论文标题
人颞骨CT图像的基于半圆形管分割的侧向半圆形分割的几何校准
A lateral semicircular canal segmentation based geometric calibration for human temporal bone CT Image
论文作者
论文摘要
颞骨的计算机断层扫描（CT）已成为诊断耳病的重要方法。由于受试者的姿势不同和CT扫描仪的设置，应对人颞骨的CT图像进行几何校准，以确保双侧解剖结构的对称性。对于放射科医生来说，手动校准是一项耗时的任务，也是进一步的计算机辅助CT分析的重要预处理步骤。我们提出了一种用于颞骨CT图像的自动校准算法。首先将侧半圆形管（LSC）分割为锚。然后，我们定义一个标准的3D坐标系。关键步骤是LSC分割。我们设计了一个新颖的3D LSC分割编码器网络，该网络引入了3D扩张的卷积和一个多功能方案，用于在编码阶段进行特征融合。实验结果表明，我们的LSC分割网络达到了更高的分割精度。我们提出的方法可以有助于对颞骨CT图像进行校准。
Computed Tomography (CT) of the temporal bone has become an important method for diagnosing ear diseases. Due to the different posture of the subject and the settings of CT scanners, the CT image of the human temporal bone should be geometrically calibrated to ensure the symmetry of the bilateral anatomical structure. Manual calibration is a time-consuming task for radiologists and an important pre-processing step for further computer-aided CT analysis. We propose an automatic calibration algorithm for temporal bone CT images. The lateral semicircular canals (LSCs) are segmented as anchors at first. Then, we define a standard 3D coordinate system. The key step is the LSC segmentation. We design a novel 3D LSC segmentation encoder-decoder network, which introduces a 3D dilated convolution and a multi-pooling scheme for feature fusion in the encoding stage. The experimental results show that our LSC segmentation network achieved a higher segmentation accuracy. Our proposed method can help to perform calibration of temporal bone CT images efficiently.
