IEEE Trans Med Imaging. 2014 Apr;33(4):861-74. doi: 10.1109/TMI.2013.2296976.
In this paper, we propose a novel approach to landmark-based shape representation that is based on transportation theory, where landmarks are considered as sources and destinations, all possible landmark connections as roads, and established landmark connections as goods transported via these roads. Landmark connections, which are selectively established, are identified through their statistical properties describing the shape of the object of interest, and indicate the least costly roads for transporting goods from sources to destinations. From such a perspective, we introduce three novel shape representations that are combined with an existing landmark detection algorithm based on game theory. To reduce computational complexity, which results from the extension from 2-D to 3-D segmentation, landmark detection is augmented by a concept known in game theory as strategy dominance. The novel shape representations, game-theoretic landmark detection and strategy dominance are combined into a segmentation framework that was evaluated on 3-D computed tomography images of lumbar vertebrae and femoral heads. The best shape representation yielded symmetric surface distance of 0.75 mm and 1.11 mm, and Dice coefficient of 93.6% and 96.2% for lumbar vertebrae and femoral heads, respectively. By applying strategy dominance, the computational costs were further reduced for up to three times.
在本文中，我们提出了一种基于运输理论的新的基于地标形状表示方法，其中地标被视为源和目的地，所有可能的地标连接被视为道路，已建立的地标连接被视为通过这些道路运输的货物。通过描述感兴趣物体形状的统计特性来选择性地建立地标连接，并指示从源到目的地运输货物的最低成本道路。从这个角度出发，我们提出了三种新的形状表示方法，并将其与基于博弈论的现有地标检测算法相结合。为了降低计算复杂度，即从二维扩展到三维分割的结果，地标检测通过博弈论中的策略优势概念得到增强。新的形状表示、博弈论地标检测和策略优势被结合到一个分割框架中，该框架在腰椎和股骨头的三维计算机断层扫描图像上进行了评估。最好的形状表示分别产生了 0.75 毫米和 1.11 毫米的对称表面距离，以及 93.6%和 96.2%的骰子系数。通过应用策略优势，计算成本最高可降低三倍。
