Comput Math Methods Med - A novel adaptive level set segmentation method.

Tópicos

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Resumo

The adaptive distance preserving level set (ADPLS) method is fast and not dependent on the initial contour for the segmentation of images with intensity inhomogeneity, but it often leads to segmentation with compromised accuracy. And the local binary fitting model (LBF) method can achieve segmentation with higher accuracy but with low speed and sensitivity to initial contour placements. In this paper, a novel and adaptive fusing level set method has been presented to combine the desirable properties of these two methods, respectively. In the proposed method, the weights of the ADPLS and LBF are automatically adjusted according to the spatial information of the image. Experimental results show that the comprehensive performance indicators, such as accuracy, speed, and stability, can be significantly improved by using this improved method.

Resumo Limpo

adapt distanc preserv level set adpl method fast depend initi contour segment imag intens inhomogen often lead segment compromis accuraci local binari fit model lbf method can achiev segment higher accuraci low speed sensit initi contour placement paper novel adapt fuse level set method present combin desir properti two method respect propos method weight adpl lbf automat adjust accord spatial inform imag experiment result show comprehens perform indic accuraci speed stabil can signific improv use improv method

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