Philips Healthcare, Healthcare Informatics, 5680 DA Best, The Netherlands.
IEEE Trans Biomed Eng. 2010 Jun;57(6):1306-17. doi: 10.1109/TBME.2010.2040280. Epub 2010 Feb 17.
A well-known reading pitfall in computed tomography (CT) colonography is posed by artifacts at T-junctions, i.e., locations where air-fluid levels interface with the colon wall. This paper presents a scale-invariant method to determine material fractions in voxels near such T-junctions. The proposed electronic cleansing method particularly improves the segmentation at those locations. The algorithm takes a vector of Gaussian derivatives as input features. The measured features are made invariant to the orientation-dependent apparent scale of the data and normalized in a way to obtain equal noise variance. A so-called parachute model is introduced that maps Gaussian derivatives onto material fractions near T-junctions. Projection of the noisy derivatives onto the model yields improved estimates of the true, underlying feature values. The method is shown to render an accurate representation of the object boundary without artifacts near junctions. Therefore, it enhances the reading of CT colonography in a 3-D display mode.
在计算机断层扫描（CT）结肠成像中，一个众所周知的阅读陷阱是 T 型交界处的伪影，即气液平面与结肠壁交界的位置。本文提出了一种用于确定此类 T 型交界处附近体素中材料分数的尺度不变方法。所提出的电子清洗方法特别改善了这些位置的分割。该算法以一组高斯导数作为输入特征。所测量的特征对数据的与方向相关的明显尺度具有不变性，并以一种获得相等噪声方差的方式进行归一化。引入了一种所谓的降落伞模型，将高斯导数映射到 T 型交界处附近的材料分数。将有噪声的导数投影到模型上，可以得到真实、基础特征值的改进估计。该方法在没有交界处伪影的情况下，能够准确地表示物体边界。因此，它增强了在 3D 显示模式下对 CT 结肠成像的阅读。
