J Med Syst - Manual refinement system for graph-based segmentation results in the medical domain.

Tópicos

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{ result(1111) use(1088) new(759) }
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Resumo

The basic principle of graph-based approaches for image segmentation is to interpret an image as a graph, where the nodes of the graph represent 2D pixels or 3D voxels of the image. The weighted edges of the graph are obtained by intensity differences in the image. Once the graph is constructed, the minimal cost closed set on the graph can be computed via a polynomial time s-t cut, dividing the graph into two parts: the object and the background. However, no segmentation method provides perfect results, so additional manual editing is required, especially in the sensitive field of medical image processing. In this study, we present a manual refinement method that takes advantage of the basic design of graph-based image segmentation algorithms. Our approach restricts a graph-cut by using additional user-defined seed points to set up fixed nodes in the graph. The advantage is that manual edits can be integrated intuitively and quickly into the segmentation result of a graph-based approach. The method can be applied to both 2D and 3D objects that have to be segmented. Experimental results for synthetic and real images are presented to demonstrate the feasibility of our approach.

Resumo Limpo

basic principl graphbas approach imag segment interpret imag graph node graph repres d pixel d voxel imag weight edg graph obtain intens differ imag graph construct minim cost close set graph can comput via polynomi time st cut divid graph two part object background howev segment method provid perfect result addit manual edit requir especi sensit field medic imag process studi present manual refin method take advantag basic design graphbas imag segment algorithm approach restrict graphcut use addit userdefin seed point set fix node graph advantag manual edit can integr intuit quick segment result graphbas approach method can appli d d object segment experiment result synthet real imag present demonstr feasibl approach

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