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应用于计算机断层扫描图像的半自动集成分割方法和轮廓提取

Semi-automatic integrated segmentation approaches and contour extraction applied to computed tomography scan images.

作者信息

Khoodoruth B Dhalila S Y, Rughooputh Harry C S, Lefer Wilfrid

机构信息

Department of Computer Science, University of Pau and Pays de l'Adour, 64012 PauCedex, France.

出版信息

Int J Biomed Imaging. 2008;2008:759354. doi: 10.1155/2008/759354. Epub 2008 Oct 27.

Abstract

We propose to segment two-dimensional CT scans traumatic brain injuries with various methods. These methods are hybrid, feature extraction, level sets, region growing, and watershed which are analysed based upon their parametric and nonparametric arguments. The pixel intensities, gradient magnitude, affinity map, and catchment basins of these methods are validated based upon various constraints evaluations. In this article, we also develop a new methodology for a computational pipeline that uses bilateral filtering, diffusion properties, watershed, and filtering with mathematical morphology operators for the contour extraction of the lesion in the feature available based mainly on the gradient function. The evaluations of the classification of these lesions are very briefly outlined in this context and are being undertaken by pattern recognition in another paper work.

摘要

我们提议用各种方法对二维CT扫描的创伤性脑损伤进行分割。这些方法包括混合法、特征提取法、水平集法、区域生长法和分水岭法,我们将根据其参数和非参数论据对这些方法进行分析。基于各种约束评估,对这些方法的像素强度、梯度幅值、亲和度图和集水盆进行验证。在本文中,我们还开发了一种新的计算流程方法,该方法主要基于梯度函数,利用双边滤波、扩散特性、分水岭法以及使用数学形态学算子进行滤波,从可用特征中提取病变轮廓。在这种背景下,对这些病变分类的评估进行了非常简要的概述,并且在另一篇论文工作中通过模式识别来进行。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4eae/2579322/9002825145fc/IJBI2008-759354.001.jpg

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