造影图像序列中动脉血管的三维测量

针对X射线心血管造影图像的后处理问题,本文提出一种采用两个近似正交的单面X射线造影图像序列对冠状动脉的三维形状和运动参数进行定量测量的方法.该方法首先采用snake技术从两个角度的图像中重建出各时刻的三维血管轴线.根据三维重建和二维提取的结果,完成对血管形状参数(如长度和腔径)的测量.然后将血管运动场的估计转化为对相邻时刻间血管分支轴线的逐点匹配,并获得位移幅值和运动轨迹等重要参数.最后分别采用模型的X射线图像、计算机模拟数据和临床图像对该方法进行了验证.实验结果表明,该方法是可行的.     

一种自动提取IVUS图像血管包络的新方法

提取血管内超声(IVUS)图像的血管包络对冠状动脉疾病的诊断有一定的积极意义。本文综合考虑IVUS图像的灰度特征、序列时间特性、先验知识等三类信息,提出一种自动提取血管包络的方法。先由序列时间特性和先验知识减少噪声和伪像干扰,提取出第一帧图像的初始包络;然后用结合梯度、灰度方差、灰度均值信息的B样条GVFsnake对初始包络进行变形得到第一帧的最终包络;最后利用序列图像的时间特性提取后续帧的包络。通过实验表明:综合三类信息的包络自动提取方法在精度和鲁棒性等方面优于以往的方法。     

基于snake模型的IVUS图像序列三维分割方法

针对血管内超声（Intravascular Ultrasound,IVUS）图像序列中血管壁内外膜轮廓的提取问题,提出一种基于snake模型的三维并行分割方法。首先,对原始图像进行滤除噪声和抑制环晕伪像等预处理。然后,获取IVUS图像序列的四个纵向视图,并从中提取出内腔边界和中-外膜边界。通过将这些边界曲线映射到各帧IVUS图像中,得到横向视图中的初始轮廓。最后,将该初始轮廓作为snake模型的初始形状,通过使snake能量函数最小,模型不断变形,最终得到各帧IVUS图像中的内腔和中-外膜边界。该方法可实现对IVUS图像序列的并行分割,与二维串行分割方法相比,可大大提高处理效率。采用大量临床图像数据的实验结果证明该方法可自动、快速、可靠的完成IVUS图像序列的分割。     

一种抑制IVUS图像序列中运动伪像的方法

针对连续回撤超声导管采集的冠状动脉血管内超声(intravascularultrasound,IVUS)图像序列中存在由周期性心脏运动所致运动伪像的问题,提出一种抑制方法,以改善IVUS纵向视图的视觉效果。首先,在综合分析运动伪像产生机制和表现形式的基础上,对相邻帧之间血管壁的刚性运动进行定量估计;然后,采用谱分析方法完成刚性运动参数中运动分量和几何分量的分离;最后,通过对各帧图像中血管壁的运动分量进行补偿,完成对运动伪像的抑制。该方法既不需要专门的ECG门控图像采集装置,也无需记录ECG信号,同时不需要抛弃有用帧,在抑制运动伪像的同时保证图像数据集合的完整性。对模拟图像和临床图像的实验验证了方法的可行性。     

人体微小管状血管血液流速自动测量方法研究

提出了一种基于视频图像序列的人体微小管状血管血液流速自动测量方法.在提取血管中心线时采用基于图像帧序列方差的种子点自动选取方法,设计了基于Hessian矩阵的血管中心线提取的迭代算法;提取血管中心线后,根据连续帧图像的中心线灰度统计曲线,计算出血液流速.结果表明:该方法测量速度快、精度高,与专家测量结果之间的相关系数为0.901 4.     

