Department of Electronics and Communication Engineering, K.S.Rangasamy College of Technology, Tamil Nadu, India.
Department of Electronics and Communication Engineering, Sri Shakthi Institute of Engineering and Technology, Coimbatore, 641 062, India.
J Med Syst. 2018 Jul 9;42(8):154. doi: 10.1007/s10916-018-1001-y.
The measurement of Carotid Intima Media Thickness (IMT) on Common Carotid Artery (CCA) is a principle marker of risk of cardiovascular disease. This paper presents a novel method of using deep Convolutional Neural Network (CNN) for identification and measurement of IMT on the far wall of the artery. The Region of Interest (ROI) is extracted using CNN architecture with 8 layers. 110 subjects are taken for the study. Each subject is recorded with one Right Common Carotid Artery (RCCA) and Left Common Carotid Artery (LCCA) frame resulting in 220 recordings. Patch based segmentation with 2640 patches are given to the training network for ROI localization. Intima Media Complex (IMC) is the area where IMT is measured. This region is extracted after defining the ROI. Keeping in mind the end objective of measurement of IMT values binary threshold with snake algorithm is applied to extract the lumen-intima and media-adventitia boundary. IMT values are measured for 20 cases and mean difference is found to be 0.08 mm.
颈总动脉（CCA）的颈动脉内膜中层厚度（IMT）测量是心血管疾病风险的一个重要标志物。本文提出了一种新的方法，使用深度卷积神经网络（CNN）来识别和测量动脉远壁的 IMT。使用具有 8 层的 CNN 架构提取感兴趣区域（ROI）。研究共纳入 110 例受试者，每位受试者均记录了右颈总动脉（RCCA）和左颈总动脉（LCCA）各一帧图像，共 220 个记录。对 2640 个补丁进行基于补丁的分割，并将其提供给训练网络进行 ROI 定位。IMT 是在定义 ROI 后测量的内中膜复合体（IMC）区域。考虑到测量 IMT 值的最终目标，应用蛇算法的二进制阈值来提取管腔-内膜和中膜-外膜边界。对 20 例患者进行了 IMT 值测量，发现平均差值为 0.08mm。
