Blood vessel enhancement for DSA images based on adaptive multi-scale filtering

Digital subtraction angiography (DSA) plays a significant role in the diagnosis, treatment planning and assessment of diseases. However, because of the geometrical complexity and fine characteristics of blood vessel structures, accurate and robust detection of blood vessels still remains a problem. In this paper, a blood vessel enhancement algorithm is proposed. The main purpose of this work is to improve the visual quality of blood vessels in DSA images. The new blood vessel enhancement algorithm is based on the multi-scale space theory and Hessian matrix. Not only the eigenvalues of Hessian matrix but also the angles between eigenvectors are utilized for the blood vessel enhancement of DSA. The filter parameters and scale factors are decided adaptively. Eigenvalues of the Hessian matrix are also used for the noise elimination. Experimental results show that the proposed algorithm has a good performance in blood vessel enhancement of DSA images. The proposed algorithm filters image background and non-vascular structure effectively. The deformation of blood vessels occurred in the enhancement process is avoided and more small blood vessels are visible in DSA images.     

改进的经验模态分解法分离超声多普勒血流与管壁信号

超声多普勒血流信号常包含管壁信号的干扰,准确分离二者对提高血流检测的精度具有重要作用。本文提出两种改进的经验模态分解(EMD)方法,先将含管壁信号的超声多普勒信号分解成多层本征模态函数(IMF),然后根据血流信号与管壁信号的不同特性,对既含管壁信号又含血流信号的IMF分量进行分离处理,最后将各层IMF分量中的管壁成分叠加得到管壁信号的估计,而血流信号可通过原信号减去估计的管壁信号而得到。将本方法用于计算机仿真信号和人体实测的超声多普勒信号,并与高通滤波器法、空间选择性降噪法和原EMD法进行比较,结果表明:本文提出的两种方法能在较大的管壁搏动速度范围内准确地分离血流信号和管壁信号,其平均相对误差比高通滤波器的结果降低了约52%和57%。可见,本文提出的两种方法有望用于血流信号与管壁信号的准确分离。      

Wavelet and model-based spectral analysis of color doppler optical coherence tomography

Color doppler optical coherence tomography (CD-OCT) uses time-frequency analysis (TFA) to extract motion-induced Doppler shifted in the interferometric OCT signal. In this paper, the performance of three TFAs are compared in a scattering flow phantom and in in vivo human retina: the short-time Fourier transform, the Morlet-wavelet transform, and the short-time MUSIC transform (STMT). The STMT is a new TFA that incorporates the MUSIC eigenfrequency estimator in a generalized short-time framework. The Morlet transform excels at identifying blood vessels, while the STMT is the most accurate predictor of Doppler shift frequency.     

Boundary segmentation based on modified random walks for vascular Doppler optical coherence tomography images

Vascular Doppler optical coherence tomography(DOCT) images with weak boundaries are usually difficult for most algorithms to segment. We propose a modified random walk(MRW) algorithm with a novel regularization for the segmentation of DOCT vessel images. Based on MRW, we perform automatic boundary detection of the vascular wall from intensity images and boundary extraction of the blood flowing region from Doppler phase images. Dice, sensitivity, and specificity coefficients were adopted to verify the segmentation performance. The experimental study on DOCT images of the mouse femoral artery showed the effectiveness of our proposed method, yielding three-dimensional visualization and quantitative evaluation of the vessel.     

