基于配准前特征提取的颅脑病变检出方法研究

针对从高分辨率颅脑CT图像中自动检出病变以实现计算机辅助诊断的需求,提出配准前特征提取的方法。该方法的主要特点是在图谱创建过程中使用散布点内插法获得整数点的特征值,而在病变检出时则采用格子点内插法获得非整数点的特征值。相对于配准后的特征提取,配准前的特征提取能够更加准确地描述图像的灰度特征和纹理特征。通过实验验证,基于配准前特征提取的颅脑病变检出方法能够提高病变检出率,提高检测精度,但同时也增加了假阳性率。为了减少假阳性率、进一步提高检测精度,在下一步的工作中要研究基于三维体数据的病变检出方法,同时还需要进一步研究非刚性配准的可逆性。     

良恶性肺小结节CT图像基于灰度共生矩阵10种纹理特征研究

目的 建立多水平模型研究良恶性肺小结节CT图像的灰度共生矩阵纹理特征,更好地描述肺小结节CT图像,达到辅助肺小结节鉴别的目的.方法 对185例2171张肺小结节CT图像基于灰度共生矩阵提取10个纹理特征,拟合多水平统计模型分析良恶性CT图像的纹理特征的差异.结果 在考虑患者水平的基础上能量、惯性矩等8个纹理特征,在良恶性肺小结节的CT图像间的差异有统计学意义.结论 基于灰度共生矩阵的一些纹理特征是反应肺小结节CT图像良恶性的有效特征参量,在一定程度上有助于早期肺癌的鉴别诊断.     

肺癌分形维数特征的研究

目的:探索肺癌图像的纹理分形维数特征.材料与方法:选取得到病理证实的180例病变组织(良性或恶性),在小扫描野高分辨率条件下获取CT图像电子数据,应用盒维数方法计算病变组织纹理的分维数值.结果:良性病变组织分维数值大约在2.35左右,恶性病变其分维数值在2.50以上.结论:分维数值从某种意义上揭示了组织的纹理特征信息,有望通过CT图像的纹理分形维数的分析对肺癌的诊断提供依据.     

一种基于小波变换的配准特征点自动标记算法

以颅脑CT图像为研究对象,提出了一种基于小波变换的自动标记非刚性配准所需对应特征点的算法.这种算法充分考虑了颅脑CT图像的像素点及其临域的纹理特征,通过进行小波变换建立对应于每个像素点的多分辨率小波特征向量,并以小波特征向量间的差异作为判别依据,在目标图像中标记非刚性配准所需的对应特征点.一系列的实验结果表明,这种基于小波变换的算法能够准确地在目标图像中标记出配准所需的对应特征点,可以作为基于特征的非刚性配准对应特征点自动标记的参量之一.     

基于肺部PET/CT图像不同纹理特征的K最近邻分类器

目的对PET/CT图像高维纹理参数进行降维,基于不同纹理参数建立肺结节良恶性的K最近邻(K-nearest neighbor,KNN)分类器,探究最佳建模方法,提高分类的准确率。方法采用回顾性研究的方式,收集52例首都医科大学宣武医院核医学科肺结节患者的PET/CT图像,对图像的感兴趣区域基于Contourlet变换提取灰度共生矩阵的纹理参数。对肺结节PET/CT图像的纹理参数首先采用单因素分析的方法,根据ROC曲线下面积筛选纹理参数,再对其进行主成分分析提取主要成分。基于主成分、根据ROC曲线筛选的纹理及原始纹理分别采用K最近邻分类算法建立肺结节良恶性的分类器,通过正确率、灵敏度、特异度、阳性预测值(positive predictive value,PPV)、阴性预测值(negative predictive value,NPV)、ROC曲线下面积(area under curve,AUC)这些指标评价分类效果。结果 PET/CT图像共提取1344个原始纹理参数,经单因素分析后筛选出89个纹理参数,对筛选后的纹理共提取11个主成分。基于主成分、筛选纹理、原始纹理的分类模型正确率分别为0.614、0.579、0.263;AUC分别为0.645、0.610、0.515。结论在主成分纹理、单因素分析筛选的纹理、原始纹理中,基于主成分纹理建立K最近邻分类器的效果最好。     

