Dual-mode registration of dynamic contrast-enhanced ultrasound combining tissue and contrast sequences

This study proposes a new method for automatic, iterative image registration in the context of dynamic contrast-enhanced ultrasound (DCE-US) imaging. By constructing a cost function of image registration using a combination of the tissue and contrast-microbubble responses, this new method, referred to as dual-mode registration, performs alignment based on both tissue and vascular structures. Data from five focal liver lesions (FLLs) were used for the evaluation. Automatic registration based on the dual-mode registration technique and tissue-mode registration obtained using the linear response image sequence alone were compared to manual alignment of the sequence by an expert. Comparison of the maximum distance between the transformations applied by the automatic registration techniques and those from expert manual registration reference showed that the dual-mode registration provided better precision than the tissue-mode registration for all cases. The reduction of maximum distance ranged from 0.25 to 9.3 mm. Dual-mode registration is also significantly better than tissue-mode registration for the five sequences with p  -values lower than 0.03$0.03$. The improved sequence alignment is also demonstrated visually by comparison of images from the sequences and the video playbacks of the motion-corrected sequences. This new registration technique better maintains a selected region of interest (ROI) within a fixed position of the image plane throughout the DCE-US sequence. This should reduce motion-related variability of the echo-power estimations and, thus, contribute to more robust perfusion quantification with DCE-US.     

嫦娥一号月面成像的高精度匹配及月貌三维重建

针对嫦娥一号探月卫星2C级月面成像,提出了基于待配点最优模板选择的二次函数形变补偿迭代匹配方法。仿真表明它能有效地适应地形起伏引起的图像形变,匹配精度较高且稳定性好。在标准相关匹配的基础上结合所提出的方法完成了下视图与前、后视图的精确匹配,采用三视约束机制和顺序检验机制保证了匹配的稳健性。分析了线阵相机成像的仿射近似模型,并以此为基础实现同轨三视重建。基于邻轨下视图同名特征点,采用RANSAC方法估计邻轨三维坐标转换参数,完成邻轨拼接。实验结果表明,三维重建的月貌图能够更好地表达月球表面的形状和地形。     

基于白光干涉彩色图像的微结构表面形貌测量

微结构的表面形貌会显著地影响微纳器件的使用性能及产品质量,是微纳测试领域的一个重要研究方面,利用白光干涉技术是测量物体表面形貌的一种常见方法。区别于常用的CCD黑白相机,使用CCD彩色相机采集白光干涉条纹的彩色图像,使获取的图像包含了R、G、B三个通道的信息。利用小波变换法分别求解出在不同扫描位置处R、G、B通道的相位信息,通过建立的评价函数,并结合最小二乘法可精确确定零光程差的位置,利用相对高度和零光程差位置的线性关系,进而得到物体的表面形貌。通过仿真以及实际测量由VLSI标准公司制造的标准台阶结构,验证了所提出方法的有效性。     

航天时间延迟积分CCD相机摆扫成像快速几何校正设计与分析

为实现在轨卫星机动成像条带的快速准确拼接和应用,针对高分辨力卫星在轨推摆扫相结合的机动成像模式,提出了一种光线追迹像移匹配数学建模方法。通过对卫星机动过程中的摆角变化、地球表面面型的影响分析,利用摆扫过程中姿态对地指向不断改变导致的交轨方向速度失配量和成像变形量,补偿相机像面各点处的像移量从而进行快速几何校正。利用小卫星姿态控制系统全物理仿真平台对成像进行了仿真分析。分析结果表明,成像过程中随着扫描角的增加,像面上的像移量增大,成像变形情况也变严重。利用均方误差分析仿真成像与实验成像质量,仿真成像与实验成像相差-0.000011左右,较好地满足地面卫星相机成像仿真需求。对不同扫描角下存在速度失配的图像进行快速几何校正,该校正后图像的均方误差变小。该校正方法具有效率高,便于拼接应用的优点。     

基于聚类分割和形态学的可见光与SAR图像配准

针对可见光与SAR图像灰度差异大,共有特征提取难的问题,提出了一种基于k-均值聚类分割和形态学处理的轮廓特征配准方法。利用k-均值聚类算法对两类图像进行分割,得到图像分割区域;通过形态学处理,有效减少SAR图像斑点噪声影响,准确提取两类图像的封闭轮廓;采用轮廓不变矩理论,引入矩变量距离均值、方差约束机制和一致性检查的匹配策略,获取最佳匹配对,实现了两类图像的配准。通过实验,三组图像的配准精度分别达到0.3450、0.2163和0.1810,结果表明该法可行且能达到亚像素的配准精度。     

Multiplicative intrinsic component optimization (MICO) for MRI bias field estimation and tissue segmentation

This paper proposes a new energy minimization method called multiplicative intrinsic component optimization (MICO) for joint bias field estimation and segmentation of magnetic resonance (MR) images. The proposed method takes full advantage of the decomposition of MR images into two multiplicative components, namely, the true image that characterizes a physical property of the tissues and the bias field that accounts for the intensity inhomogeneity, and their respective spatial properties. Bias field estimation and tissue segmentation are simultaneously achieved by an energy minimization process aimed to optimize the estimates of the two multiplicative components of an MR image. The bias field is iteratively optimized by using efficient matrix computations, which are verified to be numerically stable by matrix analysis. More importantly, the energy in our formulation is convex in each of its variables, which leads to the robustness of the proposed energy minimization algorithm. The MICO formulation can be naturally extended to 3D/4D tissue segmentation with spatial/sptatiotemporal regularization. Quantitative evaluations and comparisons with some popular softwares have demonstrated superior performance of MICO in terms of robustness and accuracy.     

