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Early Detection, Segmentation Quantification of Coronary Artery Blockage Using Efficient Image Processing Technique

机译:使用高效图像处理技术对冠状动脉阻塞进行早期检测,分割和量化

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The proposed method aims towards a full automation of the detection of coronary artery blockage through image processing techniques so that the system does not have to rely on human's inspection. The goal of the research is to implement the proposed image processing techniques so the system can detect the narrowing area of the wall of coronary arteries due to the condensation of different artery blocking agents. The research suggests that the system will require a 64-slice CTA image as input. After the acquisition of the desired input image, it will go through several steps to determine the region of interest. This research proposes a two stage approach that includes the pre-processing stage and decision stage. The pre-processing stage involves common image processing strategies while the decision stage involves the extraction and calculation of two feature ratios to finally determine the intended result. Moreover, in order to get more insights of the subject of these examinations, this research enables creating a 3-D model.
机译:所提出的方法旨在通过图像处理技术实现对冠状动脉阻塞的完全自动化检测,从而使系统不必依靠人工检查。该研究的目的是实施所提出的图像处理技术,以便该系统能够检测由于不同的动脉阻滞剂的凝结而引起的冠状动脉壁狭窄区域。研究表明,该系统将需要64层CTA图像作为输入。在获取所需的输入图像后,它将经过几个步骤来确定感兴趣的区域。这项研究提出了一种包括预处理阶段和决策阶段的两阶段方法。预处理阶段涉及常见的图像处理策略,而决策阶段涉及对两个特征比率的提取和计算,以最终确定预期结果。此外,为了对这些考试的主题有更多的了解,这项研究可以创建3-D模型。

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