title: Pulmonary Nodule Detection Model Based on SVM and CT Image Feature-Level Fusion with Rough Sets.
abstract: In order to improve the detection accuracy of pulmonary nodules in CT image, considering two problems of pulmonary nodules detection model, including unreasonable feature structure and nontightness of feature representation, a pulmonary nodules detection algorithm is proposed based on SVM and CT image feature-level fusion with rough sets. Firstly, CT images of pulmonary nodule are analyzed, and 42-dimensional feature components are extracted, including six new 3-dimensional features proposed by this paper and others 2-dimensional and 3-dimensional features. Secondly, these features are reduced for five times with rough set based on feature-level fusion. Thirdly, a grid optimization model is used to optimize the kernel function of support vector machine (SVM), which is used as a classifier to identify pulmonary nodules. Finally, lung CT images of 70 patients with pulmonary nodules are collected as the original samples, which are used to verify the effectiveness and stability of the proposed model by four groups' comparative experiments. The experimental results show that the effectiveness and stability of the proposed model based on rough set feature-level fusion are improved in some degrees.
authors.affiliation: School of Science, Ningxia Medical University, Ningxia, Yinchuan 750004, China.
authors.forename: Tao
authors.identifier: 0000-0002-8145-712X
authors.initials: T
authors.lastname: Zhou
authors.affiliation: School of Science, Ningxia Medical University, Ningxia, Yinchuan 750004, China.
authors.forename: Huiling
authors.initials: H
authors.lastname: Lu
authors.affiliation: School of Science, Ningxia Medical University, Ningxia, Yinchuan 750004, China.
authors.forename: Junjie
authors.initials: J
authors.lastname: Zhang
authors.affiliation: Department of Urology, The Generel Hospital of Ningxia Medical University, Ningxia, Yinchuan 750004, China.
authors.forename: Hongbin
authors.initials: H
authors.lastname: Shi
mesh_terms: D006801:Humans; D008175:Lung Neoplasms / Q000000981:diagnostic imaging*; D010363:Pattern Recognition, Automated / Q000379:methods*; D011856:Radiographic Image Enhancement / Q000379:methods; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D003074:Solitary Pulmonary Nodule / Q000000981:diagnostic imaging*; D013382:Subtraction Technique; D060388:Support Vector Machine; D014057:Tomography, X-Ray Computed / Q000379:methods*