基于三维CT图像肠区域分割的肠可视化辅助肠梗阻诊断
Visualizing intestines for diagnostic assistance of ileus based on intestinal region segmentation from 3D CT images
摘要：
本文提出了一种肠（小肠和大肠）区域及其狭窄部分的肠梗阻引起的CT体积的可视化方法。由于非专业临床医生很难找到狭窄部位，因此应直观地显示肠道及其狭窄部位。此外，肠梗阻病例的肠区域很难分割。该方法利用3D FCN（3D U-Net）分割肠道区域。肠区域在肠梗阻病例中很难分割，因为肠内充满了液体。这些液体在3D CT体积上具有与肠壁相似的强度。我们使用弱注释方法训练的3D U-Net分割肠道区域。弱注释使得可以使用肠的小的手动跟踪标签图像来训练3D U-Net。这就避免了我们为长而弯曲的肠准备许多注释标签。对每个肠段进行体绘制，并根据体绘制中与其端点的距离对其进行着色。狭窄部分（肠段的分离点）可以在这种可视化上容易地识别。在实验中，我们表明，狭窄的部分直观地可视化为分割区域的端点，用红色或蓝色着色。
英文摘要：
This paper presents a visualization method of intestine (the small and large intestines) regions and their stenosed parts caused by ileus from CT volumes. Since it is difficult for non-expert clinicians to find stenosed parts, the intestine and its stenosed parts should be visualized intuitively. Furthermore, the intestine regions of ileus cases are quite hard to be segmented. The proposed method segments intestine regions by 3D FCN (3D U-Net). Intestine regions are quite difficult to be segmented in ileus cases since the inside the intestine is filled with fluids. These fluids have similar intensities with intestinal wall on 3D CT volumes. We segment the intestine regions by using 3D U-Net trained by a weak annotation approach. Weak-annotation makes possible to train the 3D U-Net with small manually-traced label images of the intestine. This avoids us to prepare many annotation labels of the intestine that has long and winding shape. Each intestine segment is volume-rendered and colored based on the distance from its endpoint in volume rendering. Stenosed parts (disjoint points of an intestine segment) can be easily identified on such visualization. In the experiments, we showed that stenosed parts were intuitively visualized as endpoints of segmented regions, which are colored by red or blue.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
