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Abdominal wall extraction using constrained deformable model and abdominal context

机译:使用受限变形模型和腹部环境提取腹壁

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Information about abdominal wall can be used for many applications from organ segmentation, registration, and surgical simulation. The challenges exist in abdominal wall extraction due to its varieties in shapes, connection to the internal organs and anterior layer edge formed between the muscle and fascia/fatty layer, which may distract the shape model. In this paper we present an approach to the posterior abdominal wall extraction using the shape model and other abdominal context, particularly with the rib-spine bone information and the wall image features. The shape model is constructed based on the training abdominal walls that are delineated manually. After bone information being extracted, the wall shape deforms from the prior shape model using the snake, which is constrained by the bone context and guided by the processed image energy map with the aim of removing distracted image features of anterior abdominal wall and the outer region from the original map. Meanwhile, an overall convex shape is maintained by limiting the angles of the contour points. The proposed approach is tested on abdominal CT data which provides encouraging results.
机译:有关腹壁的信息可用于器官分割,配准和手术模拟等许多应用。由于腹壁形状的多样性,与内脏器官的连接以及在肌肉与筋膜/脂肪层之间形成的前层边缘的多样性,腹壁提取存在挑战,这可能会分散形状模型的注意力。在本文中,我们提出了一种使用形状模型和其他腹部环境(特别是肋骨-脊骨信息和壁图像特征)进行后腹壁提取的方法。基于手动绘制的训练腹壁构造形状模型。提取骨骼信息后,使用蛇将壁形状从先前的形状模型变形,该形状受骨骼上下文约束并由处理后的图像能量图引导,以消除前腹壁和外部区域的分散图像特征从原始地图开始。同时,通过限制轮廓点的角度来保持整体凸形。在腹部CT数据上对提出的方法进行了测试,结果令人鼓舞。

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