Comput Math Methods Med - Potential lung nodules identification for characterization by variable multistep threshold and shape indices from CT images.

Tópicos

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Resumo

Computed tomography (CT) is an important imaging modality. Physicians, surgeons, and oncologists prefer CT scan for diagnosis of lung cancer. However, some nodules are missed in CT scan. Computer aided diagnosis methods are useful for radiologists for detection of these nodules and early diagnosis of lung cancer. Early detection of malignant nodule is helpful for treatment. Computer aided diagnosis of lung cancer involves lung segmentation, potential nodules identification, features extraction from the potential nodules, and classification of the nodules. In this paper, we are presenting an automatic method for detection and segmentation of lung nodules from CT scan for subsequent features extraction and classification. Contribution of the work is the detection and segmentation of small sized nodules, low and high contrast nodules, nodules attached with vasculature, nodules attached to pleura membrane, and nodules in close vicinity of the diaphragm and lung wall in one-go. The particular techniques of the method are multistep threshold for the nodule detection and shape index threshold for false positive reduction. We used 60 CT scans of "Lung Image Database Consortium-Image Database Resource Initiative" taken by GE medical systems LightSpeed16 scanner as dataset and correctly detected 92% nodules. The results are reproducible.

Resumo Limpo

comput tomographi ct import imag modal physician surgeon oncologist prefer ct scan diagnosi lung cancer howev nodul miss ct scan comput aid diagnosi method use radiologist detect nodul earli diagnosi lung cancer earli detect malign nodul help treatment comput aid diagnosi lung cancer involv lung segment potenti nodul identif featur extract potenti nodul classif nodul paper present automat method detect segment lung nodul ct scan subsequ featur extract classif contribut work detect segment small size nodul low high contrast nodul nodul attach vasculatur nodul attach pleura membran nodul close vicin diaphragm lung wall onego particular techniqu method multistep threshold nodul detect shape index threshold fals posit reduct use ct scan lung imag databas consortiumimag databas resourc initi taken ge medic system lightspe scanner dataset correct detect nodul result reproduc

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