A hybrid of light-field and light-sheet imaging to study myocardial function and intracardiac blood flow during zebrafish development

Biomechanical forces intimately contribute to cardiac morphogenesis. However, volumetric imaging to investigate the cardiac mechanics with high temporal and spatial resolution remains an imaging challenge. We hereby integrated light-field microscopy (LFM) with light-sheet fluorescence microscopy (LSFM), coupled with a retrospective gating method, to simultaneously access myocardial contraction and intracardiac blood flow at 200 volumes per second. While LSFM allows for the reconstruction of the myocardial function, LFM enables instantaneous acquisition of the intracardiac blood cells traversing across the valves. We further adopted deformable image registration to quantify the ventricular wall displacement and particle tracking velocimetry to monitor intracardiac blood flow. The integration of LFM and LSFM enabled the time-dependent tracking of the individual blood cells and the differential rates of segmental wall displacement during a cardiac cycle. Taken together, we demonstrated a hybrid system, coupled with our image analysis pipeline, to simultaneously capture the myocardial wall motion with intracardiac blood flow during cardiac development.     

3-D image analysis system and megakaryocyte quantitation

A quasi-automatic computer image analysis system has been developed for 3-D reconstruction of stained serial sections and implemented on an IBAS system. Some new automatic image analysis techniques have been designed and incorporated into the system. For image segmentation, a transition region determination based thresholding method is introduced. Neither histogram calculation nor empirical parameters are needed in the automatic threshold selection. A two step 3-D reconstruction procedure--symbolic and pictorial reconstructions--is designed to improve the flexibility and the computational capability of the system. The global level registration and local level registration are separated. The former consists of establishing the relationship among a large numbers of profile pairs dispersed in adjacent sections. A pattern matching method based on pattern recognition principles is devised to exploit the information about the statistical character of mismatch caused by deformation of sections and about the relationship of nearby objects. For the latter, an equivalent elliptical approximation method based on the physical theory of the rotation of rigid bodies is proposed. The system has been used for 3-D reconstruction and quantitation of megakaryocytes in human bone marrow tissue. Features about individual 3-D megakaryocyte cell and the spatial distribution of megakaryocytes are determined. The latter is a new contribution to megakaryocyte quantitation and is not possible by using conventional stereologic techniques. These experimental results have demonstrated the ability of the system to perform quantitative analysis.     

基于图像处理的血液细胞特征提取

利用数学形态学知识和图像处理方法,对缺铁性贫血的血液显微图像进行了分析,编制了相应的计算程序,对选取的区域内细胞的个数、半径和面积等重要参数进行了统计和处理,这对进一步研究细胞及其组织变化、医学临床诊断等问题,具有一定的指导意义。     

Enhancing vascular visualization in laser speckle contrast imaging of blood flow using multi‐focus image fusion

Laser speckle contrast imaging (LSCI) is a full‐field optical imaging method for monitoring blood flow and vascular morphology with high spatiotemporal resolution. However, due to the limited depth of field of optical system, it is difficult to capture a clear blood flow image with all blood vessels focused, especially for the non‐planar biological tissues. In this study, a multi‐focus image fusion method based on contourlet transform is introduced to reduce the misfocus effects in LSCI. The experimental results suggest that this method can provide an all‐in‐focus blood flow image, which is convenient to observe the blood vessels.      

一种显微图像的拼接方法

描述了一种显微图像拼接的方法,共包括特征检测、特征匹配、空间坐标转换和图像混合等四个步骤。实验结果显示本方法对重叠面积在50％以上的显微图像,能够进行拼接并且都没有出现明显的缝隙、错位、变形、图像模糊、图像重影等错误。     

