Petkov Simeon, Carrillo Xavier, Radeva Petia, Gatta Carlo
Centre de Visió per Computador, Bellaterra, Spain; Universitat de Barcelona, Barcelona, Spain.
University Hospital "Germans Trias i Pujol", Badalona, Spain.
Comput Med Imaging Graph. 2014 Jun;38(4):296-305. doi: 10.1016/j.compmedimag.2014.01.003. Epub 2014 Jan 31.
X-ray angiography is widely used in cardiac disease diagnosis during or prior to intravascular interventions. The diaphragm motion and the heart beating induce gray-level changes, which are one of the main obstacles in quantitative analysis of myocardial perfusion. In this paper we focus on detecting the diaphragm border in both single images or whole X-ray angiography sequences. We show that the proposed method outperforms state of the art approaches. We extend a previous publicly available data set, adding new ground truth data. We also compose another set of more challenging images, thus having two separate data sets of increasing difficulty. Finally, we show three applications of our method: (1) a strategy to reduce false positives in vessel enhanced images; (2) a digital diaphragm removal algorithm; (3) an improvement in Myocardial Blush Grade semi-automatic estimation.
X射线血管造影术在血管内介入治疗期间或之前的心脏病诊断中被广泛应用。膈肌运动和心脏跳动会引起灰度变化，这是心肌灌注定量分析的主要障碍之一。在本文中，我们专注于在单幅图像或整个X射线血管造影序列中检测膈肌边界。我们表明，所提出的方法优于现有技术方法。我们扩展了先前公开可用的数据集，添加了新的地面真值数据。我们还合成了另一组更具挑战性的图像，从而拥有两个难度逐渐增加的独立数据集。最后，我们展示了我们方法的三个应用：(1) 一种减少血管增强图像中假阳性的策略；(2) 一种数字膈肌去除算法；(3) 心肌造影剂增强等级半自动估计的改进。
