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首页> 外文会议>International Workshop on Computer Vision for Biomedical Image Applications(CVBIA 2005); 20051021; Beijing(CN) >Fast 3D Brain Segmentation Using Dual-Front Active Contours with Optional User-Interaction
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Fast 3D Brain Segmentation Using Dual-Front Active Contours with Optional User-Interaction

机译：使用带有可选用户交互功能的双前活动轮廓进行快速3D脑分割

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摘要

Important attributes of 3D brain segmentation algorithms include robustness, accuracy, computational efficiency, and facilitation of user interaction, yet few algorithms incorporate all of these traits. Manual segmentation is highly accurate but tedious and laborious. Most automatic techniques, while less demanding on the user, are much less accurate. It would be useful to employ a fast automatic segmentation procedure to do most of the work but still allow an expert user to interactively guide the segmentation to ensure an accurate final result. We propose a novel 3D brain cortex segmentation procedure utilizing dual-front active contours, which minimize image-based energies in a manner that yields more global minimizers compared to standard active contours. The resulting scheme is not only more robust but much faster and allows the user to guide the final segmentation through simple mouse clicks which add extra seed points. Due to the global nature of the evolution model, single mouse clicks yield corrections to the segmentation that extend far beyond their initial locations, thus minimizing the user effort. Results on 15 simulated and 20 real 3D brain images demonstrate the robustness, accuracy, and speed of our scheme compared with other methods.
机译：3D大脑分割算法的重要属性包括健壮性，准确性，计算效率和用户交互便利性，但是很少有算法能够融合所有这些特征。手动分割非常准确，但繁琐且费力。大多数自动技术虽然对用户的要求不高，但准确性却低得多。采用快速的自动分割程序来完成大部分工作会很有用，但仍然允许专家用户交互式地指导分割以确保准确的最终结果。我们提出了一种利用双前活动轮廓的新颖3D脑皮质分割程序，该方法以与标准活动轮廓相比产生更多全局最小化器的方式最小化了基于图像的能量。所得方案不仅更鲁棒，而且速度更快，并且允许用户通过简单的鼠标单击来引导最终的细分，从而增加额外的种子点。由于演化模型的全局性质，单次单击鼠标即可产生对细分的更正，该细分远远超出了其初始位置，从而最大程度地减少了用户的工作量。与其他方法相比，在15张模拟和20张真实3D大脑图像上的结果证明了我们的方案的鲁棒性，准确性和速度。

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