Optical flow sensor for continuous invasive measurement of blood flow velocity

Continuous monitoring of intrapulse measurement of blood flow in humans is currently not achievable with clinically available instruments. In this paper, we demonstrate a method of measuring the instantaneous variations in flow during pulsatile blood flow with an optical flow sensor comprising a fiber Bragg grating sensor and illumination from a 565 nm Light‐Emitting‐Diode. The LED illumination heats the blood and fluctuations in temperature, due to variations in flow, are detected by the fiber sensor. A set of experiments at different flow rates (20 to 900 mL/min) are performed in a simulated cardiac circulation setup with pulsatile flow. Data are compared with an in‐line time of flight ultrasound flow sensor. Our results show that the optical and ultrasonic signals correlate with Pearson coefficients ranging from ?0.83 to ?0.98, dependent on the pulsatile frequency. Average flow determined by ultrasound and the optical fiber sensor showed a parabolic relationship with R² = 0.99. An abrupt step change in flow induced by occlusion and release of the circuit tubing demonstrated that the optical fiber and ultrasound sensor had similar response. The method described is capable of intrapulse blood flow measurement under pulsatile flow conditions, with potential applications in medicine where continuous blood flow sensing is desired.     

Homographic Patch Feature Transform: A Robustness Registration for Gastroscopic Surgery

Image registration is a key component of computer assistance in image guided surgery, and it is a challenging topic in endoscopic environments. In this study, we present a method for image registration named Homographic Patch Feature Transform (HPFT) to match gastroscopic images. HPFT can be used for tracking lesions and augmenting reality applications during gastroscopy. Furthermore, an overall evaluation scheme is proposed to validate the precision, robustness and uniformity of the registration results, which provides a standard for rejection of false matching pairs from corresponding results. Finally, HPFT is applied for processing in vivo gastroscopic data. The experimental results show that HPFT has stable performance in gastroscopic applications.     

Electrical impedance assays of blood cells

In this review, the capability of electrical impedance spectroscopy analysis of blood cells, especially for red blood cells is presented, highlighting its large area of related biomedical relevance. The method is briefly introduced and basic theoretical aspects are discussed by considering both phenomenological (e.g. equivalent circuit) and microscopic approaches. The latter include a comparative analysis of the relevance of considering real shape (consistent with microscopic observations) versus spheroidal approximations (prolate and oblate spheroids) with the same surface and volume concentration. We show that while ellipsoidal approximation is fairly good for randomly oriented cells, it is quite poor whenever oriented cells are measured. The voluminous literature on the electrical analysis of blood cells is reviewed to stress the most promising biomedical applications of the method either per se or in combination with complementary e.g. (micro) fluidic approaches.     

共聚焦激光检眼镜下眼底图像的非特征配准约束模型研究

研究共聚焦激光检眼镜下不基于特征提取的眼底图像自动配准方法中的运动约束模型,从成像机理上分析共聚焦激光检眼镜下图像对间的运动模式,并分析比较多种实际全局运动模型约束下的配准精度和效率,进而给出一种由粗到细的复合约束模型对眼底图像进行配准。实验结果证实了该模型效果良好。     

Functional morphology and patterns of blood flow in the heart of Python regius

Brightness‐modulated ultrasonography, continuous‐wave Doppler, and pulsed‐wave Doppler‐echocardiography were used to analyze the functional morphology of the undisturbed heart of ball pythons. In particular, the action of the muscular ridge and the atrio‐ventricular valves are key features to understand how patterns of blood flow emerge from structures directing blood into the various chambers of the heart. A step‐by‐step image analysis of echocardiographs shows that during ventricular diastole, the atrio‐ventricular valves block the interventricular canals so that blood from the right atrium first fills the cavum venosum, and blood from the left atrium fills the cavum arteriosum. During diastole, blood from the cavum venosum crosses the muscular ridge into the cavum pulmonale. During middle to late systole the muscular ridge closes, thus prohibiting further blood flow into the cavum pulmonale. At the same time, the atrio‐ventricular valves open the interventricular canal and allow blood from the cavum arteriosum to flow into the cavum venosum. In the late phase of ventricular systole, all blood from the cavum pulmonale is pressed into the pulmonary trunk; all blood from the cavum venosum is pressed into both aortas. Quantitative measures of blood flow volume showed that resting snakes bypass the pulmonary circulation and shunt about twice the blood volume into the systemic circulation as into the pulmonary circulation. When digesting, the oxygen demand of snakes increased tremendously. This is associated with shunting more blood into the pulmonary circulation. The results of this study allow the presentation of a detailed functional model of the python heart. They are also the basis for a functional hypothesis of how shunting is achieved. Further, it was shown that shunting is an active regulation process in response to changing demands of the organism (here, oxygen demand). Finally, the results of this study support earlier reports about a dual pressure circulation in Python regius. J. Morphol., 2009. © 2008 Wiley‐Liss, Inc.     

