A geometric model for 3-D confocal image analysis
A geometric model for 3-D confocal image analysis
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DOI：
10.1109/10.887941
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发表时间：
2000-12-01
影响因子：
4.6
通讯作者：
Malladi, R
中科院分区：
文献类型：
--
作者：
Sarti, A;de Solórzano, CO;Malladi, R
本文采用基于偏微分方程的滤波作为计算机辅助细胞学的前处理加后处理策略，希望能够准确地提取和分类细胞学细胞。这是对组织和培养标本进行准确的核内(基因型别和表型)和核间(组织结构)定量分析的先决条件。首先，我们研究了在核分割之前使用一种几何驱动的边缘保持图像平滑机制。我们展示了该比特如何优于其他广泛使用的滤波器，因为它提供更高的边缘保真度。然后，我们应用相同的过滤器，在不同的初始条件下，对核表面进行平滑处理，获得亚像素精度。最后，我们使用几何过滤器的另一个实例来纠正分割算法对核表面的误解。我们的前滤波和后滤波很好地补充了我们最初的分割策略，因为它在核表面的清晰度方面提供了实质性和可测量的改进。
In this paper, we use partial-differential-equation-based filtering as a preprocessing add post processing strategy for computer-aided cytology, We wish to accurately extract and classify. the shapes of nuclei from confocal microscopy images, which is a prerequisite to an accurate quantitative intranuclear (genotypic and phenotypic) and internuclear (tissue structure) analysis of tissue and cultured specimens. First, we study the use of a geometry-driven edge-preserving image smoothing mechanism before nuclear segmentation. We show how this biter outperforms other widely-used filters in that it provides higher edge fidelity. Then we apply the same filter,,vith a different initial condition, to smooth nuclear surfaces and obtain sub-pixel accuracy. Finally we use another instance of the geometrical filter to correct for misinterpretations of the nuclear surface by the segmentation algorithm. Our prefiltering and post filtering nicely complements our initial segmentation strategy, in that it provides substantial and measurable improvement in the definition of the nuclear surfaces.