A fully automated algorithm under modified FCM framework for improved brain MR image segmentation

Automated brain magnetic resonance image (MRI) segmentation is a complex problem especially if accompanied by quality depreciating factors such as intensity inhomogeneity and noise. This article presents a new algorithm for automated segmentation of both normal and diseased brain MRI. An entropy driven homomorphic filtering technique has been employed in this work to remove the bias field. The initial cluster centers are estimated using a proposed algorithm called histogram-based local peak merger using adaptive window. Subsequently, a modified fuzzy c-mean (MFCM) technique using the neighborhood pixel considerations is applied. Finally, a new technique called neighborhood-based membership ambiguity correction (NMAC) has been used for smoothing the boundaries between different tissue classes as well as to remove small pixel level noise, which appear as misclassified pixels even after the MFCM approach. NMAC leads to much sharper boundaries between tissues and, hence, has been found to be highly effective in prominently estimating the tissue and tumor areas in a brain MR scan. The algorithm has been validated against MFCM and FMRIB software library using MRI scans from BrainWeb. Superior results to those achieved with MFCM technique have been observed along with the collateral advantages of fully automatic segmentation, faster computation and faster convergence of the objective function.     

Noncontact blood species identification method based on spatially resolved near-infrared transmission spectroscopy

The inspection and identification of whole blood are crucially significant for import-export ports and inspection and quarantine departments. In our previous research, we proved Near-Infrared diffuse transmitted spectroscopy method was potential for noninvasively identifying three blood species, including macaque, human and mouse, with samples measured in the cuvettes. However, in open sampling cases, inspectors may be endangered by virulence factors in blood samples. In this paper, we explored the noncontact measurement for classification, with blood samples measured in the vacuum blood vessels. Spatially resolved near-infrared spectroscopy was used to improve the prediction accuracy. Results showed that the prediction accuracy of the model built with nine detection points was more than 90% in identification between all five species, including chicken, goat, macaque, pig and rat, far better than the performance of the model built with single-point spectra. The results fully supported the idea that spatially resolved near-infrared spectroscopy method can improve the prediction ability, and demonstrated the feasibility of this method for noncontact blood species identification in practical applications.     

Estimation of emissivities in a two-dimensional irregular geometry by inverse radiation analysis using hybrid genetic algorithm

An inverse radiation analysis is presented for estimating the wall emissivities for an absorbing, emitting, scattering media in a two-dimensional irregular geometry with diffusely emitting and reflecting opaque boundaries from the measured temperatures. The finite-volume method was employed to solve the radiative transfer equation for 2D irregular geometry. The hybrid genetic algorithm which contains local optimization algorithm was adopted to estimate wall emissivities by minimizing an objective function, while reducing computation time. It was found that an increase in the standard deviation in measurements significantly deteriorated the estimation of wall emissivities. Thus, a very accurate measurement was required in inverse radiation for better estimation of wall emissivities, especially, in a high temperature environment.     

不同激光参数照射下血管中血栓的演变

目前,激光是治疗葡萄酒色斑(Port Wine Stain,PWS)最有效的疗法。然而,由于选择性光热效应机理研究的欠缺,PWS的临床彻底清除率依然很低(<20%)。本文利用鼠脊视窗模型研究了不同激光参数照射下血管中光凝块和血栓的演变规律,以期为开发新的治疗策略提供依据。实验结果表明,Nd:YAG激光(1064 nm)照射后血管中只出现光凝块。长脉宽532nm激光照射后血管中首先形成光凝块,随着光凝块的流走,血栓产生并粘着血管壁。血栓面积随时间先增大后减小,存在时间长达4 h以上。短脉宽532 nm激光照射后,则形成非粘着血管壁血栓并随血流流走。由于形成完全堵塞血管的血栓是清除血管的前提,长脉宽532 nm激光联合抗血栓药物治疗PWS有望改善激光治疗PWS疗效。     

Experimental evaluation of an ultrasound technique for the biometric recognition of human hand anatomic elements

In this work the moving ultrasound linear array technique has been used to perform 3D echographic images of different human hands, in order to evaluate this technique to biometric recognition purposes. An automated set up, based on a commercial echographic machine provided with a high frequency (12 MHz) linear array, has been built up. The probe is moved in the direction orthogonal to the array and at each step a B-scan is performed and stored to form a 3D matrix representing the under skin hand volume.B-scan and C-scan images of the hand of different users were analysed and compared. The results have shown that, in the analysed region (about 10 mm under the palm skin), there are several anatomic elements (including hand bones, bending tendons, muscle tissue, blood vessels) that can be exploited for measurements of biometric parameters.The characteristics of the proposed technique are compared with those of the 2D optical hand geometry, which is a well established biometric technique, and its possible advantages are underlined and discussed.     

