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dc.contributor.authorHanbay, K. and Talu, M.F.
dc.date.accessioned2021-04-08T12:07:31Z
dc.date.available2021-04-08T12:07:31Z
dc.date.issued2018
dc.identifier10.1016/j.camwa.2018.01.033
dc.identifier.issn08981221
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85045266304&doi=10.1016%2fj.camwa.2018.01.033&partnerID=40&md5=e09d3fe5651ea7115ecbeaddc75f14b9
dc.identifier.urihttp://acikerisim.bingol.edu.tr/handle/20.500.12898/4352
dc.description.abstractThis paper presents a new level set formulation for active contour models (ACM). We propose the idea of integrating the eigenvalue information of Hessian matrix into the level set function. By this new level set function, the principal curvature information of images is used to enhance the ability of segmenting boundary regions. The advantages of our model are as follows: firstly, the interior and exterior object boundaries can be segmented with the initial contour being anywhere in the input image. Secondly, this method can work with heterogeneous images. Thirdly, the proposed model can produce smooth and right boundaries of objects having vital importance in medical operations. Extensive experiments demonstrate that the proposed model can obtain better segmentation results. © 2018 Elsevier Ltd
dc.language.isoEnglish
dc.sourceComputers and Mathematics with Applications
dc.titleA novel active contour model for medical images via the Hessian matrix and eigenvalues


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