CN114587324A - System and method for non-invasive analysis of blood flow velocity and components - Google Patents
System and method for non-invasive analysis of blood flow velocity and components Download PDFInfo
- Publication number
- CN114587324A CN114587324A CN202011415191.XA CN202011415191A CN114587324A CN 114587324 A CN114587324 A CN 114587324A CN 202011415191 A CN202011415191 A CN 202011415191A CN 114587324 A CN114587324 A CN 114587324A
- Authority
- CN
- China
- Prior art keywords
- image
- blood
- blood flow
- sequence
- capillary
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 230000017531 blood circulation Effects 0.000 title claims abstract description 126
- 238000000034 method Methods 0.000 title claims abstract description 40
- 238000004458 analytical method Methods 0.000 title claims description 17
- 210000004369 blood Anatomy 0.000 claims abstract description 66
- 239000008280 blood Substances 0.000 claims abstract description 66
- 210000000265 leukocyte Anatomy 0.000 claims abstract description 35
- 239000000203 mixture Substances 0.000 claims abstract description 34
- 210000003743 erythrocyte Anatomy 0.000 claims abstract description 12
- QVGXLLKOCUKJST-UHFFFAOYSA-N atomic oxygen Chemical compound [O] QVGXLLKOCUKJST-UHFFFAOYSA-N 0.000 claims abstract description 8
- 238000004820 blood count Methods 0.000 claims abstract description 8
- 229910052760 oxygen Inorganic materials 0.000 claims abstract description 8
- 239000001301 oxygen Substances 0.000 claims abstract description 8
- WQZGKKKJIJFFOK-GASJEMHNSA-N Glucose Natural products OC[C@H]1OC(O)[C@H](O)[C@@H](O)[C@@H]1O WQZGKKKJIJFFOK-GASJEMHNSA-N 0.000 claims abstract description 6
- 239000008103 glucose Substances 0.000 claims abstract description 6
- 238000003384 imaging method Methods 0.000 claims description 27
- 238000012545 processing Methods 0.000 claims description 26
- 239000000126 substance Substances 0.000 claims description 9
- 230000008569 process Effects 0.000 claims description 5
- 230000002452 interceptive effect Effects 0.000 claims description 4
- 238000004891 communication Methods 0.000 claims description 3
- 238000009499 grossing Methods 0.000 claims description 2
- 230000003287 optical effect Effects 0.000 abstract description 7
- 238000005286 illumination Methods 0.000 abstract description 6
- 230000003993 interaction Effects 0.000 abstract description 2
- 239000012472 biological sample Substances 0.000 description 10
- 210000001519 tissue Anatomy 0.000 description 10
- 239000000306 component Substances 0.000 description 9
- 238000005259 measurement Methods 0.000 description 6
- 238000009534 blood test Methods 0.000 description 5
- 238000000605 extraction Methods 0.000 description 5
- 230000005484 gravity Effects 0.000 description 5
- 239000000523 sample Substances 0.000 description 5
- 210000000601 blood cell Anatomy 0.000 description 4
- 239000012503 blood component Substances 0.000 description 4
- 238000010586 diagram Methods 0.000 description 4
- 238000010241 blood sampling Methods 0.000 description 3
- 239000000284 extract Substances 0.000 description 3
- 241001465754 Metazoa Species 0.000 description 2
- 206010028980 Neoplasm Diseases 0.000 description 2
- 238000002512 chemotherapy Methods 0.000 description 2
- 201000010099 disease Diseases 0.000 description 2
- 208000037265 diseases, disorders, signs and symptoms Diseases 0.000 description 2
- 210000000624 ear auricle Anatomy 0.000 description 2
- 210000002615 epidermis Anatomy 0.000 description 2
- 230000036541 health Effects 0.000 description 2
- 208000014951 hematologic disease Diseases 0.000 description 2
- 238000010801 machine learning Methods 0.000 description 2
- 230000010287 polarization Effects 0.000 description 2
- 238000001959 radiotherapy Methods 0.000 description 2
- 230000001360 synchronised effect Effects 0.000 description 2
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 description 2
- 241000894006 Bacteria Species 0.000 description 1
- 208000035143 Bacterial infection Diseases 0.000 description 1
- 241000700605 Viruses Species 0.000 description 1
- 208000022362 bacterial infectious disease Diseases 0.000 description 1
- 210000003651 basophil Anatomy 0.000 description 1
- 210000001772 blood platelet Anatomy 0.000 description 1
- 210000004027 cell Anatomy 0.000 description 1
- 210000003855 cell nucleus Anatomy 0.000 description 1
- 238000003745 diagnosis Methods 0.000 description 1
- 238000007865 diluting Methods 0.000 description 1
