title: [Structural analysis based on adaptive window for pulmonary nodule detection].
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.
authors: School of Biomedical Engineering, Nanfang Hospital, Southern Medical University, Guangzhou 510515, China.E-mail: 007wangkai008@163.com.
authors: Kai
authors: K
authors: Wang
authors: Yu
authors: Y
authors: Zhang
authors: Zhexing
authors: Z
authors: Liu
authors: Bingquan
authors: B
authors: Lin
authors: Zhiqiang
authors: Z
authors: Wu
authors: Lei
authors: L
authors: Cao
mesh_terms: D006801:Humans; D008168:Lung / Q000473:pathology*; D008175:Lung Neoplasms / Q000175:diagnosis*; D014057:Tomography, X-Ray Computed