文件名称:Thimelg
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This study presents a geometric model for
segmentation of ultrasound images. A partial differential
equation based flow is designed in order to achieve a
maximum likelihood segmentation of the target in the
scene. The flow is derived as the steepest descent of an
energy functional taking into account the density
probability distribution of the gray levels of the image as
well as smoothness constraints. To model gray level
behavior of ultrasound images the classic Rayleigh
probability distribution is considered. The steady state of
the flow presents a maximum likelihood
segmentation of ultrasound images. A partial differential
equation based flow is designed in order to achieve a
maximum likelihood segmentation of the target in the
scene. The flow is derived as the steepest descent of an
energy functional taking into account the density
probability distribution of the gray levels of the image as
well as smoothness constraints. To model gray level
behavior of ultrasound images the classic Rayleigh
probability distribution is considered. The steady state of
the flow presents a maximum likelihood
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