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基于局部特征的医学影像形态分析理论与方法
Alternative TitleTheory and Methods of Local-Feature based Morphometry for Medical Images
王虎
Subtype工学博士
Thesis Advisor张文生
2012-05-30
Degree Grantor中国科学院研究生院
Place of Conferral中国科学院自动化研究所
Degree Discipline模式识别与智能系统
Keyword医学影像 形态分析 个体分类 局部特征 特征提取 Medical Image Morphometric Analysis Individual Classification Local Feature Feature Extraction
Abstract医学影像是现代医学研究和疾病诊断的重要依据。形态分析旨在利用组织结构的高分辨率三维影像和现代信息技术,更加客观、准确地检测与疾病等因素相关的形态特征,用于人体生理机制研究和疾病的计算机辅助诊断。现有形态分析方法大多基于影像间的一一对应假设获取形态单元在所有样本中的模式对应,忽略了多样性组织结构所呈现的多种形态模式,导致影像间出现错误的模式对应。这降低了形态分析结果的准确性,进而制约了形态特征在医学研究和疾病诊断中的应用。 本文重点研究多样性组织结构的形态分析问题。首先,针对多样性组织结构的模式表示,研究三维影像基本模式的局部特征表示方法,综合局部特征的空间位置、尺度和区域纹理信息,对多样性组织结构产生的不同形态模式进行区分。其次,针对三维影像的数据特点和形态分析需求,研究局部特征检测和描述的改进算法,提高局部特征刻画三维影像细节模式的详尽程度和特异性。最后,研究多样性组织结构的形态分析算法,依据准确且有效的模式对应,提高形态分析结果的准确性和可解释性,并结合形态特征和模式分类技术研究疾病诊断。 本文主要工作与贡献如下: (1)在多样性组织结构的模式表示理论方面,依据三维影像样本中的局部特征的空间分布,建立了稳定的模板单元;借助模板单元的特异性,获取影像间的模式对应,克服了多样性组织结构导致的错误对应问题;提出了模式对应的有效性和准确性的度量准则,用于评估模板单元的稳定性,通过排除不稳定模板单元提高了形态分析的可靠性。 (2)在局部特征提取算法方面,提出了基于放宽极值约束的局部特征检测算法,通过放宽离散尺度空间极值约束减少影像噪声的影响,在不降低检测重复率的前提下产生稠密的局部特征集合,实现了对三维影像细节模式更加详尽有效地刻画;提出了基于最大方向导数梯度直方图的局部特征描述算法,通过对三维梯度方向进行均匀同质划分,增加了局部特征的特异性。 (3)在形态分析算法方面,提出了基于稳定模板单元的形态分析算法,实现了对多样性组织结构的分析。首先,使用稠密的局部特征集合和改进的特征匹配算法检测模板单元在各影像样本中的模式对应,降低了传统方法中的影像噪声对模式对应造成的干扰,从而使得模式对应集合更有效地反映多样性组织结构的分布规律;其次,依据模式对应的尺度空间参数提取具有明确含义的形态特征,从而提高了形态分析结果的可解释性。 (4)在临床应用方面,采用华盛顿大学公开的大脑三维影像数据集(OASIS),对阿尔兹海默病(Alzheimer's disease, AD)进行形态分析,并结合形态特征和模式分类技术进行疾病的计算机辅助诊断实验。在具有不同年龄范围和疾病程度的测试集上,与相关研究相比,本文将疾病诊断的准确率平均提高了2.7%,所检测到与AD显著相关的形态特征具有更明确的临床解释。
Other AbstractMedical images are the important basis of modern medical research and disease diagnosis. Morphometric analysis aims to detect and quantify more objective and more accurate morphological features that are related disease and other factors. Morphological features are mainly used for the research of human physiological mechanism and for the computer-aided diagnosis. Existing morphometry methods mostly assume one-to-one correspondence between images in order to identify correspondences of a morphological unit in all samples. This assumption ignores the variety of morphological patterns presented in diverse anatomical structures, resulting in inaccurate correspondences between images. The diversity problem has reduced the accuracy of morphometric analysis, and thus restricting the application of the morphological features in medical research and disease diagnosis. This thesis focuses on the morphometric analysis problem of diverse anatomical structures. Firstly, for the pattern representation of diverse anatomical structures, the thesis studies the representation technology with local features of three-dimensional images. The spatial location, scale and regional texture information of local features are used to distinguish the patterns which are caused by the diversity. Secondly, considering the data characteristics of three-dimensional images and the demands of morphometric analysis, the thesis studies the improved local feature extraction algorithms, in order to enhance the level of detail and distinctiveness of local features for the characterization of localized patterns of three-dimensional images. Finally, the thesis studies the morphometry methods for diverse anatomical structures according to the accurate and effective correspondences, in order to improve the accuracy and interpretability of morphometry results. The morphological features are then combined with pattern classification technology for research of disease diagnosis. The main work and contributions are as follows: (1) In the aspect of pattern representation theory for the diverse anatomical structures, stable template patterns are constructed according to spatial distributions of local features in three-dimensional images. Correspondences between images are identified according to the distinctiveness of template patterns, therefore overcoming the inaccuracy problem from diversity. The measurement criteria for the effectiveness and accuracy of the correspondences are proposed to quantify ...
shelfnumXWLW1745
Other Identifier200918014628053
Language中文
Document Type学位论文
Identifierhttp://ir.ia.ac.cn/handle/173211/6456
Collection毕业生_博士学位论文
Recommended Citation
GB/T 7714
王虎. 基于局部特征的医学影像形态分析理论与方法[D]. 中国科学院自动化研究所. 中国科学院研究生院,2012.
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