Introduction - If you have any usage issues, please Google them yourself
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 distributions.
To deal with these difficulties, in this paper, an adaptive shape
prior constrained directional level set model is proposed to segment
the inner and outer boundaries of the bladder wall. In addition,
a coupled directional level set model is presented to refine
the segmentation by exploiting the prior knowledge of region information
and minimum thickness. With our proposed method,
the influence of the artifacts in the bladder lumen and the complicated
outside tissues surrounding the bladder can be appreciably
reduced