Comput Math Methods Med - Segmentation of intensity inhomogeneous brain MR images using active contours.

Tópicos

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Resumo

Segmentation of intensity inhomogeneous regions is a well-known problem in image analysis applications. This paper presents a region-based active contour method for image segmentation, which properly works in the context of intensity inhomogeneity problem. The proposed region-based active contour method embeds both region and gradient information unlike traditional methods. It contains mainly two terms, area and length, in which the area term practices a new region-based signed pressure force (SPF) function, which utilizes mean values from a certain neighborhood using the local binary fitted (LBF) energy model. In turn, the length term uses gradient information. The novelty of our method is to locally compute new SPF function, which uses local mean values and is able to detect boundaries of the homogenous regions. Finally, a truncated Gaussian kernel is used to regularize the level set function, which not only regularizes it but also removes the need of computationally expensive reinitialization. The proposed method targets the segmentation problem of intensity inhomogeneous images and reduces the time complexity among locally computed active contour methods. The experimental results show that the proposed method yields better segmentation result as well as less time complexity compared with the state-of-the-art active contour methods.

Resumo Limpo

segment intens inhomogen region wellknown problem imag analysi applic paper present regionbas activ contour method imag segment proper work context intens inhomogen problem propos regionbas activ contour method emb region gradient inform unlik tradit method contain main two term area length area term practic new regionbas sign pressur forc spf function util mean valu certain neighborhood use local binari fit lbf energi model turn length term use gradient inform novelti method local comput new spf function use local mean valu abl detect boundari homogen region final truncat gaussian kernel use regular level set function regular also remov need comput expens reiniti propos method target segment problem intens inhomogen imag reduc time complex among local comput activ contour method experiment result show propos method yield better segment result well less time complex compar stateoftheart activ contour method

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