- 238000003255 drug test Methods 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 239000003792 electrolyte Substances 0.000 description 1
- 210000003979 eosinophil Anatomy 0.000 description 1
- 210000004905 finger nail Anatomy 0.000 description 1
- 230000006870 function Effects 0.000 description 1
- 208000018706 hematopoietic system disease Diseases 0.000 description 1
- 208000026278 immune system disease Diseases 0.000 description 1
- 238000001727 in vivo Methods 0.000 description 1
- 238000002372 labelling Methods 0.000 description 1
- 210000004698 lymphocyte Anatomy 0.000 description 1
- 239000012528 membrane Substances 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 210000001616 monocyte Anatomy 0.000 description 1
- 210000000214 mouth Anatomy 0.000 description 1
- 210000000440 neutrophil Anatomy 0.000 description 1
- 150000002894 organic compounds Chemical class 0.000 description 1
- 210000005259 peripheral blood Anatomy 0.000 description 1
- 239000011886 peripheral blood Substances 0.000 description 1
- 239000010665 pine oil Substances 0.000 description 1
- 230000001737 promoting effect Effects 0.000 description 1
- 102000004169 proteins and genes Human genes 0.000 description 1
- 108090000623 proteins and genes Proteins 0.000 description 1
- 230000005855 radiation Effects 0.000 description 1
- -1 red blood cells Substances 0.000 description 1
- 230000000717 retained effect Effects 0.000 description 1
- 238000005070 sampling Methods 0.000 description 1
- 238000012360 testing method Methods 0.000 description 1
- 229940126585 therapeutic drug Drugs 0.000 description 1
- 230000036962 time dependent Effects 0.000 description 1
Images
Classifications
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/02—Detecting, measuring or recording pulse, heart rate, blood pressure or blood flow; Combined pulse/heart-rate/blood pressure determination; Evaluating a cardiovascular condition not otherwise provided for, e.g. using combinations of techniques provided for in this group with electrocardiography or electroauscultation; Heart catheters for measuring blood pressure
- A61B5/026—Measuring blood flow
- A61B5/0261—Measuring blood flow using optical means, e.g. infrared light
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/145—Measuring characteristics of blood in vivo, e.g. gas concentration, pH value; Measuring characteristics of body fluids or tissues, e.g. interstitial fluid, cerebral tissue
- A61B5/14532—Measuring characteristics of blood in vivo, e.g. gas concentration, pH value; Measuring characteristics of body fluids or tissues, e.g. interstitial fluid, cerebral tissue for measuring glucose, e.g. by tissue impedance measurement
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/145—Measuring characteristics of blood in vivo, e.g. gas concentration, pH value; Measuring characteristics of body fluids or tissues, e.g. interstitial fluid, cerebral tissue
- A61B5/14546—Measuring characteristics of blood in vivo, e.g. gas concentration, pH value; Measuring characteristics of body fluids or tissues, e.g. interstitial fluid, cerebral tissue for measuring analytes not otherwise provided for, e.g. ions, cytochromes
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/145—Measuring characteristics of blood in vivo, e.g. gas concentration, pH value; Measuring characteristics of body fluids or tissues, e.g. interstitial fluid, cerebral tissue
- A61B5/1455—Measuring characteristics of blood in vivo, e.g. gas concentration, pH value; Measuring characteristics of body fluids or tissues, e.g. interstitial fluid, cerebral tissue using optical sensors, e.g. spectral photometrical oximeters
- A61B5/14551—Measuring characteristics of blood in vivo, e.g. gas concentration, pH value; Measuring characteristics of body fluids or tissues, e.g. interstitial fluid, cerebral tissue using optical sensors, e.g. spectral photometrical oximeters for measuring blood gases
Abstract
The invention discloses a system and a method for non-invasively analyzing blood flow velocity and components. The system and method obtains a sequence of optical images of the capillary vessel, analyzes discrete blood flow events occurring in the sequence of images and the interaction between the blood and the illumination light to measure blood flow rate and blood composition, such as white blood cell count, red blood cell content, blood glucose concentration, blood oxygen concentration.
