Meiburger Kristen M, Molinari Filippo, Zeng Guang, Saba Luca, Suri Jasjit S
BioLab, Department of Electronics, Politecnico di Torino, Torino, Italy.
Annu Int Conf IEEE Eng Med Biol Soc. 2011;2011:575-8. doi: 10.1109/IEMBS.2011.6090107.
This paper presents a completely user-independent algorithm, that automatically extracts the far (distal) double line (lumen-intima and media-adventitia) in the carotid artery using an Edge Flow technique (a class of AtheroEdge™ systems) based on directional probability maps using the attributes of intensity and texture. The extracted double line translates into a measure of the intima-media thickness (IMT), a validated marker for the progression of atherosclerosis. The Carotid Automated Double Line Extraction System based on Edge-Flow (CADLES-EF) is characterized and validated by comparing the output of the algorithm with two other completely automatic techniques (CALEXia and CULEXsa) published by the same authors. Validation was performed on a multi-institutional database of 300 longitudinal B-mode carotid images with normal and pathologic arteries. CADLES-EF showed an intima-media thickness (IMT) bias of 0.043 ± 0.097 mm in comparison to CALEXia and CULEXsa that showed 0.134 ± 0.0.88 mm and 0.74 ± 0.092 mm, respectively. The system's Figure of Merit (FoM) showed an improvement when compared to previous automated methods: CALEXia and CULEXsa, leading to values of 84.7%, 91.5%, while our new approach, CADLES-EF performed the best with 94.8%.
本文提出了一种完全独立于用户的算法,该算法使用基于方向概率图的边缘流技术(一类AtheroEdge™系统),利用强度和纹理属性,自动提取颈动脉中的远(远端)双线(管腔-内膜和中膜-外膜)。提取的双线转化为内膜-中膜厚度(IMT)的测量值,这是动脉粥样硬化进展的一个经过验证的标志物。基于边缘流的颈动脉自动双线提取系统(CADLES-EF)通过将算法输出与同一作者发表的其他两种完全自动技术(CALEXia和CULEXsa)进行比较来进行特征描述和验证。在一个包含300张正常和病理动脉纵向B模式颈动脉图像的多机构数据库上进行了验证。与CALEXia和CULEXsa相比,CADLES-EF显示的内膜-中膜厚度(IMT)偏差分别为0.043±0.097mm,而CALEXia和CULEXsa分别为0.134±0.088mm和0.74±0.092mm。与之前的自动方法CALEXia和CULEXsa相比,该系统的品质因数(FoM)有所提高,分别为84.7%、91.5%,而我们的新方法CADLES-EF表现最佳,为94.8%。