用于前列腺轮廓描绘的交互式二元活动轮廓

F. Derraz, L. Peyrodie, A. Taleb-Ahmed, G. Forzy
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引用次数: 1

摘要

我们提出了一个新的交互式分割框架,以描绘前列腺从磁共振图像。首先,通过结合统计和几何形状先验知识,明确地解决了基于快速全局Finsler活动轮廓(FAC)的分割问题。在这样做的过程中,我们能够通过在细分过程中纳入用户反馈来开发更全面的细分方面。此外,一旦前列腺形状被分割,一个代价函数被设计来结合作为用户反馈的局部图像统计和学习到的形状先验。我们提供了实验结果,其中包括几个具有挑战性的临床数据集,以突出该算法稳健处理仰卧/俯卧前列腺分割的能力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Interactive binary active contours for prostate contour delineation
We present a new interactive segmentation framework to delineate the prostate from MR images. We first explicitly address the segmentation problem based on fast globally Finsler Active Contours (FAC) by incorporating both statistical and geometric shape prior knowledge. In doing so, we are able to exploit the more global aspects of segmentation by incorporating user feedback in segmentation process. In addition, once the prostate shape has been segmented, a cost functional is designed to incorporate both the local image statistics as user feedback and the learned shape prior. We provide experimental results, which include several challenging clinical data sets, to highlight the algorithm's capability of robustly handling supine/prone prostate segmentation.
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