Image segmentation and bias correction using local inhomogeneous iNtensity clustering (LINC): A region-based level set method

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• 作者：Chaolu Feng^a ; ^b ; ^c ; ^{fengchl@mail.neu.edu.cn}Author Vitae ; Dazhe Zhao^a ; ^b ; ^cAuthor Vitae ; Min Huang^a ; ^dAuthor Vitae
• 关键词：Level set ; Image segmentation ; Bias correction ; Orthogonal basis function ; Energy minimization
• 刊名：Neurocomputing
• 出版年：2017
• 出版时间：5 January 2017
• 年：2017
• 卷：219
• 期：Complete
• 页码：107-129
• 全文大小：13608 K
• 卷排序：219

文摘

A level set method is proposed for image segmentation and bias correction. The bias field is simulated by linearly combining a given set of basis functions. The proposed method is able to segment images with intensity inhomogeneity. The proposed method is also able to correct the bias field from the image. Experiments demonstrate that our method is also robust to noise and initialization.