核仁与细胞膜分割的混合轮廓模型

Min Chen, Shengyong Chen, Q. Guan
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引用次数: 4

摘要

区域差分是图像分割领域的核心指导。本文提出了一种新的基于区域的活动轮廓模型,该模型可用于从背景中检测核仁和细胞膜的轮廓。基于区域差异最大原则,利用局部和全局强度信息作为活动等高线模型的驱动力。局部拟合力和全局拟合力保证了局部差异的捕获和全局不同区域的分割。结合局部信息和全局信息的优势,利用能量泛函中局部拟合项和全局拟合项组成的混合拟合力驱动轮廓运动。引入了一个利用梯度信息的策略权重参数来解释局部和全局拟合项如何作为混合拟合力一起工作。实验结果表明,该模型具有良好的核仁分割性能。
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Hybrid Contour Model for Segmentation of Cell Nucleolus and Membranes
Regional difference is the kernel guidance in the area of image segmentation. In this paper, we present a novel region- based active contour model that could be applied to detect the contour of both nucleolus and cell membrane from the background. Both local and global intensity information are used as the driving forces of the active contour model on the principle of maximum regional difference. The local and global fitting forces ensure that local dissimilarities could be captured and global different areas could be segmented respectively. By combining the advantages of local and global information, the motion of contour is driven by the mixed fitting force, which is composed of the local and global fitting term in energy functional. A strategic weight parameter using the gradient information is introduced to explain how the local and global fitting terms work together as the mixed fitting force. Experimental results show desirable performances of our model in segmenting nucleolus.
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