利用随机过程的可变形区域模型应用于超声心动图图像

Proceedings 1992 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Pub Date : 1992-06-15 DOI:10.1109/CVPR.1992.223139

I. Herlin, C. Nguyen, C. Graffigne

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引用次数: 39

摘要

解决了利用灰度、纹理和梯度信息对医疗数据进行初始分割的问题。数学环境是马尔可夫随机场和随机过程。这产生了两个主要优点:自动选择程序参数和人体工程学软件，可用于测试区域的均匀性。该方法应用于超声心动图图像，以分割心脏腔

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A deformable region model using stochastic processes applied to echocardiographic images

The problem of improving an initial segmentation of medical data by making use of gray level, texture, and gradient information is addressed. The mathematical environment is that of Markov random fields and stochastic processes. This yields two major advantages: automatic selection of program parameters and ergonomic software that can be used to test homogeneity properties of regions. The method is applied to echocardiographic images in order to segment cardiac cavities.<>

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Proceedings 1992 IEEE Computer Society Conference on Computer Vision and Pattern Recognition

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