Structural analysis based on adaptive window for pulmonary nodule detection.
- Author:
Kai WANG
1
,
2
;
Yu ZHANG
;
Zhexing LIU
;
Bingquan LIN
;
Zhiqiang WU
;
Lei CAO
Author Information
1. School of Biomedical Engineering, Nanfang Hospital, Southern Medical University, Guangzhou 510515, China.E-mail: 007wangkai008@
2. com.
- Publication Type:Journal Article
- MeSH:
Humans;
Lung;
pathology;
Lung Neoplasms;
diagnosis;
Tomography, X-Ray Computed
- From:
Journal of Southern Medical University
2014;34(6):759-765
- CountryChina
- Language:Chinese
-
Abstract:
Radiographic detection of pulmonary nodules based on three-dimensional Hessian matrix is highly sensitive but frequently produces false positive results in areas where blood vessels intersect. We propose a novel approach to pulmonary nodule detection using Hessian matrix-based adaptive window structure analysis, in which the structure coefficients is used to differentiate a voxel that belongs to a nodule or vascular structures, followed by construction of the 3D adaptive window to analyze the local structure characteristics; the nodules were then detected using the discrimination function. The experimental results on pulmonary CT images from 17 patients showed a 100% detection sensitivity for nodules of varying sizes and types, with also significantly reduced false positive results generated by the vessel junctions. This approach provides valuable assistance to follow-up positioning and segmentation of the pulmonary nodules.
