Contour-based lung shape analysis in order to tuberculosis detection: modeling and feature description.
Statistical shape analysis of lung is a reliable alternative method for diagnosing pulmonary diseases such as tuberculosis (TB). The 2D contour-based lung shape analysis is investigated and developed using Fourier descriptors (FDs). The proposed 2D lung shape analysis is carried out in threefold: (1...
| Publicado en: | Medical & Biological Engineering & Computing Vol. 58; no. 9; pp. 1965 - 1987 |
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| Autores principales: | , , |
| Formato: | research tables/charts Journal Article |
| Publicado: |
Springer Nature
Sep2020
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=145048073&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 145048073 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 01400118 PO0 jtl: Medical & Biological Engineering & Computing issn: 01400118 maglogo: N pubinfo: dt: Sep2020 vid: 58 iid: 9 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 145048073 144438171 145048073 NLM32572669 145048073 10.1007/s11517-020-02192-y NLM32572669 145048073 ppf: 1965 ppct: 22 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: Contour-based lung shape analysis in order to tuberculosis detection: modeling and feature description. aug: au: Afzali, Ali Babapour Mofrad, Farshid Pouladian, Majid affil: Department of Medical Radiation Engineering, Science and Research Branch, Islamic Azad University, Tehran, Iran sug: subj: Lung Tuberculosis, Pulmonary Tuberculosis, Pulmonary Pathology Lung Pathology Models, Statistical Body Weights and Measures Mathematics Resource Databases Models, Anatomic Biomedical Engineering Radiographic Image Interpretation, Computer-Assisted Statistics and Numerical Data Factor Analysis ab: Statistical shape analysis of lung is a reliable alternative method for diagnosing pulmonary diseases such as tuberculosis (TB). The 2D contour-based lung shape analysis is investigated and developed using Fourier descriptors (FDs). The proposed 2D lung shape analysis is carried out in threefold: (1) represent the normal and the abnormal (i.e. pulmonary tuberculosis (PTB)) lung shape models using Fourier descriptors modeling (FDM) framework from chest X-ray (CXR) images, (2) estimate and compare the 2D inter-patient lung shape variations for the normal and abnormal lungs by applying principal component analysis (PCA) techniques, and (3) describe the optimal type of contour-based feature vectors to train a classifier in order to detect TB using one publicly available dataset-namely the Montgomery dataset. Since almost all of the previous works in lung shape analysis are content-based analysis, we proposed contour-based lung shape analysis for statistical modeling and feature description of PTB cases. The results show that the proposed approach is able to explain more than 95% of total variations in both of the normal and PTB cases using only 6 and 7 principal component modes for the right and the left lungs, respectively. In case of PTB detection, using 138 lung cases (80 normal and 58 PTB cases), we achieved the accuracy (ACC) and the area under the curve (AUC) of 82.03% and 88.75%, respectively. In comparison with existing state-of-art studies in the same dataset, the proposed approach is a very promising supplement for diagnosis of PTB disease. The method is robust and valuable for application in 2D automatic segmentation, classification, and atlas registration. Moreover, the approach could be used for any kind of pulmonary diseases. Graphical abstract Contour-based lung shape analysis in order to detect tuberculosis: modeling and feature description. pubtype: Academic Journal doctype: research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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