基于配准方法的颅脑CT图像病变信息自动提取算法

医学图像中病变信息的计算机自动提取是实现计算机智能辅助诊断的关键与难点,本研究的目的就是提出一个解决该难题的算法,称之为PATHOINFER。该算法的基本过程是首先选择一幅具有代表性的模板图像帆和一系列与其相应的正常图像样奉Mi,利用非刚性配准分别建立表示“正常图像”灰度变化的灰度均值图谱,表示正常变异的统计概率图谱和反映其解剖结构空间关系的分割模板。以实现对“正常图像”的计算机描述。再通过M0与目标图像S的配准,达到“正常图像”与S在空间关系上的一致,然后通过S与“正常图像”的比较,利用模糊逻辑推理,自动检出S中的病变区域,并实现对其病变特征信息的自动提取。实验结果表明,PATHOINFER算法可自动地检出并分割病变区域,并能够自动地提取包括病变发生部位在内的特征信息。实现了计算机智能辅助诊断研究中病变信息自动提取的难胚。     

基于PET/CT图像纹理参数的肺结节诊断模型

目的基于PET/CT融合图像纹理参数建立肺结节良恶性诊断模型,提高肺癌的识别率。方法选取宣武医院核医学科经PET/CT检查的52例肺结节患者,收集其PET/CT影像图像及人口学、影像学信息。以Contourlet变换和灰度共生矩阵相结合的方式,对PET/CT图像的感兴趣区域提取纹理参数。基于所提取的纹理参数建立支持向量机模型,得到每个肺结节良恶性判别结果。为了提高模型的诊断效果,将结节边缘、最大摄取值、有晕征等影像学信息也纳入模型,重新建立支持向量机模型。通过灵敏度、特异度、正确率等指标对模型诊断效果进行评价。结果纹理参数肺结节诊断模型的灵敏度、特异度分别为90.7%、93.5%,纹理参数结合影像学信息的肺结节诊断模型的灵敏度、特异度分别为95.7%、100.0%。结论基于PET/CT图像纹理参数建立的支持向量机模型对良恶性肺结节具有较好的鉴别诊断效果。     

基于纹理统计特征的医学图像颜色映射方法

为提高灰度医学图像颜色增强的有效性和视觉合理性,提出了一种基于纹理统计特征的颜色增强处理方法。此方法的颜色映射机理不是传统的在灰度级和颜色模型间经验性构筑一对一或多对一的映射关系函数,而是借助彩色可视化人体（VHP）解剖断层源图像数据,利用共生矩阵纹理统计特征信息,实现颜色在图像间的传输。实验结果证明了此方法的可行性,高维度、高阶数统计量的运用提高了颜色映射的准确性和有效性。     

解剖学结构方法在基于医学图像内容检索中的应用

基于图像内容的检索content-based Image retrieval，CBIR)在医学领域的应用有着广阔的前景。针对医学图像特点，我们提出基于解剖结构的灰度及纹理特征的医学图像检索方法，CT／MRI图像数据库的检索效果较好。     

分形模型的超声图像纹理分析

采用分形模型对超声图像进行了纹理分析,提出了肝脏超声图像具有分形的特点,结合肝脏两类不同的散射体解释了超声图像的二重分形特性,并对十例正常人、三例肝癌患者、三例肝硬化患者肝脏的临床超声图像计算了分维Ｄ,结果表明分维Ｄ是区分病变的重要特性量。根据分维Ｄ和尺度ε的综合影响,进一步提出纹理分类参数Ｓ作为区分病变的定量指标,实验结果表明参数Ｓ可以有效地区分病变。     

MARS: a mouse atlas registration system based on a planar x-ray projector and an optical camera

This paper introduces a mouse atlas registration system (MARS), composed of a stationary top-view x-ray projector and a side-view optical camera, coupled to a mouse atlas registration algorithm. This system uses the x-ray and optical images to guide a fully automatic co-registration of a mouse atlas with each subject, in order to provide anatomical reference for small animal molecular imaging systems such as positron emission tomography (PET). To facilitate the registration, a statistical atlas that accounts for inter-subject anatomical variations was constructed based on 83 organ-labeled mouse micro-computed tomography (CT) images. The statistical shape model and conditional Gaussian model techniques were used to register the atlas with the x-ray image and optical photo. The accuracy of the atlas registration was evaluated by comparing the registered atlas with the organ-labeled micro-CT images of the test subjects. The results showed excellent registration accuracy of the whole-body region, and good accuracy for the brain, liver, heart, lungs and kidneys. In its implementation, the MARS was integrated with a preclinical PET scanner to deliver combined PET/MARS imaging, and to facilitate atlas-assisted analysis of the preclinical PET images.     