Nocturnal variations in human lower leg subcutaneous blood flow related to sleep stages.

Nocturnal subcutaneous adipose tissue blood flow rate was measured in the lower legs of 10 normal human subjects together with systemic arterial blood pressure, heart rate, and registration of sleep stages under ambulatory conditions. The 133Xe washout technique, portable CdTe(Cl) detectors, and a portable data storage unit were used for measurement of blood flow rates. The sleep recordings were performed with a portable computerized sleep analysis system. In accordance with the results of previous studies, a hyperemic blood flow rate phase (mean increase 140%) for 100 min was observed approximately 60 min after the subjects went to bed. The moment of onset of the hyperemic phase was closely related to the moment of onset of the first episode of deep sleep (stages 3 and 4). There was a significant (P < 0.01) overrepresentation of deep sleep in the hyperemic phase compared with adjacent phases, and rapid-eye-movement sleep predominantly occurred in the latter part of the night, when the subcutaneous blood flow rate was stable. The results of the present study are in accordance with current theories of the interrelationship between the thermoregulatory and the arousal state control systems and, thus, might suggest that the nightly subcutaneous hyperemia represents a thermoregulatory effector mechanism.     

Performance of a cost‐effective and automated blood counting system for resource‐limited settings operated by trained and untrained users

Current flow‐based blood counting devices require expensive and centralized medical infrastructure and are not appropriate for field use. In this article we report a streamlined, easy‐to‐use method to count red blood cells (RBC), white blood cells (WBC), platelets (PLT) and 3‐part WBC differential through a cost‐effective and automated image‐based blood counting system. The approach consists of using a compact, custom‐built microscope with large field‐of‐view to record bright‐field and fluorescence images of samples that are diluted with a single, stable reagent mixture and counted using automatic algorithms. Sample collection utilizes volume‐controlled capillary tubes, which are then dropped into a premixed, shelf‐stable solution to stain and dilute in a single step. Sample measurement and analysis are fully automated, requiring no input from the user. Cost of the system is minimized through the use of custom‐designed motorized components. We compare the performance of our system, as operated by trained and untrained users, to the clinical gold standard on 120 adult blood samples, demonstrating agreement within Clinical Laboratory Improvement Amendments guidelines, with no statistical difference in performance among different operator groups. The system's cost‐effectiveness, automation and performance indicate that it can be successfully translated for use in low‐resource settings where central hematology laboratories are not accessible.      

RAMTaB: robust alignment of multi-tag bioimages

Background

In recent years, new microscopic imaging techniques have evolved to allow us to visualize several different proteins (or other biomolecules) in a visual field. Analysis of protein co-localization becomes viable because molecules can interact only when they are located close to each other. We present a novel approach to align images in a multi-tag fluorescence image stack. The proposed approach is applicable to multi-tag bioimaging systems which (a) acquire fluorescence images by sequential staining and (b) simultaneously capture a phase contrast image corresponding to each of the fluorescence images. To the best of our knowledge, there is no existing method in the literature, which addresses simultaneous registration of multi-tag bioimages and selection of the reference image in order to maximize the overall overlap between the images.

