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Thalur-coloue-suggesatial
- by traditional level set based segmentation models. In this paper, we propose a new level set method integrating local and global intensity information adaptively to segment inhomogeneous images. The local image information is associated with the
Imasas
- Image segmentation is among the most studied problems in image understanding and computer vision. The goal of image segmentation is to partition the image plane into a set of meaningful regions. Here meaningful typically refers to a semantic part
imadder-lumend-compl
- image analysis, since thickening of the bladder wall can indicate abnormality. However, it is a challenging task due to the artifacts inside bladder lumen, weak boundaries in the apex and base areas, and complicated outside intensity distributi
thmogenr
- resonance imaging (MRI) data and estimation of intensity inhomogeneities using fuzzy logic. MRI intensity inhomogeneities can be attributed to imperfections in the radio-frequency coils or to problems associated with the acquisition sequences
easourfd
- that arises the surface coil array. This entropy-based method does not require classification and robustly addresses some problems that are more severe than those found in brain imaging, including noise, steep bias field, sensitivity of arter
Pulialroximndi
- Pulse coupled neural network (PCNN) has a specific feature that the fire of one neuron ca pture its adjacent neurons to fire due to their spatial proximity and intensity similarity. In this paper, it is indicated that this feature itself is a ver