id: 05980245
dt: a
an: 05980245
au: Liu, Xiaozheng; Liu, Wei; Xu, Yan; Zhou, Yongdi; Zhu, Junming; Peterson,
    Bradley S.; Xu, Dongrong
ti: Segmentation of medical images of different modalities using distance
    weighted C-V model.
so: Liu, Tianming (ed.) et al., Multimodal brain image analysis. First
    international workshop, MBIA 2011, held in conjunction with MICCAI
    2011, Toronto, Canada, September 18, 2011. Proceedings. Berlin:
    Springer (ISBN 978-3-642-24445-2/pbk). Lecture Notes in Computer
    Science 7012, 110-117 (2011).
py: 2011
pu: Berlin: Springer
la: EN
cc: 
ut: 
ci: 
li: doi:10.1007/978-3-642-24446-9_14
ab: Summary: Region-based active contour model (ACM) has been extensively used
    in medical image segmentation and Chan \& Vese’s (C-V) model is one
    of the most popular ACM methods. We propose to incorporate into the C-V
    model a weighting function to take into consideration the fact that
    different locations in an image with differing distances from the
    active contour have differing importance in generating the segmentation
    result, thereby making it a weighted C-V (WC-V) model. The theoretical
    properties of the model and our experiments both demonstrate that the
    proposed WC-V model can significantly reduce the computational cost
    while improve the accuracy of segmentation over the results using the
    C-V model.
rv: