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Online extraction of lumen region and boundary from endoscopic images using a quad structure

机译:用四边形探测内窥镜图像的腔区域和边界的在线提取

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A new approach for the automatic extraction of the lumen region and its boundary for the gastrointestinal (GI) endoscopic images is presented. At first, a quasi region of interest representing the darker regions of the image is segmented by usinga region splitting scheme named progressive thresholding. Then the lumen region is obtained by using a region growing technique called integrated neighborhood search (INS). A new quad-structure based technique is introduced to enhance the speed of INSsignificantly. A back projection algorithm is suggested to optimise the search for the pixels belonging to the lumen region and boundary. A boundary-thinning algorithm is also proposed to remove the redundant pixels from the lumen boundary and to generate a connected single pixel width boundary. The proposed approach does not need a priori knowledge about the image characteristics. The efficiency of this method in terms of speed and accuracy is validated by various GI images and the results of theexperiments are presented. The main advantage of the proposed technique is its high-speed response that facilitates real time analysis of the endoscopic images.
机译:提出了一种新的腔区域自动提取的新方法及其对胃肠道(GI)内窥镜图像的边界。首先,通过使用名为渐进阈值的区域分割方案来分割代表图像的较暗区域的准感兴趣区域。然后通过使用称为集成邻域搜索(INS)的区域生长技术获得腔区域。引入了一种新的四结构技术,以提高廉价的速度。建议对后投影算法进行优化搜索属于内腔区域和边界的像素。还提出了一种边界化细化算法以从内腔边界移除冗余像素,并产生连接的单像素宽度边界。所提出的方法不需要关于图像特征的先验知识。通过各种GI图像验证了这种方法在速度和精度方面的效率,并呈现了专家的结果。所提出的技术的主要优点是其高速响应,便于对内窥镜图像的实时分析。

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