Faculty, Computer Science and Engineering, Manipal Institute of Technology, Manipal University, Manipal, 576104, India.
Faculty, Biomedical Engineering, Manipal Institute of Technology, Manipal University, Manipal, 576104, India.
Int J Comput Assist Radiol Surg. 2017 Nov;12(11):1845-1855. doi: 10.1007/s11548-017-1615-4. Epub 2017 Jun 1.
Automated measurement of the size and shape of colon polyps is one of the challenges in Computed tomography colonography (CTC). The objective of this retrospective study was to improve the sensitivity and specificity of smaller polyp measurement in CTC using image processing techniques.
A domain knowledge-based method has been implemented with hybrid method of colon segmentation, morphological image processing operators for detecting the colonic structures, and the decision-making system for delineating the smaller polyp-based on a priori knowledge.
The method was applied on 45 CTC dataset. The key finding was that the smaller polyps were accurately measured. In addition to 6-9 mm range, polyps of even <5 mm were also detected. The results were validated qualitatively and quantitatively using both 2D MPR and 3D view. Implementation was done on a high-performance computer with parallel processing. It takes [Formula: see text] min for measuring the smaller polyp in a dataset of 500 CTC images. With this method, [Formula: see text] and [Formula: see text] were achieved.
The domain-based approach with morphological image processing has given good results. The smaller polyps were measured accurately which helps in making right clinical decisions. Qualitatively and quantitatively the results were acceptable when compared to the ground truth at [Formula: see text].
在计算机断层结肠成像术（CTC）中，结肠息肉大小和形状的自动测量是一个挑战。本回顾性研究的目的是使用图像处理技术提高 CTC 中小息肉测量的灵敏度和特异性。
实现了一种基于领域知识的方法，采用结肠分割的混合方法、用于检测结肠结构的形态图像处理运算符，以及基于先验知识的较小息肉的决策系统。
该方法应用于 45 个 CTC 数据集。主要发现是能够准确测量较小的息肉。除了 6-9mm 范围外，甚至 <5mm 的息肉也被检测到。使用 2D MPR 和 3D 视图对结果进行了定性和定量验证。在具有并行处理的高性能计算机上进行了实现。在 500 个 CTC 图像的数据集上测量较小息肉需要 [Formula: see text] 分钟。使用这种方法，实现了 [Formula: see text] 和 [Formula: see text]。
基于形态图像处理的基于领域的方法取得了良好的效果。能够准确测量较小的息肉，有助于做出正确的临床决策。与 [Formula: see text] 处的地面实况相比，定性和定量结果是可以接受的。
