Literature DB >> 15376596

RAGS: Region-aided Geometric Snake.

Xianghua Xie1, Majid Mirmehdi.   

Abstract

An enhanced, region-aided, geometric active contour that is more tolerant toward weak edges and noise in images is introduced. The proposed method integrates gradient flow forces with region constraints, composed of image region vector flow forces obtained through the diffusion of the region segmentation map. We refer to this as the Region-aided Geometric Snake or RAGS. The diffused region forces can be generated from any reliable region segmentation technique, greylevel or color. This extra region force gives the snake a global complementary view of the boundary information within the image which, along with the local gradient flow, helps detect fuzzy boundaries and overcome noisy regions. The partial differential equation (PDE) resulting from this integration of image gradient flow and diffused region flow is implemented using a level set approach. We present various examples and also evaluate and compare the performance of RAGS on weak boundaries and noisy images.

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Year:  2004        PMID: 15376596     DOI: 10.1109/tip.2004.826124

Source DB:  PubMed          Journal:  IEEE Trans Image Process        ISSN: 1057-7149            Impact factor:   10.856


  3 in total

1.  A segmentation method of lung cavities using region aided geometric snakes.

Authors:  Alireza Osareh; Bita Shadgar
Journal:  J Med Syst       Date:  2009-02-06       Impact factor: 4.460

2.  A Novel Gradient Vector Flow Snake Model Based on Convex Function for Infrared Image Segmentation.

Authors:  Rui Zhang; Shiping Zhu; Qin Zhou
Journal:  Sensors (Basel)       Date:  2016-10-21       Impact factor: 3.576

3.  A novel approach to segment and classify regional lymph nodes on computed tomography images.

Authors:  Hongmin Cai; Chunyan Cui; Haiying Tian; Min Zhang; Li Li
Journal:  Comput Math Methods Med       Date:  2012-10-31       Impact factor: 2.238

  3 in total

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