Methodology/Principal Findings

We employ a block-based method for registration, which yields a confidence measure to indicate the accuracy of our registration results. We derive a shift metric in order to select the Reference Image with Maximal Overlap (RIMO), in turn minimizing the total amount of non-overlapping signal for a given number of tags. Experimental results show that the Robust Alignment of Multi-Tag Bioimages (RAMTaB) framework is robust to variations in contrast and illumination, yields sub-pixel accuracy, and successfully selects the reference image resulting in maximum overlap. The registration results are also shown to significantly improve any follow-up protein co-localization studies.

Conclusions

For the discovery of protein complexes and of functional protein networks within a cell, alignment of the tag images in a multi-tag fluorescence image stack is a key pre-processing step. The proposed framework is shown to produce accurate alignment results on both real and synthetic data. Our future work will use the aligned multi-channel fluorescence image data for normal and diseased tissue specimens to analyze molecular co-expression patterns and functional protein networks.     

使用Radon变换进行二维MRI图像配准

使用了一种基于Radon变换的技术来进行二维的MRI图像配准。MRI的图像配准一般使用灰度配准,而Radon变换一般用于CT图像的重建,虽然现已经存在使用Radon变换进行图像配准,但是比较繁琐,我们对这一配准算法进行了简化。     

Age-related characteristics of relationships between brain blood flow, liquor dynamics and biomechanical properties of human cranium

The peculiarities of relationships between changes of cerebral blood flow, intracranial liquor dynamics and skull biomechanics in humans were studied in an age aspect. For this aim, a non-invasive method was proposed based on concomitant registration of rheoencephalogram and transcranial dopplerogram and evaluation of relationships between intracranial volume and pulse pressure changes (P-V index). The data obtained were analyzed by pattern-phase computer processing and compared with the blood flow parameters. The investigation was carried out on healthy volunteers of 18-25, 40-50 and 65-75 years of age. It was shown that circulatory-metabolic supplying of human brain was supported by such factors as volume brain blood flow, intracranial liquor dynamics in cooperation with skull biomechanics. The cerebral blood flow decrease at aging could be compensated by increase of the reserve-compensatory abilities of the system of cranial-spinal liquor dynamics.     

Multiresolution image registration for two-dimensional gel electrophoresis

In proteomic research, two-dimensional electrophoresis (2-D) is an important tool for investigating differential patterns of qualitative and quantitative protein expression. The strength of the technique is due to its unrivalled power of being able to separate simultaneously thousands of proteins. The key to the comparison of 2-D protein profiles, however, lies in the use of a fast and robust image matching process which is essential to the subsequent quantification procedure. To satisfy the growing demand for a robust and fully automatic method of matching 2-D gel protein separation profiles, we describe in this paper a novel registration technique based on image intensity distribution rather than selected features. The method uses a multiresolution representation of the gel profiles and exploits the fact that coarse approximations to the optimal matching can be extracted efficiently from low-resolution images. This permits the removal of misalignments at different scales in a systematic manner and the strength of the new method has been confirmed by a double blind trial of 111 2-D gel pairs. The proposed method requires neither landmarks nor an a priori image alignment, and takes about five seconds for processing a typical gel pair on a standard personal computer.     

Image Registration Algorithm Using Mexican Hat Function-Based Operator and Grouped Feature Matching Strategy

Feature detection and matching are crucial for robust and reliable image registration. Although many methods have been developed, they commonly focus on only one class of image features. The methods that combine two or more classes of features are still novel and significant. In this work, methods for feature detection and matching are proposed. A Mexican hat function-based operator is used for image feature detection, including the local area detection and the feature point detection. For the local area detection, we use the Mexican hat operator for image filtering, and then the zero-crossing points are extracted and merged into the area borders. For the feature point detection, the Mexican hat operator is performed in scale space to get the key points. After the feature detection, an image registration is achieved by using the two classes of image features. The feature points are grouped according to a standardized region that contains correspondence to the local area, precise registration is achieved eventually by the grouped points. An image transformation matrix is estimated by the feature points in a region and then the best one is chosen through competition of a set of the transformation matrices. This strategy has been named the Grouped Sample Consensus (GCS). The GCS has also ability for removing the outliers effectively. The experimental results show that the proposed algorithm has high registration accuracy and small computational volume.     

