NDLI: Active Contour Method with Locally Computed Signed Pressure Force Function: An Application to Brain MR Image Segmentation

Content Provider	IEEE Xplore Digital Library
Author	Akram, F. Jeong Heon Kim Kwang Nam Choi
Copyright Year	2013
Description	Author affiliation: Global Sci. Exp. Data Hub Center, Korea Inst. of Sci. & Technol. Inf., Daejeon, South Korea (Jeong Heon Kim) \|\| Dept. of Comput. Sci. & Eng., Chung-Ang Univ., Seoul, South Korea (Akram, F.; Kwang Nam Choi)
Abstract	This paper presents a region-based active contour method that embeds both region and gradient information. In the proposed algorithm area term practices a new region-based signed pressure force (SPF) function which utilizes the image local information obtained using the local binary fitted (LBF) energy model. By introducing the SPF function based on local fitted image (LFI), the proposed model is able to segment images with intensity in homogeneities. A Gaussian kernel is used to regularize the level set function which not only regularizes it but also removes the need of computationally expensive re-initialization. The proposed segmentation algorithm is applied to synthetic and real images in order to demonstrate the accuracy, effectiveness, and robustness of the algorithm.
Starting Page	154
Ending Page	159
File Size	760129
Page Count	6
File Format	PDF
ISBN	9780769550503
DOI	10.1109/ICIG.2013.37
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-07-26
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Image segmentation Image edge detection Level set Computational modeling active contour method local binary fitted local image fitted Nonhomogeneous media Brain modeling segmentation SPF function Active contours
Content Type	Text
Resource Type	Article

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