Texture feature extraction based on a uniformity estimation method for local brightness and structure in chest CT images

Texture feature is one of most important feature analysis methods in the computer-aided diagnosis (CAD) systems for disease diagnosis. In this paper, we propose a Uniformity Estimation Method (UEM) for local brightness and structure to detect the pathological change in the chest CT images. Based on the characteristics of the chest CT images, we extract texture features by proposing an extension of rotation invariant LBP (ELBP(riu4)) and the gradient orientation difference so as to represent a uniform pattern of the brightness and structure in the image. The utilization of the ELBP(riu4) and the gradient orientation difference allows us to extract rotation invariant texture features in multiple directions. Beyond this, we propose to employ the integral image technique to speed up the texture feature computation of the spatial gray level dependent method (SGLDM).     

Stereo Navi 2.0: Software for stereotaxic surgery of the common marmoset (Callithrix jacchus)

Recently, we reported our web-accessible digital brain atlas of the common marmoset (Callithrix jacchus) at http://marmoset-brain.org:2008. Using digital images obtained during construction of this website, we developed stand-alone software for navigation of electrodes or injection needles for stereotaxic electrophysiological or anatomical experiments in vivo. This software enables us to draw lines on exchangeable section images, measure the length and angle of lines, superimpose a stereotaxic reference grid on the image, and send the image to the system clipboard. The software, Stereo Navi 2.0, is freely available at our brain atlas website.     

骨科医学断层图像的三维重构应用及其纹理特征研究

目的在已有的骨科多源信息综合管理及特征分析系统基础上,设计开发嵌入式的、可辅助临床的医学断层图像三维可视化模块,研究医学断层图像重构后任意剖切面纹理特征的应用意义。方法在Visual Studio 6.0开发平台上开发图像三维重构模块;利用数字特征提取功能模块分别提取断层图像重构前和重构后的纹理信息,进行统计学分析。结果三维重构模块扩展原有数字特征提取模块的应用范围,可有效辅助临床医生观察疾病病灶三维体位,可对三维重构图像的任意切面进行数字化特征提取和研究。结论经实验研究验证重构图像新剖面的纹理特征有效保留断层图像纹理特征,可用于疾病辅助诊断的研究。     

基于MR图像女性阿尔茨海默症海马纹理特征研究

目的基于MR图像研究女性阿尔茨海默症患者海马纹理特征的改变。方法取阿尔茨海默症(Alzheimer’s disease,AD)患者组、老年和青年对照组各9例女性样本,提取海马和均值、灰度不均匀性等纹理参数和海马体积参数,测试各组间参数是否显著不同,并测试纹理特征和体积的相关性。结果 AD组与老年对照组海马和均值、灰度不均匀性以及体积显著不同(p0.05),纹理参数与海马体积显著相关(r0.5,p0.01)。老年对照组和青年对照组各参数均未见显著性差异。结论纹理参数可能反映AD脑组织的病理改变,海马增龄性变化与AD病理改变有本质不同。此项研究可能为AD早期诊断提供帮助。     

Differential diagnosis of CT focal liver lesions using texture features, feature selection and ensemble driven classifiers

OBJECTIVES: The aim of the present study is to define an optimally performing computer-aided diagnosis (CAD) architecture for the classification of liver tissue from non-enhanced computed tomography (CT) images into normal liver (C1), hepatic cyst (C2), hemangioma (C3), and hepatocellular carcinoma (C4). To this end, various CAD architectures, based on texture features and ensembles of classifiers (ECs), are comparatively assessed. MATERIALS AND METHODS: Number of regions of interests (ROIs) corresponding to C1-C4 have been defined by experienced radiologists in non-enhanced liver CT images. For each ROI, five distinct sets of texture features were extracted using first order statistics, spatial gray level dependence matrix, gray level difference method, Laws' texture energy measures, and fractal dimension measurements. Two different ECs were constructed and compared. The first one consists of five multilayer perceptron neural networks (NNs), each using as input one of the computed texture feature sets or its reduced version after genetic algorithm-based feature selection. The second EC comprised five different primary classifiers, namely one multilayer perceptron NN, one probabilistic NN, and three k-nearest neighbor classifiers, each fed with the combination of the five texture feature sets or their reduced versions. The final decision of each EC was extracted by using appropriate voting schemes, while bootstrap re-sampling was utilized in order to estimate the generalization ability of the CAD architectures based on the available relatively small-sized data set. RESULTS: The best mean classification accuracy (84.96%) is achieved by the second EC using a fused feature set, and the weighted voting scheme. The fused feature set was obtained after appropriate feature selection applied to specific subsets of the original feature set. CONCLUSIONS: The comparative assessment of the various CAD architectures shows that combining three types of classifiers with a voting scheme, fed with identical feature sets obtained after appropriate feature selection and fusion, may result in an accurate system able to assist differential diagnosis of focal liver lesions from non-enhanced CT images.     