基于造影图像的冠状动脉血管三维表面重建方法

在冠状动脉树骨架三维重建的基础上,研究了基于造影图像的血管表面重建方法。首先采用B样条曲线拟合血管的三维骨架,建立了骨架点的局部坐标系。同时研究了血管横截面的椭圆模型,并推导了椭圆方程。针对血管树表面重建中的自相交问题,提出一种新型顶点融合技术,给出了融合点的计算方法。最后利用两幅不同角度的临床冠脉造影图像,成功实现了血管的三维表面重建。     

血管内超声图像后处理综述

血管内超声显像是目前临床常用的诊断血管病变的介入影像手段,可在活体中观察血管壁和管腔的形态,以及斑块的形态和成分。采用数字图像处理技术,对血管内超声图像序列进行自动或半自动地处理和分析,对于血管病变的计算机辅助诊断和制定最佳诊疗方案具有重要意义。本文就近年来血管内超声图像计算机后处理的研究现状进行综述,包括图像分割和组织标定、运动伪影的抑制、血管的三维重建、血管形态和血流动力学参数的测量、组织定征显像及与其他影像的融合等,评价了目前的研究情况,并对未来的研究提出了展望。     

冠状动脉造影图像序列中估计二维运动及变形的弹性配准算法

提出一种由单面血管造影图像序列分析心脏冠状动脉运动和变形的方法，即利用弹性配准算法，将动脉运动的估计简化为对连续两帧图像的骨架像素的匹配．采用动态规划的方法进行配准，同时引入自回归建模，二者结合起来互相作用：动态规划为自回归模型参数的估计提供样本值；自回归模型为动态规划提供适当的成本函数。采用临床得到的单面冠状动脉造影图像序列对该算法进行了验证。实验结果表明应用该方法计算血管骨架图像中各点的光滑移动向量场，能够得到精确的结果。     

基于光流法的冠状动脉造影图像序列中血管运动的估计

利用冠状动脉造影图像序列进行二维血管运动的分析，对于准确估计与解释心脏的运动，从而正确诊断心血管和心脏疾病十分关键。同时也是由血管造影图进行冠状动脉树三维重建的重要步骤。笔者采用光流法对单面冠状动脉造影图像序列进行血管运动估计，以动脉分叉点作为运动跟踪的标志，并提出在很短的时间间隔内冠状动脉上很小部分的运动可以认为是简单平移的假设，从而计算出血管以及相关心外膜的运动参数。     

复杂场景条件下的运动目标检测算法

针对复杂场景条件下运动目标检测方法存在的局限性,提出了一种基于运动检测和静止图像分割相融合的算法。采用相邻帧差法结合建立的假设检验模型进行自适应的运动目标检测;为消除孔径效应和噪声的影响,根据运动目标检测的结果,在当前帧利用区域增长法融合运动分割的结果。试验结果表明,算法能从复杂场景的图像序列中有效地检测和提取出运动目标,并有很强的鲁棒性。     

Supervised method for blood vessel segmentation from coronary angiogram images using 7-D feature vector

With the recent advancement in medical image processing field and sophisticated simulation tools it has been possible to acquire useful information from raw images for different parts of the body. Coronary artery segmentation is the fundamental component which extract significant features from angiogram images. Cardiac catheterization is an invasive diagnostic procedure that provides important information about the structure and function of heart. The procedure usually involves X-ray images of heart, arteries using coronary angiography. The resultant images (coronary angiogram) are considered as best of way to diagnose cardiac heart disease. The main focus of coronary angiography is to find the blockage in major blood vessels, however if the blockage is not found in large blood vessels and patient persists to have pain (angina) then it is concluded that the patient is having micro vascular disease (MVD). MVD is caused by blockage or narrowing of small blood vessels in heart, unfortunately there is no specific test to diagnose MVD but it is common in people having diabetes and blood pressure. This paper proposes an automated method of vessel segmentation from coronary angiogram images using radial basis function and moment invariant-based features to extract the small blood vessel for diagnosis of MVD. Experimental results show that the proposed method is capable of extracting small blood vessels from coronary artery and can be a basis to identify key characteristics for MVD. The dataset of angiogram images have been provided by ISRA University Hospital and MATLAB is used for implementing the proposed method.     

