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Early and Accurate Model of Malignant Lung Nodule Detection System with Less False Positives BABT
Krishnamurthy,Senthilkumar; Narasimhan,Ganesh; Rengasamy,Umamaheswari.
ABSTRACT The objective of this work is to identify the malignant lung nodules accurately and early with less false positives. ‘Nodule’ is the 3mm to 30mm diameter size tissue clusters present inside the lung parenchyma region. Segmenting such a small nodules from consecutive CT scan slices are a challenging task. In our work Auto-seed clustering based segmentation technique is used to segment all the possible nodule candidates. Efficient shape and texture features (2D and 3D) were computed to eliminate the false nodule candidates. The change in centroid position of nodule candidates from consecutive slices was used as a measure to remove the vessels. The two-stage classifier is used in this work to classify the malignant and benign nodules. First stage...
Tipo: Info:eu-repo/semantics/article Palavras-chave: Lung cancer; 3-D Image Segmentation; 3-D image features; Volume growth; Lung nodule classifier.
Ano: 2018 URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S1516-89132018000100308
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