Automatic leukocyte nucleus segmentation by intuitionistic fuzzy divergence based thresholding

The paper proposes a robust approach to automatic segmentation of leukocyte's nucleus from microscopic blood smear images under normal as well as noisy environment by employing a new exponential intuitionistic fuzzy divergence based thresholding technique. The algorithm minimizes the divergence between the actual image and the ideally thresholded image to search for the final threshold. A new divergence formula based on exponential intuitionistic fuzzy entropy has been proposed. Further, to increase its noise handling capacity, a neighborhood-based membership function for the image pixels has been designed. The proposed scheme has been applied on 110 normal and 54 leukemia (chronic myelogenous leukemia) affected blood samples. The nucleus segmentation results have been validated by three expert hematologists. The algorithm achieves an average segmentation accuracy of 98.52% in noise-free environment. It beats the competitor algorithms in terms of several other metrics. The proposed scheme with neighborhood based membership function outperforms the competitor algorithms in terms of segmentation accuracy under noisy environment. It achieves 93.90% and 94.93% accuracies for Speckle and Gaussian noises, respectively. The average area under the ROC curves comes out to be 0.9514 in noisy conditions, which proves the robustness of the proposed algorithm.     

基于免疫模板聚类的模糊中波红外图像目标提取

借鉴生物先天性免疫与适应性免疫的协调作用机制,综合考虑中波红外图像的光谱成像机理和频域模板统计特征,提出一种免疫模板聚类目标提取算法。借鉴先天性免疫对抗原表面分子模式的识别作用,以最大类间方差,将模糊中波红外图像初分割为目标像素集、背景像素集和模糊像素集;借鉴先天性免疫的特征提呈作用,提取中波红外图像模糊像素的频域模板特征,将图像的像素灰度特征空间映射为频域模板特征空间;基于提呈得到的模板特征,对模糊像素集进行适应性免疫聚类,将模糊像素划分为目标像素或背景像素。用手部痕迹的模糊中波红外图像进行实验,并与经典边缘检测模板法和传统区域模板法进行了效果比较和定量评价,结果表明免疫模板聚类算法的目标提取率、与参考标准的重合度、绝对误差率均优于现有模板方法,能够有效实现模糊中波红外图像的目标提取。     

玉米作物多光谱图像精准分割与叶绿素诊断方法研究

为了快速获取大田玉米作物长势信息, 基于多光谱图像开展了大田玉米叶绿素指标的非破坏性诊断研究。应用自主开发的2-CCD多光谱图像感知系统, 在田间采集玉米冠层可见光［Blue(B), Green(G), Red(R);400～700 nm］和近红外(Near-infrared: NIR, 760～1 000 nm)图像, 并使用SPAD同步测量样本叶绿素指标。采集后图像经自适应平滑滤波处理后, 进行图像玉米植株提取。为了选择最优算法实现玉米植株与杂草、土壤背景的分割, 首先比较了最大类间方差(OTSU)分割算法和局部阈值处理分割算法, 选取了基于局部统计的可变阈值处理方法对玉米NIR图像进行初步分割, 进而采用区域标记算法进行精细分割, 分割准确率达95.59%。将分割结果应用于玉米植株可见光图像R, G, B各通道, 从而实现了玉米植株多光谱图像中可见光图像的整体分割。基于分割后R, G, B和NIR四个通道的玉米冠层图像, 提取了各通道图像灰度均值(ANIR, ARed, AGreen和ABlue)并计算了归一化植被指数(NDVI)、比值植被指数(RVI)和绿色归一化植被指数(NDGI)作为光谱特征参数, 建立了玉米冠层叶绿素指标诊断的偏最小二乘法回归模型。结果表明, 建模R2达0.596 0, 预测R2达0.568 5, 该方法通过玉米多光谱图像特征参数评估叶片叶绿素含量, 可为大田玉米长势监测提供支持。     

基于ARM架构的图形水幕系统

传统的以水为装饰的方法形式比较单一,缺乏创新性的现状,因此提出了一种基于ARM架构,结合了人体传感、无线传输等功能的数字图形水幕系统,能够精确控制电磁水阀开/闭合,实现了以水为媒介的图形、文字的展示;同时,在系统中开发了一种自由落体图像补偿算法,创建了图像补偿表,通过对原始图像的补偿可在系统人眼感兴趣的区域很好展示所需的图形及文字;在实验中可看出系统在1.26 m×1.26 m的显示区域内对64×64像素的图形进行补偿时达到了较好的效果;该系统综合考虑了性能、成本等因素,具有很强的创新性和实用价值。