数字化人脑图谱演示系统的设计与制作

目的：设计并制作一个高精度、高速度、又易于操作的二-维数字化人脑图谱，重建出人脑内部各个组织之间复杂的空间关系：方法：住PC机上使用自己开发的工具对采集到的二维人脑图像进行先期处理，并自动生成各组织的三维模型，然后使用VRML将三维模型组织在一起并在浏览器中显示出来：结果：成功构建出一个操作简单、效果逼真的脑图谱，适用于手术计划导航以及神经解剖教学：结论：利用可视化技术构建的数字化人脑图谱能够为医学研究、教学与临床提供形象而真实的模型，而且构造出的三维模型文件较小，适合于网络传输和资源共享：     

STUDY ABOUT CLINICAL APPLICATION OF BRAIN ATLAS IN PAEDIATRICS

Objectives To explore clinical application on brain atlas in paediatrics. Methode: Brainatlas was applied in diagnosis and treatment of paediatric diseases and its clinical value was discussed in 1990～2001. The manifestation of these diseases in brain atlas were analysed and the manifestation of CT of 67 cases andmanifestations of EEG of 37 cases with that of BA were compared. Results The changes of cerebral electrical ac-tivity of these diseases were reflected objectively and showed directly in BA. Conclusion Brain atlas not only canpoint out quality of disease but also define position of disease. Therefore, brain atlas has important clinical valuein paediatrics.     

A three-dimensional digital atlas database of the adult C57BL/6J mouse brain by magnetic resonance microscopy

A comprehensive three-dimensional digital atlas database of the C57BL/6J mouse brain was developed based on magnetic resonance microscopy images acquired on a 17.6-T superconducting magnet. By using both manual tracing and an atlas-based semi-automatic segmentation approach, T2-weighted magnetic resonance microscopy images of 10 adult male formalin-fixed, excised C57BL/6J mouse brains were segmented into 20 anatomical structures. These structures included the neocortex, hippocampus, amygdala, olfactory bulbs, basal forebrain and septum, caudate-putamen, globus pallidus, thalamus, hypothalamus, central gray, superior colliculi, inferior colliculi, the rest of midbrain, cerebellum, brainstem, corpus callosum/external capsule, internal capsule, anterior commissure, fimbria, and ventricles. The segmentation data were formatted and stored into a database containing three different atlas types: 10 single-specimen brain atlases, an average brain atlas and a probabilistic atlas. Additionally, quantitative group information, such as variations in structural volume, surface area, magnetic resonance microscopy image intensity and local geometry, were computed and stored as an integral part of the database. The database augments ongoing efforts with other high priority strains as defined by the Mouse Phenome Database focused on providing a quantitative framework for accurate mapping of functional, genetic and protein expression patterns acquired by a myriad of technologies and imaging modalities.     

髋关节骨内植入体模型的创建

目的利用CT/MRI医学影像数据,在建立人体髋关节三维模型的基础上,运用Mimics软件中MedCAD模块创建个性化的人体髋关节植入体模型。方法应用Mimics软件,对髋关节组织扫描图像进行处理,根据病体使用MedCAD模块创建植入体CAD模型,然后选择合适的植入体将其放入病体髋关节骨的合理位置上。结果首先创建病体髋关节模型,在此基础上运用Mimics的MedCAD模块在髋骨三维模型上进行植入体的操作,可根据患者的个性化对植入体的大小、形状进行选择或设计,对植入体所放的位置进行定位。结论该研究强调针对不同患者进行个性化的产品研发与设计。依据关节解剖结构的特异性,来创建人体植入体,以符合患者术后关节功能性解剖的需要。