Synthetic aperture-based beam compression for intravascular ultrasound imaging

In this paper, intravascular ultrasound (IVUS) images acquired with a 64-element array transducer using a multistatic acquisition scheme are presented. The images are reconstructed from a collection of pulse-echo measurements using a synthetic aperture array imaging technique. The main limitations of IVUS imaging are a poor lateral resolution and elevated grating lobes caused by the imaging geometry. We propose a Synthetic Aperture Focusing Technique (SAFT), which uses a limited number of A-scan signals. The focusing process, which is performed in the Fourier domain, requires far less computation time than conventional delay-and-sum methods. Two different reconstruction kernel functions have been derived and are compared for the processing of experimental data     

In-vivo measurement of coronary stent dimensions throughout entire vascular segments with quantitative three-dimensional intravascular ultrasound: a review

The implantation of metallic endoprostheses (i. e., stents) is a rapidly expanding interventional technique for the catheter-based therapy of symptomatic patients with significant coronary stenoses. But stents are frequently radiolucent and after deployment difficult to appreciate on fluoroscopy and coronary angiograms obtained by x-ray. Intravascular ultrasound (IVUS), on the other hand, permits detailed examination of coronary stent apposition and expansion in vivo. Recently, automated systems for three-dimensional (3-D) reconstruction and analysis of IVUS images have been developed. The initial experience with 3-D IVUS in coronary stenting is positive. Different technical approaches demonstrated superiority of 3-D IVUS in detecting both, the site of the smallest in-stent lumen cross-sectional area and sub-optimal results following stent deployment. In-addition, the restenosis process inside stents can excellently be studied with IVUS. In-stent neointimal ingrowth can be exmined with a computerized 3-D contour detection system that permits off-line detection of the neointimal leading edge and the coronary stent struts. This 3-D approach provides computerized measurement of neointimal volume, based on a large number of IVUS images. Considering the current trend towards more complex coronary stenting procedures, a feasible and reliable 3-D analysis tool for clinical on-line assessment after stent deployment may also be very useful.     

Intravascular photoacoustic imaging using an IVUS imaging catheter

Catheter-based imaging of atherosclerosis with high resolution, albeit invasive, is extremely important for screening and characterization of vulnerable plaques. Currently, there is a need for an imaging technique capable of providing comprehensive morphological and functional information of plaques. In this paper, we present an intravascular photoacoustic imaging technique to characterize vulnerable plaques by using optical absorption contrast between normal tissue and atherosclerotic lesions. Specifically, we investigate the feasibility of obtaining intravascular photoacoustic (IVPA) images using a high-frequency intravascular ultrasound (IVUS) imaging catheter. Indeed, the combination of IVPA imaging with clinically available IVUS imaging may provide desired functional and morphological assessment of the plaque. The imaging studies were performed with tissue-mimicking arterial vessel phantoms and excised samples of rabbit artery. The results of our study suggest that catheter-based intravascular photoacoustic imaging is possible, and the combination of IVPA with IVUS has the potential to detect and differentiate atherosclerosis based on both the structure and composition of the plaque.     

Intravascular ultrasound detection and delivery of molecularly targeted microbubbles for gene delivery

We are investigating the combination of microbubble-based targeted drug delivery and intravascular ultrasound (IVUS) imaging as a potential therapy to reduce incidence of restenosis following stent placement in atherosclerotic coronary arteries. The goal of these studies was to determine whether IVUS could be used to detect targeted microbubbles and enhance drug/gene delivery through targeting. Quiescent vascular smooth muscle cells (SMCs) were stimulated with cytokine IL-1β to induce the inflammatory cell surface marker vascular cell adhesion molecule 1 (VCAM-1). Molecular-targeted (VCAM-1 Ab or IgG control Ab), fluorescent-labeled microbubbles were conjugated with plasmid DNA expressing green fluorescent protein (GFP, pMax-GFP) and exposed to the inflamed SMCs under flow to measure adhesion compared with control microbubbles. Gene delivery was performed using a modified IVUS catheter to generate 1.5-MHz ultrasound at 200 kPa. Detection of adherent microbubbles to inflamed SMCs in culture and flow chambers was measured using an IVUS catheter and scanner. VCAM-1-targeted microbubbles enhanced adhesion to inflamed SMCs 100-fold over nontargeted microbubbles. Compared with noninflamed SMCs, VCAM-1-targeted microbubbles exhibited a 7.9-fold increase in adhesion to IL-1β-treated cells. Targeted microbubbles resulted in a 5.5-fold increase in plasmid DNA transfection over nontargeted microbubbles in conjunction with a focused 2.54-cm (1-in) diameter 1-MHz transducer and also enhanced transfection by the modified IVUS transducer at 1.5 MHz. Targeted microbubbles (at a density of 3 × 10? microbubbles/mm2) increased IVUS image intensity 13.2 dB over non-microbubble-coated surfaces. Rupture of microbubbles from the modified IVUS transducer resulted in a 53% reduction in image intensity. Taken together, these results indicate that IVUS may be used to detect targeted microbubbles to inflamed vasculature and subsequently deliver a gene/drug locally.     