3D depth-coded photoacoustic microscopy with a large field of view for human skin imaging

Photoacoustic(PA) microscopy comes with high potential for human skin imaging, since it allows noninvasively high-resolution imaging of the natural hemoglobin at depths of several millimeters. Here, we developed a PA microscopy to achieve high-resolution, high-contrast, and large field of view imaging of skin. A three-dimensional(3D) depth-coding technology was used to encode the depth information in PA images, which is very intuitive for identifying the depth of blood vessels in a two-dimensional image, and the vascular structure can be analyzed at different depths. Imaging results demonstrate that the 3D depth-coded PA microscopy should be translated from the bench to the bedside.     

Laser optical method of visualizing cutaneous blood vessels and its applications in biometry and photomedicine

We propose and examine a new approach to visualizing a local network of cutaneous blood vessels using laser optical methods for applications in biometry and photomedicine. Various optical schemes of the formation of biometrical information on the architecture of blood vessels of skin tissue are analyzed. We developed an optical model of the interaction of the laser radiation with the biological tissue and a mathematical algorithm of processing of measurement results. We show that, in medicine, the visualization of blood vessels makes it possible to calculate and determine regions of disturbance of blood microcirculation and to control tissue hypoxia, as well as to maintain the local concentration of oxygen at a level necessary for the normal cellular metabolism. We propose noninvasive optical methods for modern photomedicine and biometry for diagnostics and elimination of tissue hypoxia and for personality identification and verification via the pattern of cutaneous blood vessels.     

MR image-based measurement of rates of change in volumes of brain structures. Part I: method and validation

A detailed analysis procedure is described for evaluating rates of volumetric change in brain structures based on structural magnetic resonance (MR) images. In this procedure, a series of image processing tools have been employed to address the problems encountered in measuring rates of change based on structural MR images. These tools include an algorithm for intensity non-uniformity correction, a robust algorithm for three-dimensional image registration with sub-voxel precision and an algorithm for brain tissue segmentation. However, a unique feature in the procedure is the use of a fractional volume model that has been developed to provide a quantitative measure for the partial volume effect. With this model, the fractional constituent tissue volumes are evaluated for voxels at the tissue boundary that manifest partial volume effect, thus allowing tissue boundaries be defined at a sub-voxel level and in an automated fashion. Validation studies are presented on key algorithms including segmentation and registration. An overall assessment of the method is provided through the evaluation of the rates of brain atrophy in a group of normal elderly subjects for which the rate of brain atrophy due to normal aging is predictably small. An application of the method is given in Part II where the rates of brain atrophy in various brain regions are studied in relation to normal aging and Alzheimer's disease.     

Modeling wave propagation in realistic heart geometries using the phase-field method

We present a novel algorithm for modeling electrical wave propagation in anatomical models of the heart. The algorithm uses a phase-field approach that represents the boundaries between the heart muscle and the surrounding medium as a spatially diffuse interface of finite thickness. The chief advantage of this method is to automatically handle the boundary conditions of the voltage in complex geometries without the need to track the location of these boundaries explicitly. The algorithm is shown to converge accurately in nontrivial test geometries with no-flux (zero normal current) boundary conditions as the width of the diffuse interface becomes small compared to the width of the cardiac action potential wavefront. Moreover, the method is illustrated for anatomically realistic models of isolated rabbit and canine ventricles as well as human atria.     

