Comput Methods Programs Biomed - Automated pulmonary nodule detection based on three-dimensional shape-based feature descriptor.

Tópicos

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{ cancer(2502) breast(956) screen(824) }
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{ method(2212) result(1239) propos(1039) }

Resumo

Computer-aided detection (CAD) can help radiologists to detect pulmonary nodules at an early stage. In pulmonary nodule CAD systems, feature extraction is very important for describing the characteristics of nodule candidates. In this paper, we propose a novel three-dimensional shape-based feature descriptor to detect pulmonary nodules in CT scans. After lung volume segmentation, nodule candidates are detected using multi-scale dot enhancement filtering in the segmented lung volume. Next, we extract feature descriptors from the detected nodule candidates, and these are refined using an iterative wall elimination method. Finally, a support vector machine-based classifier is trained to classify nodules and non-nodules. The performance of the proposed system is evaluated on Lung Image Database Consortium data. The proposed method significantly reduces the number of false positives in nodule candidates. This method achieves 97.5% sensitivity, with only 6.76 false positives per scan.

Resumo Limpo

computeraid detect cad can help radiologist detect pulmonari nodul earli stage pulmonari nodul cad system featur extract import describ characterist nodul candid paper propos novel threedimension shapebas featur descriptor detect pulmonari nodul ct scan lung volum segment nodul candid detect use multiscal dot enhanc filter segment lung volum next extract featur descriptor detect nodul candid refin use iter wall elimin method final support vector machinebas classifi train classifi nodul nonnodul perform propos system evalu lung imag databas consortium data propos method signific reduc number fals posit nodul candid method achiev sensit fals posit per scan

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