3D GGO candidate extraction in lung CT images using multilevel thresholding on supervoxels

Shan Huang; Xiabi Liu; Guanghui Han; Xinming Zhao; Yanfeng Zhao; Chunwu Zhou

doi:10.1117/12.2293217

27 February 2018 3D GGO candidate extraction in lung CT images using multilevel thresholding on supervoxels

Shan Huang, Xiabi Liu, Guanghui Han, Xinming Zhao, Yanfeng Zhao, Chunwu Zhou

Proceedings Volume 10575, Medical Imaging 2018: Computer-Aided Diagnosis; 1057533 (2018) https://doi.org/10.1117/12.2293217
Event: SPIE Medical Imaging, 2018, Houston, Texas, United States

Abstract

The earlier detection of ground glass opacity (GGO) is of great importance since GGOs are more likely to be malignant than solid nodules. However, the detection of GGO is a difficult task in lung cancer screening. This paper proposes a novel GGO candidate extraction method, which performs multilevel thresholding on supervoxels in 3D lung CT images. Firstly, we segment the lung parenchyma based on Otsu algorithm. Secondly, the voxels which are adjacent in 3D discrete space and sharing similar grayscale are clustered into supervoxels. This procedure is used to enhance GGOs and reduce computational complexity. Thirdly, Hessian matrix is used to emphasize focal GGO candidates. Lastly, an improved adaptive multilevel thresholding method is applied on segmented clusters to extract GGO candidates. The proposed method was evaluated on a set of 19 lung CT scans containing 166 GGO lesions from the Lung CT Imaging Signs (LISS) database. The experimental results show that our proposed GGO candidate extraction method is effective, with a sensitivity of 100% and 26.3 of false positives per scan (665 GGO candidates, 499 non-GGO regions and 166 GGO regions). It can handle both focal GGOs and diffuse GGOs.

Citation Download Citation

Shan Huang, Xiabi Liu, Guanghui Han, Xinming Zhao, Yanfeng Zhao, and Chunwu Zhou "3D GGO candidate extraction in lung CT images using multilevel thresholding on supervoxels", Proc. SPIE 10575, Medical Imaging 2018: Computer-Aided Diagnosis, 1057533 (27 February 2018); https://doi.org/10.1117/12.2293217

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available