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自动颅面结构检测在头影测量图像上的应用。

Automatic craniofacial structure detection on cephalometric images.

机构信息

Computational Instrumentation Unit, Central Scientific Instruments Organisation (CSIO), Chandigarh, 160030, India.

出版信息

IEEE Trans Image Process. 2011 Sep;20(9):2606-14. doi: 10.1109/TIP.2011.2131662. Epub 2011 Mar 24.

Abstract

Anatomical structure tracing on cephalograms is a significant way to obtain cephalometric analysis. Cephalometric analysis is divided in two categories, manual and automatic approaches. The manual approach is limited in accuracy and repeatability due to differences in inter- and intra-personal marking. In this paper, we have attempted to develop and test a novel method for automatic localization of craniofacial structures based on the detected edges in the region of interest. Before edge detection of the particular region, the region was filtered by adaptive non local filter for noise removal by keeping the edge information undisturbed. According to the gray-scale feature at the different regions of the cephalograms, modified Canny edge detection algorithm for obtaining tissue contour was proposed. With the application of morphological opening and edge linking approaches, an improved bidirectional contour tracing methodology was proposed by an interactive selection of the starting edge pixels, the tracking process searches repetitively for an edge pixel at the neighborhood of previously searched edge pixel to segment images, and then craniofacial structures are obtained. The effectiveness of the algorithm is demonstrated by the preliminary experimental results obtained with the proposed method.

摘要

头影测量片中的解剖结构追踪是获得头影测量分析的重要方法。头影测量分析分为手动和自动两种方法。由于个体之间和个体内部标记的差异,手动方法在准确性和可重复性方面受到限制。在本文中,我们尝试开发并测试了一种基于感兴趣区域中检测到的边缘的自动定位颅面结构的新方法。在进行特定区域的边缘检测之前,通过自适应非局部滤波器对区域进行滤波,以在不干扰边缘信息的情况下去除噪声。根据头影测量片中不同区域的灰度特征,提出了一种改进的 Canny 边缘检测算法,用于获取组织轮廓。通过形态学开运算和边缘连接方法的应用,提出了一种改进的双向轮廓跟踪方法,通过交互式选择起始边缘像素进行跟踪过程,在先前搜索的边缘像素的邻域中重复搜索边缘像素,以分割图像,然后获取颅面结构。通过使用所提出的方法获得的初步实验结果证明了该算法的有效性。

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