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Segmentation of hand radiographs using fast marching methods

机译:使用快速行进方法分割手射线照片

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Rheumatoid Arthritis is one of the most common chronic diseases. Joint space width in hand radiographs is evaluated to assess joint damage in order to monitor progression of disease and response to treatment. Manual measurement of joint space width is time-consuming and highly prone to inter- and intra-observer variation. We propose a method for automatic extraction of finger bone boundaries using fast marching methods for quantitative evaluation of joint space width. The proposed algorithm includes two stages: location of hand joints followed by extraction of bone boundaries. By setting the propagation speed of the wave front as a function of image intensity values, the fast marching algorithm extracts the skeleton of the hands, in which each branch corresponds to a finger. The finger joint locations are then determined by using the image gradients along the skeletal branches. In order to extract bone boundaries at joints, the gradient magnitudes are utilized for setting the propagation speed, and the gradient phases are used for discriminating the boundaries of adjacent bones. The bone boundaries are detected by searching for the fastest paths from one side of each joint to the other side. Finally, joint space width is computed based on the extracted upper and lower bone boundaries. The algorithm was evaluated on a test set of 8 two-hand radiographs, including images from healthy patients and from patients suffering from arthritis, gout and psoriasis. Using our method, 97% of 208 joints were accurately located and 89% of 416 bone boundaries were correctly extracted.
机译:类风湿关节炎是最常见的慢性疾病之一。在X光片手关节间隙宽度进行评估,以评估,以便监测疾病和治疗反应的进展关节损伤。关节间隙宽度的手工测量是耗时且极易之间和内部观察员变化。我们建议使用联合空间宽度的定量评价快速行进算法手指骨边界进行自动提取的方法。该算法包括两个阶段:手关节的位置,随后骨边界提取。通过设置波前作为图像强度值的函数的传播速度,快速行进算法提取手的骨架,其中每个分支对应于手指。指关节位置然后通过使用图像梯度沿骨架的分支来确定。为了在接头处提取骨边界,梯度强度被用于设置的传播速度,并且梯度相位被用于识别相邻骨的边界。骨边界由搜索来自每个关节的一侧到另一侧的最快路径检测。最后,关节间隙宽度基于所提取的上和下边界骨计算。该算法在试验组8个双手握X光片,包括来自健康患者的图像和来自关节炎,痛风和牛皮癣的患者评价。使用我们的方法,208个关节的97%都准确地定位和416个骨边界89%被正确地提取。

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