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چکیده
This paper presents a coarse-grain approach based on the Weibull E-SD field for segmentation of an object with gray levels appearing in a volume data. The input data is on a 3D structured grid and of the form δ =) , , (k j i v , where δ is some scalar value. In this paper, we consider a voxel as a k k k × × cube, and each voxel is assigned two values: expectancy and standard deviation (E-SD). We use the Weibull noise index to estimate the noise in a voxel, and to obtain more precise E-SD values for each voxel. Our test bed includes synthetic data as well as real volume data from a scanning laser confocal microscope. Analysis of this data all show distinct and defining regions in their E-SD plot. Under the guide of an E-SD plot, we can efficiently segment an object embedded in real and simulated 3D data.
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تاریخ انتشار 2001