Extended Gabor approach applied to classification of emphysematous patterns in computed tomography.
Chronic obstructive pulmonary disease (COPD) is a progressive and irreversible lung condition typically related to emphysema. It hinders air from passing through airpaths and causes that alveolar sacs lose their elastic quality. Findings of COPD may be manifested in a variety of computed tomography...
| Publicado en: | Medical & Biological Engineering & Computing Vol. 52; no. 4; pp. 393 - 404 |
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| Autores principales: | , , , |
| Formato: | research Journal Article |
| Publicado: |
Springer Nature
Apr2014
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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=104048254&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 104048254 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 01400118 PO0 jtl: Medical & Biological Engineering & Computing issn: 01400118 maglogo: N pubinfo: dt: Apr2014 vid: 52 iid: 4 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 104048254 NLM24496558 2012516396 10.1007/s11517-014-1139-9 NLM24496558 PMC4254807 104048254 ppf: 393 ppct: 11 formats: fmt: @attributes: type: P tig: atl: Extended Gabor approach applied to classification of emphysematous patterns in computed tomography. aug: au: Nava, Rodrigo Escalante-Ramírez, Boris Cristóbal, Gabriel Estépar, Raúl San José affil: Posgrado en Ciencia e Ingeniería de la Computación, Universidad Nacional Autónoma de México, Mexico City, Mexico, uriel.nava@gmail.com. sug: subj: Algorithms Emphysema Diagnosis Emphysema Radiography Radiographic Image Interpretation, Computer-Assisted Methods Tomography, X-Ray Computed Methods Discriminant Analysis Human Reproducibility of Results ab: Chronic obstructive pulmonary disease (COPD) is a progressive and irreversible lung condition typically related to emphysema. It hinders air from passing through airpaths and causes that alveolar sacs lose their elastic quality. Findings of COPD may be manifested in a variety of computed tomography (CT) studies. Nevertheless, visual assessment of CT images is time-consuming and depends on trained observers. Hence, a reliable computer-aided diagnosis system would be useful to reduce time and inter-evaluator variability. In this paper, we propose a new emphysema classification framework based on complex Gabor filters and local binary patterns. This approach simultaneously encodes global characteristics and local information to describe emphysema morphology in CT images. Kernel Fisher analysis was used to reduce dimensionality and to find the most discriminant nonlinear boundaries among classes. Finally, classification was performed using the k-nearest neighbor classifier. The results have shown the effectiveness of our approach for quantifying lesions due to emphysema and that the combination of descriptors yields to a better classification performance. pubtype: Academic Journal doctype: research Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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