Kwon Ohjae, Lee Jeongjin, Kim Bohyoung, Shin Juneseuk, Shin Yeong-Gil
School of Computer Science and Engineering, Seoul National University, 1 Gwanak-ro, Gwanak-gu, Seoul 151-742, Republic of Korea.
School of Computer Science and Engineering, Soongsil University, 369 Sangdo-ro, Dongjak-gu, Seoul 156-743, Republic of Korea.
Comput Biol Med. 2017 Mar 1;82:87-99. doi: 10.1016/j.compbiomed.2017.01.020. Epub 2017 Jan 31.
With the recent advances regarding the acquisition and simulation of blood flow data, blood flow visualization has been widely used in medical imaging for the diagnosis and treatment of pathological vessels. In this paper, we present a novel method for the visualization of the blood flow in vascular structures. The vessel inlet or outlet is first identified using the orthogonality metric between the normal vectors of the flow velocity and vessel surface. Then, seed points are generated on the identified inlet or outlet by Poisson disk sampling. Therefore, it is possible to achieve the automatic seeding that leads to a consistent and faster flow depiction by skipping the manual location of a seeding plane for the initiation of the line integration. In addition, the early terminated line integration in the thin curved vessels is resolved through the adaptive application of the tracing direction that is based on the flow direction at each seed point. Based on the observation that blood flow usually follows the vessel track, the representative flowline for each branch is defined by the vessel centerline. Then, the flowlines are rendered through an opacity assignment according to the similarity between their shape and the vessel centerline. Therefore, the flowlines that are similar to the vessel centerline are shown transparently, while the different ones are shown opaquely. Accordingly, the opacity modulation method enables the flowlines with an unusual flow pattern to appear more noticeable, while the visual clutter and line occlusion are minimized. Finally, Hue-Saturation-Value color coding is employed for the simultaneous exhibition of flow attributes such as local speed and residence time. The experiment results show that the proposed technique is suitable for the depiction of the blood flow in vascular structures. The proposed approach is applicable to many kinds of tubular structures with embedded flow information.
随着近期在血流数据采集和模拟方面的进展，血流可视化已在医学成像中广泛用于病理性血管的诊断和治疗。在本文中，我们提出了一种用于可视化血管结构中血流的新方法。首先使用流速法向矢量与血管表面之间的正交性度量来识别血管入口或出口。然后，通过泊松圆盘采样在识别出的入口或出口上生成种子点。因此，通过跳过用于线积分起始的种子平面的手动定位，可以实现自动播种，从而实现一致且更快的血流描绘。此外，通过基于每个种子点处的流动方向自适应应用追踪方向，解决了细弯血管中提前终止的线积分问题。基于血流通常遵循血管轨迹的观察结果，每个分支的代表性流线由血管中心线定义。然后，根据流线形状与血管中心线的相似性通过不透明度分配来渲染流线。因此，与血管中心线相似的流线显示为透明，而不同的流线显示为不透明。相应地，不透明度调制方法使具有异常流动模式的流线显得更明显，同时将视觉混乱和线遮挡降至最低。最后，采用色相 - 饱和度 - 明度颜色编码来同时展示局部速度和停留时间等流动属性。实验结果表明，所提出的技术适用于血管结构中血流的描绘。所提出的方法适用于许多种包含流动信息的管状结构。
