Potential Lung Nodules Identification for Characterization by Variable Multistep Threshold and Shape Indices from CT Images

摘要: 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 scan. Computer aided methods useful radiologists detection these early Early malignant nodule helpful treatment. cancer involves segmentation, potential identification, features extraction from the nodules, classification nodules. In this paper, we presenting automatic method segmentation subsequent classification. Contribution work small sized low high contrast attached with vasculature, to pleura membrane, close vicinity diaphragm wall one-go. The particular techniques multistep threshold shape index false positive reduction. We used 60 scans “Lung Image Database Consortium-Image Resource Initiative” taken by GE medical systems LightSpeed16 scanner as dataset correctly detected 92% results reproducible.