Abstract
The segmentation of medical images is an important step in different applications such as visualization, quantitative analysis and image-guided surgery. Level Set method (LSM) is popular in image segmentation due to its intrinsic features for handling complex shapes and topological changes. In this paper, we present a novel method Level Set evolution (LSNSDR), wherein we propose to use both saliency map and color intensity as region external energy to motivate an initial evolution of level set function (LSF). Herein, a complete comparative quantitative study of the considered approaches was established. The behavior of these approaches was illustrated on real biomedical images from various fields.
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Rouini, A., Larbi, M., Larbi, S. (2022). A New Robust Level Set Segmentation Method Based of New Saliency Driven Region (LSNSDR): Application to Medical Images. In: Senouci, M.R., Boulahia, S.Y., Benatia, M.A. (eds) Advances in Computing Systems and Applications. CSA 2022. Lecture Notes in Networks and Systems, vol 513. Springer, Cham. https://doi.org/10.1007/978-3-031-12097-8_34
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