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Tissue characterization from myocardial perfusion and autonomic innervation using MRI and SPECT images in chagas disease

机译:查加斯病中心肌灌注和自主神经的组织表征(使用MRI和SPECT图像)

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Chagas disease is of major clinical relevance, with high incidence.The relation between the myocardial tissue damage, myocardial perfusion and defects in the autonomic innervations is poorly understood. This work proposes the development and application of image analysis methods capable of providing an integrated visualization and analysis of tissue injuries through magnetic resonance imaging (MRI), autonomic innervations and myocardial perfusion, available through photon emission tomography (SPECT). This paper describes and evaluates a method for tissue characterization and quantication. The proposed method is based on segmentation of MRI and registration between MRI images and SPECT images using metaiodobenzylguanidine (MIBG) and 99Tc (m)-methoxy-isobutyl-isonitrile (MIBI). To perform the segmentation of myocardium, we used Geodesic Active Contour. Fibrosis segmentation in MRI images was performed based on the algorithm of maximum Tsallis entropy. Nonrigid registrations was performed based on B-Spline method. Initially, the registration was made between SPECT images using 99Tc (m)-MIBI and MIBG. Then MRI volumes were registered with SPECT images. It is possible to observe regions of brosis and with absence or low synaptic activity comparatively to myocardial perfusion. The relationship of regions of fibrosis and regions with absence of synaptic activity was obtained by Kendall correlation, which provided a correlation coefficient of 0.8788. Thus, the developed tool provides an integrated analysis of information contributing to a better understanding of the relationship between myocardial tissue damage and autonomic innervations injuries caused by Chagas disease.
机译:Chagas疾病是主要的临床相关性,发病率高。自主密验中的心肌组织损伤,心肌灌注和缺陷之间的关系很差。这项工作提出了能够通过光子发射断层扫描(SPECT)提供的通过磁共振成像(MRI),自主神经内容和心肌灌注来提供图像分析方法的显影和应用。本文描述并评估了组织表征和量化的方法。所提出的方法基于MRI的分割和使用富含碘苄基胍(MIBG)和99TC(M) - 甲氧基异丁基 - 异腈(MIBI)的MRI图像和SPECT图像之间的分割。要执行心肌的分割,我们使用了Geodesic Active Contour。基于最大TSAllis熵的算法进行MRI图像中的纤维化分割。基于B样条方法执行非重力注册。最初,使用99TC(m)-mibi和mibg在SPECT图像之间进行注册。然后使用SPECT图像注册MRI卷。可以比较与心肌灌注相比观察斑块的区域和不存在或低突触活动。通过KENDALL相关性获得纤维化区域和不存在突触活性的区域的关系,提供了0.8788的相关系数。因此,开发的工具提供了有助于更好地理解心肌组织损伤与噬菌体疾病引起的自主神经内脏损伤之间关系的信息的综合分析。

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