SWI post processing using granularity controlled edge-preserved denoising of multichannel GRE images

The influence of granularities in the background suppressed phase of susceptibility-weighted images (SWI) and susceptibility-weighted angiogram (SWAN) becomes significant when the susceptibility based contrast is enhanced by exponential weighting of the high-pass filtered phase. Furthermore, the effect of noise due to the inherently low signal-to-noise ratio resulting from high-resolution SWI/SWAN acquisition, can be minimized by application of edge-preserved denoising of the channel phase images without loss of venous structural details. Simultaneous reduction of granularity effects with edge-preserved denoising is achieved using the proposed granularity controlled adaptive edge-preserved regularization (GRADER). In this approach, the edge-preserving cost is minimized with respect to the desired channel phase image and an unknown scale parameter that adaptively tunes the high-pass filter. The algorithm is implemented using quasi-Newton type iterations, with the scale parameter updated using a search procedure in each alternating minimization step. The iterations are stopped once the scale parameter converges to a steady state value. Extension of GRADER to parallel MRI (pMRI) by processing the real and imaginary components of complex channel images (IR-GRADER) results in enhanced susceptibility-related contrast-to-noise ratio of the magnitude SWI, leading to improved visualization of superficial veins and deep gray matter structures.     

Motion compensation for intravascular ultrasound palpography

Rupture of vulnerable plaques in coronary arteries is the major cause of acute coronary syndromes. Most vulnerable plaques consist of a thin fibrous cap covering an atheromous core. These plaques can be identified using intravascular ultrasound (IVUS) palpography, which measures radial strain by cross-correlating RF signals at different intraluminal pressures. Multiple strain images (i.e., partial palpograms) are averaged per heart cycle to produce a more robust compounded palpogram. However, catheter motion due to cardiac activity causes misalignment of the RF signals and thus of the partial palpograms, resulting in less valid strain estimates. To compensate for in-plane catheter rotation and translation, we devised four methods based on block matching. The global rotation block matching (GRBM) and contour mapping (CMAP) methods measure catheter rotation, and local block matching (LBM) and catheter rotation and translation (CRT) estimate displacements of local tissue regions. These methods were applied to nine in vivo pullback acquisitions, made with a 20 MHz phased-array transducer. We found that all these methods significantly increase the number of valid strain estimates in the partial and compounded palpograms (P < 0.008). The best method, LBM, attained an average increase of 17% and 15%, respectively. Implementation of this method should improve the information coming from IVUS palpography, leading to better vulnerable plaque detection.     

Quantitative characterization of carbon nanotube turf topology by SEM analysis

A procedure has been developed to quantify various parameters that affect the mechanical stiffness of vertically aligned multi-walled carbon nanotube turfs from secondary electron images. A representative measure of density, tortuosity, and path connectedness is obtained from the images as these parameters are presumed to correlate with measured properties for this class of materials. Elastic moduli were determined using nanoindentation techniques. Experimental evidence indicates that an increase in turf density does not necessarily result in an increase in elastic modulus. Six turfs analyzed in this work along with four additional structures selected from a previous publication support the conclusion that an increase in density is not necessarily responsible for an increase in mechanical stiffness of a turf. Tortuosity and path connectedness tend to show more of a correlation with stiffness, though no direct correlation with these parameters was identified.