基于CTA影像的头部骨骼组织提取

发布时间：2018-04-29 21:07

  本文选题：骨骼提取 + 三维分割　； 参考：《东北大学》2013年硕士论文

【摘要】：随着我国的快速发展,国民对健康生活的渴望也日渐增强。心脑血管疾病是当今人类的严重威胁之一,50岁以上中老年人更是心脑血管疾病的高发人群。我国每年有近300万人死于心脑血管疾病,占我国每年总死亡病因的51%。因此,对心脑血管疾病的早期诊断和准确诊断成为近代医学研究的一个重要课题。计算机断层造影(CTA),在医学上又叫非创伤性血管成像技术,现在已经成为诊断心脑血管疾病的一种重要方法,尤其在介入治疗中起着不可替代的作用。本文旨在更加精确更加快速地分离提取出头部骨骼组织和独立的下颌骨结构,辅助医生进行更准确的诊断。本文首先,根据人体生理特征和头部医学影像的特点,提出了医学影像预处理算法和特征区域骨骼统计头部分层算法。医学影像预处理算法可以有效地去除医学影像中的无关部分,并保留影像中有用的人体部分。特征区域骨骼统计头部分层算法可以将复杂的头部数据分成三个部分,使得针对不同部位的诊断可以仅仅只处理与之相对应的数据集,有效地减少了数据处理量。其次,本文提出一种全新的基于区域圆形度、灰度均值和均方差的组织判别方法。提出一种全新的改进的主动轮廓模型,并将它和三维区域生长算法相结合,良好地解决了头部骨骼组织提取问题。然后,通过大量临床数据的实验比较,证明了本文提出的方法优于传统的基于阈值的骨骼分割方法。再后,本文在医学影像理论的基础上提出了谷状结构理论,并以此为依据,进一步提出了关节软骨检测算法,通过该算法,使得不同骨骼的分离问题得以有效地解决。最后,本文创新地设计了下颌骨独立提取算法,并提出自主设计的下颌骨初始种子点快速确定算法和关节软骨检测算法。通过这两个自主创新设计的算法,完美地解决了下颌骨提取问题,并通过大量临床数据实验予以验证。
[Abstract]:With the rapid development of our country, the people's desire for healthy life is also increasing. Cardiovascular and cerebrovascular diseases are one of the serious threats to human beings today. The middle-aged and elderly people over 50 years of age are the high incidence of cardiovascular and cerebrovascular diseases. In our country, nearly 3 million people die from cardiovascular and cerebrovascular diseases each year, accounting for the 51%. of the total death cause of our country every year. Early diagnosis and accurate diagnosis of vascular diseases have become an important subject in modern medical research. Computed tomography (CTA), which is called non traumatic angiography, has now become an important method for the diagnosis of cardiovascular and cerebrovascular diseases, especially in interventional therapy. In this paper, a medical image preprocessing algorithm and a feature region skeleton algorithm are proposed for medical image preprocessing. In order to effectively remove the unrelated parts of medical images and retain the useful part of the image, the feature region skeleton statistics head stratification algorithm can divide the complex head data into three parts, so that the diagnosis of different parts can only deal with the corresponding data set and effectively reduce the amount of data processing. In this paper, a new organizational discrimination method based on regional roundness, gray mean and mean variance is proposed. A new improved active contour model is proposed and combined with three dimensional region growth algorithm to solve the problem of bone tissue extraction in the head. The method proposed in this paper is superior to the traditional threshold based bone segmentation method. After that, this paper puts forward the theory of valley structure on the basis of medical imaging theory. On the basis of this, the joint cartilage detection algorithm is further proposed. Through this algorithm, the separation problem of different bones can be effectively solved. Finally, this paper is innovative. The algorithm of mandible independent extraction is designed, and the algorithm for determining the initial seed point of the mandible is proposed and the articular cartilage detection algorithm is designed independently. Through these two independent innovative design algorithms, the problem of mandible extraction is perfectly solved and verified by a large number of clinical data experiments.

【学位授予单位】：东北大学
【学位级别】：硕士
【学位授予年份】：2013
【分类号】：R816.2;TP391.41
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本文编号：1821549