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Clavicle segmentation in chest radiographs

机译：胸部X光片中的锁骨分割

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摘要

Automated delineation of anatomical structures in chest radiographs is difficult due to superimposition of multiple structures. In this work an automated technique to segment the clavicles in posterior-anterior chest radiographs is presented in which three methods are combined. Pixel classification is applied in two stages and separately for the interior, the border and the head of the clavicle. This is used as input for active shape model segmentation. Finally dynamic programming is employed with an optimized cost function that combines appearance information of the interior of the clavicle, the border, the head and shape information derived from the active shape model. The method is compared with a number of previously described methods and with independent human observers on a large database. This database contains both normal and abnormal images and will be made publicly available. The mean contour distance of the proposed method on 249 test images is 1.1 ± 1.6. mm and the intersection over union is 0.86 ± 0.10.
机译：由于多个结构的叠加，很难在胸部X光片中自动描绘解剖结构。在这项工作中，提出了一种自动技术，用于在前后胸片中分割锁骨，其中结合了三种方法。像素分类分为两个阶段，分别应用于锁骨的内部，边界和头部。这用作活动形状模型分割的输入。最后，动态编程被用于优化成本函数，该函数结合了锁骨内部的外观信息，边界，头部和从活动形状模型得出的形状信息。将该方法与许多先前描述的方法以及大型数据库上的独立人工观察者进行了比较。该数据库包含正常图像和异常图像，并将公开提供。该方法在249张测试图像上的平均轮廓距离为1.1±1.6。毫米，联合的交点为0.86±0.10。

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