Improvement of ultrasound speckle image velocimetry using image enhancement techniques

Ultrasound-based techniques have been developed and widely used in noninvasive measurement of blood velocity. Speckle image velocimetry (SIV), which applies a cross-correlation algorithm to consecutive B-mode images of blood flow has often been employed owing to its better spatial resolution compared with conventional Doppler-based measurement techniques. The SIV technique utilizes speckles backscattered from red blood cell (RBC) aggregates as flow tracers. Hence, the intensity and size of such speckles are highly dependent on hemodynamic conditions. The grayscale intensity of speckle images varies along the radial direction of blood vessels because of the shear rate dependence of RBC aggregation. This inhomogeneous distribution of echo speckles decreases the signal-to-noise ratio (SNR) of a cross-correlation analysis and produces spurious results. In the present study, image-enhancement techniques such as contrast-limited adaptive histogram equalization (CLAHE), min/max technique, and subtraction of background image (SB) method were applied to speckle images to achieve a more accurate SIV measurement. A mechanical sector ultrasound scanner was used to obtain ultrasound speckle images from rat blood under steady and pulsatile flows. The effects of the image-enhancement techniques on SIV analysis were evaluated by comparing image intensities, velocities, and cross-correlation maps. The velocity profiles and wall shear rate (WSR) obtained from RBC suspension images were compared with the analytical solution for validation. In addition, the image-enhancement techniques were applied to in vivo measurement of blood flow in human vein. The experimental results of both in vitro and in vivo SIV measurements show that the intensity gradient in heterogeneous speckles has substantial influence on the cross-correlation analysis. The image-enhancement techniques used in this study can minimize errors encountered in ultrasound SIV measurement in which RBCs are used as flow tracers instead of exogenous contrast agents.     

Real-time blind deconvolution of retinal images in adaptive optics scanning laser ophthalmoscopy

With the use of adaptive optics (AO), the ocular aberrations can be compensated to get high-resolution image of living human retina. However, the wavefront correction is not perfect due to the wavefront measure error and hardware restrictions. Thus, it is necessary to use a deconvolution algorithm to recover the retinal images. In this paper, a blind deconvolution technique called Incremental Wiener filter is used to restore the adaptive optics confocal scanning laser ophthalmoscope (AOSLO) images. The point-spread function (PSF) measured by wavefront sensor is only used as an initial value of our algorithm. We also realize the Incremental Wiener filter on graphics processing unit (GPU) in real-time. When the image size is 512 × 480 pixels, six iterations of our algorithm only spend about 10 ms. Retinal blood vessels as well as cells in retinal images are restored by our algorithm, and the PSFs are also revised. Retinal images with and without adaptive optics are both restored. The results show that Incremental Wiener filter reduces the noises and improve the image quality.     

A novel ultrasound instrument for investigation of arterial mechanics

The study of arterial mechanics concerns functional characteristics depending on wall elasticity and flow profile. Wall elasticity can be investigated through the estimation of parameters like the arterial distensibility, which is of high clinical interest because of its known correlation not only with the advanced atherosclerotic disease, but also with aging and major risk factors for cardiovascular disease. The flow velocity profile is also clinically relevant, because it modulates endothelial function and can be responsible for the development and distribution of atherosclerotic plaques. A clinically relevant variable extracted from the blood velocity profile is the wall shear rate (WSR), which represents the spatial velocity gradient near the vessel wall. This paper describes an integrated ultrasound system, capable of detecting both the velocity profile and the wall movements in human arteries. It basically consists of a PC add-on board including a single high-speed digital signal processor. This is dedicated to the analysis of echo-signals backscattered from 128 range cells located along the axis of the interrogating ultrasound (US) beam. Echoes generated from the walls (characterized by high amplitudes and low Doppler frequencies) and from red blood cells (characterized by low amplitudes and relatively high Doppler frequencies) are independently processed in real-time. Wall velocity is detected through the autocorrelation algorithm, while blood velocity is investigated through a complete spectral analysis of all signals backscattered by erythrocytes and WSR is extracted from the estimated velocity profile. Preliminary applications of the new system, including the simultaneous analysis of blood flow and arterial wall movement in healthy volunteers and in a diseased patient, are discussed, and first results are presented.     

