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An automated recognition technique for aorta aneurysm using thoracic multi-slice CT images

机译:一种使用胸部多切片CT图像的主动脉瘤的自动识别技术

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An automated recognition technique was proposed for providing information on such as the skeleton of thoracic aorta, diameter of each cross-section along the skeleton, curvature of it and position of the aneurysm on the aorta using multi-slice CT images. The information was indispensable to design a stent with perfect fitting to the patient's aorta aneurysm region so that the stent kept the original position against the blood stream. The proposed technique was based on the fact that cross-sections of the aorta aneurysm region had deformation from circular shape while those of the normal region had circular shape due to blood pressure. The three-dimensional shape of the aorta was extracted by applying an algorithm Successive Region Growing. Cylinder model fitting well reduced noise and enabled us to detect the deformation with high accuracy. Skeleton and diameter of the aorta were obtained from the resultant fitting circle. The proposed technique was successfully applied to actual 90 slice of patient multi-slice CT data.
机译:提出了一种自动识别技术,用于提供关于诸如胸部主动脉的骨架,沿骨架的骨骼的骨骼,其直径,IT曲率和使用多切片CT图像的主动脉的位置和动脉瘤的位置。这些信息对于设计与患者的主动脉瘤区域完美的支架是必不可少的,使得支架保持原始位置对血流。所提出的技术基于以下事实:主动脉瘤区域的横截面从圆形具有变形,而常规区域的血压具有圆形形状。通过应用算法连续的区域生长来提取主动脉的三维形状。气缸模型拟合噪音降低,使我们能够高精度地检测变形。从所得拟合圆中获得主动脉的骨架和直径。所提出的技术成功应用于实际90片患者多切片CT数据。

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