Comput Math Methods Med - Detection of pulmonary nodules in CT images based on fuzzy integrated active contour model and hybrid parametric mixture model.

Tópicos

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Resumo

The segmentation and detection of various types of nodules in a Computer-aided detection (CAD) system present various challenges, especially when (1) the nodule is connected to a vessel and they have very similar intensities; (2) the nodule with ground-glass opacity (GGO) characteristic possesses typical weak edges and intensity inhomogeneity, and hence it is difficult to define the boundaries. Traditional segmentation methods may cause problems of boundary leakage and "weak" local minima. This paper deals with the above mentioned problems. An improved detection method which combines a fuzzy integrated active contour model (FIACM)-based segmentation method, a segmentation refinement method based on Parametric Mixture Model (PMM) of juxta-vascular nodules, and a knowledge-based C-SVM (Cost-sensitive Support Vector Machines) classifier, is proposed for detecting various types of pulmonary nodules in computerized tomography (CT) images. Our approach has several novel aspects: (1) In the proposed FIACM model, edge and local region information is incorporated. The fuzzy energy is used as the motivation power for the evolution of the active contour. (2) A hybrid PMM Model of juxta-vascular nodules combining appearance and geometric information is constructed for segmentation refinement of juxta-vascular nodules. Experimental results of detection for pulmonary nodules show desirable performances of the proposed method.

Resumo Limpo

segment detect various type nodul computeraid detect cad system present various challeng especi nodul connect vessel similar intens nodul groundglass opac ggo characterist possess typic weak edg intens inhomogen henc difficult defin boundari tradit segment method may caus problem boundari leakag weak local minima paper deal mention problem improv detect method combin fuzzi integr activ contour model fiacmbas segment method segment refin method base parametr mixtur model pmm juxtavascular nodul knowledgebas csvm costsensit support vector machin classifi propos detect various type pulmonari nodul computer tomographi ct imag approach sever novel aspect propos fiacm model edg local region inform incorpor fuzzi energi use motiv power evolut activ contour hybrid pmm model juxtavascular nodul combin appear geometr inform construct segment refin juxtavascular nodul experiment result detect pulmonari nodul show desir perform propos method

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