Analysis of the rogue waves in the blood based on the high-order NLS equations with variable coefficients

The research of rogue waves is an advanced field which has important practical and theoretical significances in mathematics, physics, biological fluid mechanics, oceanography, etc. Using the reductive perturbation theory and long wave approximation, the equations governing the movement of blood vessel walls and the flow of blood are transformed into high-order nonlinear Schrödinger (NLS) equations with variable coefficients. The third-order nonlinear Schrödinger equation is degenerated into a completely integrable Sasa-Satsuma equation (SSE) whose solutions can be used to approximately simulate the real rogue waves in the vessels. For the first time, we discuss the conditions for generating rogue waves in the blood vessels and effects of some physiological parameters on the rogue waves. Based on the traveling wave solutions of the fourth-order nonlinear Schrödinger equation, we analyze the effects of the higher order terms and the initial deformations of the blood vessel on the wave propagation and the displacement of the tube wall. Our results reveal that the amplitude of the rogue waves are proportional to the initial stretching ratio of the tube. The high-order nonlinear and dispersion terms lead to the distortion of the wave, while the initial deformation of the tube wall will influence the wave amplitude and wave steepness.     

Direct measurements of colloidal hydrodynamics near flat boundaries using oscillating optical tweezers

We studied the hydrodynamic interaction between a colloidal particle close to flat rigid boundaries and the surrounding fluid using oscillating optical tweezers. A colloidal particle located near walls provides a model system to study the behavior of more complex systems whose boundaries can be modeled as effective walls, such as a blood tube, cell membrane, and capillary tube in bio-MEMS. In this study, we measure the hydrodynamic interaction directly without using the Stokes–Einstein relation. Two different cases are studied: a colloidal sphere near a single flat wall and a colloidal sphere located at the midplane between two flat walls. The colloidal hydrodynamics is measured as a function of the distance between the particle and the walls, and is compared with the theoretical results from well-defined hydrodynamics approximations.     

Novel methodology for 3D reconstruction of carotid arteries and plaque characterization based upon magnetic resonance imaging carotid angiography data

In this study, we present a novel methodology that allows reliable segmentation of the magnetic resonance images (MRIs) for accurate fully automated three-dimensional (3D) reconstruction of the carotid arteries and semiautomated characterization of plaque type. Our approach uses active contours to detect the luminal borders in the time-of-flight images and the outer vessel wall borders in the T(1)-weighted images. The methodology incorporates the connecting components theory for the automated identification of the bifurcation region and a knowledge-based algorithm for the accurate characterization of the plaque components. The proposed segmentation method was validated in randomly selected MRI frames analyzed offline by two expert observers. The interobserver variability of the method for the lumen and outer vessel wall was -1.60%±6.70% and 0.56%±6.28%, respectively, while the Williams Index for all metrics was close to unity. The methodology implemented to identify the composition of the plaque was also validated in 591 images acquired from 24 patients. The obtained Cohen's k was 0.68 (0.60-0.76) for lipid plaques, while the time needed to process an MRI sequence for 3D reconstruction was only 30 s. The obtained results indicate that the proposed methodology allows reliable and automated detection of the luminal and vessel wall borders and fast and accurate characterization of plaque type in carotid MRI sequences. These features render the currently presented methodology a useful tool in the clinical and research arena.     

Using nonlocal means to separate cardiac and respiration sounds

The paper presents the results of applying nonlocal means (NLMs) approach in the problem of separating respiration and cardiac sounds in a signal recorded on a human chest wall. The performance of the algorithm was tested both by simulated and real signals. As a quantitative efficiency measure of NLM filtration, the angle of divergence between isolated and reference signal was used. It is shown that for a wide range of signal-to-noise ratios, the algorithm makes it possible to efficiently solve this problem of separating cardiac and respiration sounds in the sum signal recorded on a human chest wall.