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首页> 外文会议>Conference on physiology and function from multidimensional images >Determination of 3D vessel motion from biplane cardiac sequences
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Determination of 3D vessel motion from biplane cardiac sequences

机译：生物血糖心脏序列3D血管运动的测定

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We have developed methods for determining 3D vessel centerlines from biplane image sequences. For dynamic quantities, e.g., vessel motion or flow, the correspondence between points along calculated centerlines must be established. We have developed and compared two techniques for determination of correspondence and of vessel motion during the heart cycle. Clinical biplane image sequences of coronary vascular trees were acquired. After manual indication of vessel points in each image, vessels were tracked, bifurcation points were calculated, and vascular hierarchy was established automatically. The imaging geometry and the 3D vessel centerlines were calculated for each pair of biplane images from the image data alone. The motion vectors for all centerline points were calculated using corresponding points determined by two methods, either as points of nearest approach of the two centerlines or as having the same cumulative arclength from the vessel origin. Corresponding points calculated using the two methods agreed to within 0.3 cm on average. Calculated motion of vessels appeared to agree with motion visible in the images. Relative 3D positions and motion vectors can be calculated reliably with minimal user interaction.
机译：我们已经开发了从双向图像序列确定3D血管中心线的方法。对于动态量，例如血管运动或流动，必须建立沿着计算的中心线点之间的点之间的对应关系。我们已经开发并比较了两种技术来确定心脏周期内的对应和血管运动。获得冠状动脉血管树的临床生物血糖图像序列。在每个图像中手动指示血管点，跟踪血管，计算分叉点，自动建立血管层次。仅针对来自图像数据的每对双向图像计算成像几何和3D血管中心线。使用由两种方法确定的对应点来计算所有中心线点的运动矢量，作为两个中心线的最近方法的点，或者具有与血管来源的相同累积阶段的点。使用两种方法计算的对应点同意平均0.3厘米。计算出的血管运动似乎同意图像中可见的运动。可以通过最小的用户交互可靠地计算相对3D位置和运动矢量。

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