Quantitative Analysis of Dynamic Association in Live Biological Fluorescent Samples

Determining vesicle localization and association in live microscopy may be challenging due to non-simultaneous imaging of rapidly moving objects with two excitation channels. Besides errors due to movement of objects, imaging may also introduce shifting between the image channels, and traditional colocalization methods cannot handle such situations. Our approach to quantifying the association between tagged proteins is to use an object-based method where the exact match of object locations is not assumed. Point-pattern matching provides a measure of correspondence between two point-sets under various changes between the sets. Thus, it can be used for robust quantitative analysis of vesicle association between image channels. Results for a large set of synthetic images shows that the novel association method based on point-pattern matching demonstrates robust capability to detect association of closely located vesicles in live cell-microscopy where traditional colocalization methods fail to produce results. In addition, the method outperforms compared Iterated Closest Points registration method. Results for fixed and live experimental data shows the association method to perform comparably to traditional methods in colocalization studies for fixed cells and to perform favorably in association studies for live cells.     

Physical Constraint Finite Element Model for Medical Image Registration

Due to being derived from linear assumption, most elastic body based non-rigid image registration algorithms are facing challenges for soft tissues with complex nonlinear behavior and with large deformations. To take into account the geometric nonlinearity of soft tissues, we propose a registration algorithm on the basis of Newtonian differential equation. The material behavior of soft tissues is modeled as St. Venant-Kirchhoff elasticity, and the nonlinearity of the continuum represents the quadratic term of the deformation gradient under the Green- St.Venant strain. In our algorithm, the elastic force is formulated as the derivative of the deformation energy with respect to the nodal displacement vectors of the finite element; the external force is determined by the registration similarity gradient flow which drives the floating image deforming to the equilibrium condition. We compared our approach to three other models: 1) the conventional linear elastic finite element model (FEM); 2) the dynamic elastic FEM; 3) the robust block matching (RBM) method. The registration accuracy was measured using three similarities: MSD (Mean Square Difference), NC (Normalized Correlation) and NMI (Normalized Mutual Information), and was also measured using the mean and max distance between the ground seeds and corresponding ones after registration. We validated our method on 60 image pairs including 30 medical image pairs with artificial deformation and 30 clinical image pairs for both the chest chemotherapy treatment in different periods and brain MRI normalization. Our method achieved a distance error of 0.320±0.138 mm in x direction and 0.326±0.111 mm in y direction, MSD of 41.96±13.74, NC of 0.9958±0.0019, NMI of 1.2962±0.0114 for images with large artificial deformations; and average NC of 0.9622±0.008 and NMI of 1.2764±0.0089 for the real clinical cases. Student’s t-test demonstrated that our model statistically outperformed the other methods in comparison (p-values <0.05).     

A Practical Approach Based on Analytic Deformable Algorithm for Scenic Image Registration

Background

Image registration is to produce an entire scene by aligning all the acquired image sequences. A registration algorithm is necessary to tolerance as much as possible for intensity and geometric variation among images. However, captured image views of real scene usually produce unexpected distortions. They are generally derived from the optic characteristics of image sensors or caused by the specific scenes and objects.

Methods and Findings

An analytic registration algorithm considering the deformation is proposed for scenic image applications in this study. After extracting important features by the wavelet-based edge correlation method, an analytic registration approach is then proposed to achieve deformable and accurate matching of point sets. Finally, the registration accuracy is further refined to obtain subpixel precision by a feature-based Levenberg-Marquardt (FLM) method. It converges evidently faster than most other methods because of its feature-based characteristic.

Conclusions

We validate the performance of proposed method by testing with synthetic and real image sequences acquired by a hand-held digital still camera (DSC) and in comparison with an optical flow-based motion technique in terms of the squared sum of intensity differences (SSD) and correlation coefficient (CC). The results indicate that the proposed method is satisfactory in the registration accuracy and quality of DSC images.