Automated detection of lung nodules in CT images using shape-based genetic algorithm

被引：99

作者：

Dehmeshki, Jamshid ^{[1
]}

Ye, Xujiong ^{[1
]}

Lin, Xinyu ^{[1
]}

Valdivieso, Manho ^{[1
]}

Amin, Hamdan ^{[1
]}

机构：

[1] Medicsight PLC, London W14 8UD, England

来源：

COMPUTERIZED MEDICAL IMAGING AND GRAPHICS | 2007年 / 31卷 / 06期

关键词：

genetic algorithm; template matching; lung nodule detection; computer-aided detection; shape index;

D O I：

10.1016/j.compmedimag.2007.03.002

中图分类号：

R318 [生物医学工程];

学科分类号：

0831 ;

摘要：

A shape-based genetic algorithm template-matching (GATM) method is proposed for the detection of nodules with spherical elements. A spherical-oriented convolution-based filtering scheme is used as a pre-processing step for enhancement. To define the fitness function for GATM, a 3D geometric shape feature is calculated at each voxel and then combined into a global nodule intensity distribution. Lung nodule phantom images are used as reference images for template matching. The proposed method has been validated on a clinical dataset of 70 thoracic CT scans (involving 16,800 CT slices) that contains 178 nodules as a gold standard. A total of 160 nodules were correctly detected by the proposed method and resulted in a detection rate of about 90%, with the number of false positives at approximately 14.6/scan (0.06/slice). The high-detection performance of the method suggested promising potential for clinical applications. (c) 2007 Elsevier Ltd. All rights reserved.

引用

页码：408 / 417

页数：10

共 21 条

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[2] Automated detection of lung nodules in CT scans: Preliminary results [J].