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Lung segmentation is often performed as a preprocessing step on chest Computed Tomography (CT) images because it is important for identifying lung diseases in clinical evaluation. Hence, research on lung segmentation has received much attention. Most of the conventional methods need the post-processing just like rolling ball method or morphology method to deal with the juxtapleural lung nodules or...
In content-based image retrieval, understanding the user's needs in the process of retrieval is a challenging task. Relevance feedback (RF) has been proven to be an effective method for integrating the user's knowledge into the retrieval process to eliminate the semantic gap between the high level semantic concept and the low level features of an image. In this paper we present a framework of content-based...
Medical image segmentation is an essential step for most subsequent image analysis tasks. In this paper a hybrid image segmentation algorithm is proposed, which combines the morphological method of watershed and fuzzy c-means (FCM) clustering. A dilation-erosion contrast enhancement approach is used as a preprocessing stage in order to obtain an accurate estimation of the image borders. Then an initial...
An image segmentation approach is presented that merges watershed segmentation regions with the nearest neighbor connecting tree (NNCT). Firstly a dilation-erosion contrast enhancement processing is used as a preprocessing stage to obtain an accurate estimate of the image borders. Then the maker-controlled watershed transform is applied to produce an initial partitioning of the image into primitive...
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