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126 Segmentation and Classification of Lung Nodule in Chest Radiograph Image
Abstract-Image segmentation plays a vital step in medical image processing. Lung cancer is the largest cause of tumor deaths. Since the nodules are commonly attached to blood vessels, detection of lung nodules is the challenging task .By early detection the lung cancer can be completely recovered. Especially in the case of lung nodule detection Computer Aided Detection (CAD) is effective for the improvement of radiologists? diagnosis. In this paper an efficient lung nodule detection scheme is developed by performing nodule segmentation through Fuzzy C-Means (FCM) and Virtual Dual Energy (VDE). Here the input image is considered as an radiograph image, then the lung is segmented by using Multi segment Active Shape Model (MASM). Finally neural network classifies as a nodule or non-nodule candidates.
Index Terms — Chest Radiography (CXR), Computer Aided Diagnosis (CAD), Fuzzy C-Means (FCM), Virtual Dual Energy (VDE), Multi Segment Active Shape Model (M-ASM).
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International Journal for Trends in Technology & Engineering © 2015 IJTET JOURNAL