文件名称:Tper prentod
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- 图形图像处理(光照,映射..)
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- [PDF]
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- 2017-09-28
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- 2.33mb
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This paper presents a novel active contour model in a variational level set formulation for simultaneous segmentation and
bias field estimation of medical images. An energy function is formulated based on improved Kullback-Leibler distance (KLD)
with likelihood ratio. According to the additive model of images with intensity inhomogeneity, we characterize the statistics of
image intensities belonging to each different object in local regions as Gaussian distributions with different means and variances.
Then, we use the Gaussian distribution with bias field as a local region descr iptor in level set formulation for segmentation(This paper presents a novel active contour model in a variational level set formulation for simultaneous segmentation and
bias field estimation of medical images. An energy function is formulated based on improved Kullback-Leibler distance (KLD)
with likelihood ratio. According to the additive model of images with intensity inhomogeneity, we characterize the statistics of
image intensities belonging to each different object in local regions as Gaussian distributions with different means and variances.
Then, we use the Gaussian distribution with bias field as a local region descr iptor in level set formulation for segmentation and
bias field correction of the images with inhomogeneous intensities. Therefore, image segmentation and bias field estimation are
simultaneously achieved by minimizing the level set formulation)
bias field estimation of medical images. An energy function is formulated based on improved Kullback-Leibler distance (KLD)
with likelihood ratio. According to the additive model of images with intensity inhomogeneity, we characterize the statistics of
image intensities belonging to each different object in local regions as Gaussian distributions with different means and variances.
Then, we use the Gaussian distribution with bias field as a local region descr iptor in level set formulation for segmentation(This paper presents a novel active contour model in a variational level set formulation for simultaneous segmentation and
bias field estimation of medical images. An energy function is formulated based on improved Kullback-Leibler distance (KLD)
with likelihood ratio. According to the additive model of images with intensity inhomogeneity, we characterize the statistics of
image intensities belonging to each different object in local regions as Gaussian distributions with different means and variances.
Then, we use the Gaussian distribution with bias field as a local region descr iptor in level set formulation for segmentation and
bias field correction of the images with inhomogeneous intensities. Therefore, image segmentation and bias field estimation are
simultaneously achieved by minimizing the level set formulation)
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jiang2014.pdf