An Automated Segmentation Method for Lung Parenchyma Image Sequences Based on Fractal Geometry and Convex Hull Algorithm. Appl. Sci. 2018, 8, 832. https://doi.org/10.3390/app8050832

AMA Style

Xiao X, Zhao J, Qiang Y, Wang H, Xiao Y, Zhang X, Zhang Y. An Automated Segmentation Method for Lung Parenchyma Image Sequences Based on Fractal Geometry and Convex Hull Algorithm. Applied Sciences. 2018; 8(5):832. https://doi.org/10.3390/app8050832

Chicago/Turabian Style

Xiao, Xiaojiao, Juanjuan Zhao, Yan Qiang, Hua Wang, Yingze Xiao, Xiaolong Zhang, and Yudong Zhang. 2018. "An Automated Segmentation Method for Lung Parenchyma Image Sequences Based on Fractal Geometry and Convex Hull Algorithm" Applied Sciences 8, no. 5: 832. https://doi.org/10.3390/app8050832

APA Style

Xiao, X., Zhao, J., Qiang, Y., Wang, H., Xiao, Y., Zhang, X., & Zhang, Y. (2018). An Automated Segmentation Method for Lung Parenchyma Image Sequences Based on Fractal Geometry and Convex Hull Algorithm. Applied Sciences, 8(5), 832. https://doi.org/10.3390/app8050832

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An Automated Segmentation Method for Lung Parenchyma Image Sequences Based on Fractal Geometry and Convex Hull Algorithm

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