【作者】 刘辉；

【导师】 金心宇；

【作者基本信息】 浙江大学 ， 电路与系统， 2015， 硕士

【摘要】 随着医学成像技术迅速发展,医学影像在疾病诊断和治疗中的作用也越来越重要。CT图像三维重建是一种能够提高医生工作效率和诊断准确率的计算机辅助诊断方法,但高剂量CT图像被证明对患者健康具有较大影响,低剂量CT图像在多个检查项目得以广泛应用。然而低剂量CT图像也意味着CT图像序列层间距加大,导致三维重建质量下降。此外,目前CT图像的检索方式较为落后,多为基于固定关键字的检索,图像检索多受限制。而基于语义的CT图像检索能够以贴近人们对图像的理解习惯的方式检索图像,能极大提升CT图像的检索效率,已逐渐成为当前研究热点。本文针对低剂量CT图像三维重建问题,以肝脏CT图像数据为样本,研究了三维重建的主要技术,分别对图像预处理、分割、三维绘制的相关算法进行仿真对比。针对低剂量CT图像层间距大的问题深入研究了CT图像的插值算法,分别从图像配准、点对比配、线性插值三个方面对基于轮廓和形状的CT图像层间插值算法做出改进,改进算法具有更高的插值效率和插值准确率,更加适用于低剂量CT图像的三维重建。本文针对CT图像的检索问题,研究了CT图像语义提取相关技术,采用DICOM元数据语义信息提取和图像底层特征语义映射相结合的方式提取肝脏CT图像语义信息。首先研究了DICOM标准的信息模型以及DICOM图像的解析,并基于此直接提取DICOM元数据语义信息。然后研究了医学图像底层特征提取方法,以及SVM分类器,对比了不同的底层特征以及特征组合对于语义映射的效果,并基于最佳特征组合和SVM分类器获取语义映射模型,获得了较高的映射准确率,较好的解决了肝脏CT图像检索中的语义鸿沟问题。更多还原

【Abstract】 With the rapid development of medical imaging technology, medical imaging is playing a more and more important role in the diagnos and treatment of disease. CT image reconstruction is a computer-aided diagnostic method which can improve efficiency and diagnostic accuracy of the physicians. But high-dose CT imaging are proved to have great impact on the health of patients, so the low-dose CT imaging is widely used in many inspection items. However, the low-dose CT imaging also means that the interval of image sequence would be increased, leading to declining quality of three-dimensional reconstruction. In addition, the current CT images retrieval ways are very backward, most of which are based on definite keywords. CT image retrieval based on semantic is closer to the people’s understanding of images, which can greatly improve the CT images retrieval efficiency, and the CT image retrieval has gradually become the focus of current researches.Aiming at the problem of three dimensional reconstruction with low-dose CT images, this paper studied the main technology in three dimensional reconstruction based on liver CT images, and compared the algorithms of image preprocess, image segmentation and three dimensional rendering through simulation. Aiming at the problem of big image sequence interval in low-dose CT images, this paper studied the interpolation algorithms in-depth, and improved the image interpolation algorithm based shape and profile by image registration, optimizing the point pairs matching process and improving the linear interpolation. The modified interpolation algorithm has higher efficiency and accuracy, which is more suitable for three dimensional reconstruction of low-dose CT images.Aiming at problem of CT image retrieval,this paper studied the related technologies of semantic extraction, and extracted the semantic information of liver CT images by the method of combining extracting semantic information from DICOM files’metadata and mapping image low-level features to semantic information. Firstly, this paper studied the information model of DICOM standard and the method of DICOM files parsing, and extracted semantic information from metadata of DICOM files directly. Secondly, this paper studied the method of extracting low-level features of medical images and SVM classifier, and compared the semantic mapping effects of different low-level features and feature combinations,then obtained the semantic mapping model by the best feature combination and the SVM classifier. This model obtained superior semantic mapping accuracy, which can solve the semantic gap problem.更多还原