Automatic tracking of labeled red blood cells in microchannels (original) (raw)
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Manual and Automatic Image Analysis Segmentation Methods for Blood Flow Studies in Microchannels
Micromachines, 2021
In blood flow studies, image analysis plays an extremely important role to examine raw data obtained by high-speed video microscopy systems. This work shows different ways to process the images which contain various blood phenomena happening in microfluidic devices and in microcirculation. For this purpose, the current methods used for tracking red blood cells (RBCs) flowing through a glass capillary and techniques to measure the cell-free layer thickness in different kinds of microchannels will be presented. Most of the past blood flow experimental data have been collected and analyzed by means of manual methods, that can be extremely reliable, but they are highly time-consuming, user-intensive, repetitive, and the results can be subjective to user-induced errors. For this reason, it is crucial to develop image analysis methods able to obtain the data automatically. Concerning automatic image analysis methods for individual RBCs tracking and to measure the well known microfluidic p...
Automatic tracking of red blood cells in micro channels using OpenCV
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The present study aims to developan automatic method able to track red blood cells (RBCs) trajectories flowing through a microchannel using the Open Source Computer Vision (OpenCV). The developed method is based on optical flux calculation assisted by the maximization of the template-matching product. The experimental results show a good functional performance of this method.
Microvascular Research, 1984
In order to study the oxygen supply system within a capillary bed it is desirable to know the lineal density of red blood cells (RBCs) in individual capillaries; viz number of cells per millimeter. We have developed a video computer method for "continuous" measurements of lineal density, based on frame-by-frame analysis of the spatial-average of blood opacity over a selected length of capillary. Each capillary is calibrated separately, in order to determine the relationship between mean opacity and lineal density for that vessel. Since the method does not attempt to detect individual RBCs, it can be applied to capillaries with RBCs which overlap each other to some extent. Also, since the opacity data is normalized with respect to "background" light intensity and "contrast," this technique can be applied to thick tissues such as skeletal muscle. The method has been tested on capillaries in frog sartorius muscle and is able to predict, on average, the number of frog RBCs in an 80-micron length of capillary to +/- one-quarter cell. At present, computation times limit "real time" measurement of lineal density to a sampling rate of 10 sec-1. The data may also be used (1) to compute red cell flux (cells X sec-1), if corresponding velocity measurements are available, and (2) to estimate capillary hematocrit.
Application of image analysis for evaluation of red blood cell dynamics in capillaries
Microvascular Research, 1992
We have devised a method to display and directly evaluate red blood cell (rbc) dynamics in capillaries using the same dual camera intravital video microscopy system employed to determine rbc oxygen saturation (Ellis et al., 1990). Capillary images are recorded on videotape and an interactive graphics system is used for analysis. Data are sampled once a frame for 60 sec using a window (one pixel wide (0.93 micron) and 100 pixels high) positioned along the axis of a capillary. The resulting data are displayed as sequential space-time images 100 pixels high by 300 pixels wide (10 sec). The space-time images thus created represent the dynamics of the rbc's in a single comprehensive static image in which the rbc's appear as dark, diagonal bands separated by light bands representing plasma gaps. From these images one can obtain information on velocity of individual rbc's (micron/sec), lineal density of rbc's (rbc/mm), and rbc supply rate (rbc/sec). This information can be used to delineate the temporal and spatial heterogeneity of hemodynamics in capillary networks. These data can then be combined with coincident data on red blood cell oxygenation to provide a complete picture of oxygen transport in capillaries or it can be used alone as a tool for the evaluation of basic in vivo and in vitro rheological questions.
Flow evaluation of red blood cells in capillaroscopic videos
Proceedings of the 26th IEEE International Symposium on Computer-Based Medical Systems, 2013
We aim at describing a non-parametric approach to evaluate blood cells velocity in oral capillascopic videos. The proposed methodology is based on the application of standard optical flow algorithms and it is part of a general environment to support during the diagnostic process for evaluating peripheral microcirculation in real time. We validated our approach versus handmade measurements provided by physicians. Results on real data pointed out that our system returns an output coherent to these latter observations.
