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Proceedings Paper

Lung vessel suppression and its effect on nodule detection in chest CT scans
Author(s): Xiaomeng Gu; Weiyang Xie; Qiming Fang; Jun Zhao; Qiang Li
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Paper Abstract

The suppression of lung vessels in chest computed tomography (CT) scans can enhance the conspicuity of lung nodules, thereby may improve the detection rate of early lung cancer. This study aimed to verify the effect of lung vessel suppression on the performance of the lung nodule detector. Firstly, a lung vessel suppression technique was developed to remove the vessels while preserving the nodules. Then, a lung nodule detector was developed with two stages: nodule candidate generation and false positive reduction. The vessel suppression and nodule detection methods were validated respectively in 50 three-dimensional (3D) chest CT images with manually-labeled vessel trees and 888 3D chest CT images with manually-located nodules (LUNA16). The lung vessel suppression results were quantitatively evaluated by using the Dice coefficient (DICE) and the contrast-to-noise ratio (CNR), and the lung nodule detection results were quantitatively evaluated by using the sensitivity under two conditions: “without” and “with vessel suppression”. The lung vessel suppression accurately removed vessels with a DICE of 0.943 and improved the CNR for nodules from 4.24 (6.27 dB) to 7.02 (8.46 dB), which subsequently improved the average sensitivity from 0.948 to 0.969 under 7 specified false positives for lung nodule detection.

Paper Details

Date Published: 16 March 2020
PDF: 8 pages
Proc. SPIE 11314, Medical Imaging 2020: Computer-Aided Diagnosis, 113141E (16 March 2020); doi: 10.1117/12.2549405
Show Author Affiliations
Xiaomeng Gu, Shanghai Jiao Tong Univ. (China)
United Imaging Healthcare Co., Ltd. (China)
Weiyang Xie, United Imaging Healthcare Co., Ltd. (China)
Qiming Fang, Shanghai Jiao Tong Univ. (China)
United Imaging Healthcare Co., Ltd. (China)
Jun Zhao, Shanghai Jiao Tong Univ. (China)
Qiang Li, United Imaging Healthcare Co., Ltd. (China)
Huazhong Univ. of Science and Technology (China)


Published in SPIE Proceedings Vol. 11314:
Medical Imaging 2020: Computer-Aided Diagnosis
Horst K. Hahn; Maciej A. Mazurowski, Editor(s)

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