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Cytometry Part A, 2012
The red blood cells (RBCs) population is characterized by a high heterogeneity in membrane area, cellular volume, and mechanical properties, mainly due to the variety of mechanical and chemical stresses that a red cell undergoes in its entire life span. Here, we provide the first simultaneous area and volume measurements of RBCs flowing in microcapillaries, by using high-speed video microscopy imaging and quantitative data processing based on image analysis techniques. Both confined and unbounded flow conditions (depending on the relative size of RBCs and microcapillary diameter) are investigated. The results are compared with micropipette experiments from the literature and data from Coulter counter routine clinical blood tests. Good agreement is found for RBC volume, especially in the case of confined flow conditions. Surface area measurements, which are lacking in the routine clinical test, are of special interest being a potential diagnostic parameter of altered cell deformability and aggregability. Overall, our results provide a novel flow methodology suitable for high-throughput measurements of RBC geometrical parameters, allowing one to overcome the limits of classical static methods, such as micropipette aspiration, which are not suitable for handling a large number of cells. ' 2012 International Society for Advancement of Cytometry Key terms red blood cell volume; red blood cell surface area; mean cell volume; red blood cell distribution width; microcapillary flow; image analysis
Determination of Red Blood Cell Velocity by Video Shuttering and Image Analysis
Annals of Biomedical Engineering, 2000
A novel modification of conventional video imaging techniques has been developed to determine the velocity of red blood cells ͑RBCs͒, which offers compatibility with existing video-based methods for determining blood oxygenation and hemoglobin concentration. Traditional frame-by-frame analysis of video recordings limits the maximum velocity that can be measured for individual cells in vivo to about 2 mm/s. We have extended this range to about 20 mm/s, by electronic shuttering of an intensified charge-coupled device camera to produce multiple images of a single RBC in the same video frame. RBCs were labeled with fluorescein isothiocyanate and the labeled cells ͑FRBCs͒ were used as probes to determine RBC velocities in microvessels of the hamster retractor muscle. Velocity was computed as the product of the distance between centroids of two consecutive image positions of a FRBC and the shuttering frequency of the camera intensifier. In vitro calibrations of the system using FRBC and Sephadex beads coated onto a rotating disk yielded an average coefficient of variation of about 6%. Flow conservation studies at bifurcations indicated that the maximum diameter of microvessels below which all the FRBCs in the lumen could be detected was 50 m. The technique was used to estimate mean-FRBC velocity distributions in vessels with diameters ranging from 8 to 50 m. The mean-FRBC velocity profiles were found to be blunter than would be expected for Poiseuille flow. Single FRBCs tracked along an unbranched arteriole exhibited significant temporal variations in velocity. © 1999 Biomedical Engineering Society. ͓S0090-6964͑99͒02103-7͔
Blood Flow Analysis and Red Blood Cell Aggregation Investigation
2013
This work aims to develop a method to quantitatively analyze red blood cell (RBC) aggregates under controlled flow conditions, based on image processing. The set up consists of RBC suspensions entrained by a second fluid in a 150x33 μm microchannel. The experiments are performed by varying the hematocrit (10, 15 & 20%) and the flow rate (Q=5 & 10 μl/hr). The flow is visualized using a high speed camera coupled to a micro Particle Image Velocimetry (μPIV) system. Videos obtained with the high speed camera are processed using a MATLAB program to detect RBC aggregates based on the images intensities. An average aggregate size has been determined for each of the shear rates and hematocrits. The aggregates are shown to be larger at low flow rates and high hematocrits.
Semi-Automatic Red Blood Cells Counting in Microscopic Digital Images
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The main purpose of this study is to employ the modern technologies and techniques to semi-automate the quantification process of the Red Blood Cells in Microscopic thin blood smear digital images. The process needs to be more accurate, efficient and universal then the currently practiced methods. The study considers the process to be semi-automated for two reasons, i.e. due to the critical aspect life and due to the diverse nature of the Red Blood Cells in cluster formation. The Methodology of this study involved interactive simple cuts and morphological operations for splitting clusters of Red Blood Cells while counting is carried out through labeling matrix. The Red Blood Cells counting is part of the complete blood count test and is frequently suggested by the Physician to know the number of Red Blood Cells in the patient’s body. The proposed method considers for counting process of the Red Blood Cells first split the clusters and then count the Red Blood Cells. The proposed me...