Description
Technical Field
The invention belongs to the technical field of medical examination, and particularly relates to a system and a method for non-invasively analyzing blood flow rate and blood components.
Background
Blood is composed of plasma, which is composed of water, proteins, electrolytes and organic compounds, and blood cells, which are classified into three types of cells, red blood cells, white blood cells and platelets. The leukocytes are classified into neutrophils, eosinophils, basophils, monocytes and lymphocytes. The white blood cells are spherical, colorless, have cell nucleuses and are blood cells with larger volumes in the blood cells. The main functions of leukocytes are to phagocytize bacteria and defend diseases. If the number of leukocytes in the body is higher than normal, it is likely due to bacterial infection or hematopoietic disease; on the other hand, when a body is infected with a virus, exposed to radiation for a long period of time, receives chemotherapy and radiation therapy for tumors, undergoes an immune system disease or a hematologic disease, etc., the number of leukocytes may be lower than normal. The White Blood Cell (WBC) count per unit volume is an important index in the fields of health assessment, disease diagnosis and treatment, therapeutic drug testing, and the like. Because white blood cells are bulky, they can transiently block or roll within capillaries as they pass through capillaries in the body, such as those in the epidermis near the finger nails. When a capillary vessel is illuminated by a light source with a specific wavelength, the optical image of the capillary vessel exhibits a discontinuous phenomenon, i.e., discontinuous blood flow events. Analysis of the discrete blood flow events can extract information on the white blood cells in the blood. In addition, components in blood, such as red blood cells, can absorb and scatter incident light, and concentration information of substances in blood, such as red blood cells, blood sugar, blood oxygen and the like, can be inferred by extracting optical signals mainly comprising light and blood.
In general, blood tests measure the components of blood by obtaining a blood sample (venous blood or peripheral blood) from a human body, diluting the blood sample, labeling the blood sample, and sequentially separating the blood sample. Since sampling and analysis require professional operations, blood tests are usually performed in hospitals or special test sites. When the blood cell information of a patient needs to be known frequently, such as chemotherapy, radiotherapy and blood patient treatment of a tumor patient, the patient will undergo frequent blood sampling operation, which brings great inconvenience to the patient. Moreover, when blood tests are performed on children, the blood sampling process also brings certain pain to patients because the children may not be matched with the blood tests. In addition, in health management, it is required to frequently monitor blood information of a user, and it is also required to acquire blood information of a human body in a non-medical environment.
In order to avoid the pain and inconvenience of blood sampling process in blood test, the present invention aims to provide a system and method for obtaining optical image sequence of capillary vessel, analyzing discontinuous blood flow events appearing in the image sequence and the interaction between blood and illumination light to measure blood flow rate and blood components, such as white blood cell count, red blood cell content, blood glucose concentration and blood oxygen concentration, so as to meet the requirements of specific people.
Disclosure of Invention
The invention aims to provide a system and a method for non-invasively analyzing blood flow rate and components, such as flow rate, white blood cell count, red blood cell content, blood glucose concentration and blood oxygen concentration, so as to meet the requirement of frequently, timely and non-invasively obtaining blood component information of a human body.
The invention discloses a method for non-invasively analyzing blood flow velocity and components, which comprises the following steps: 1) collecting a capillary vessel image sequence and extracting the position and the shape size of a capillary vessel on a reference image; 2) determining from each image of the sequence of images the position of the capillary vessel in the reference image coordinate system; 3) extracting pixel values of a capillary vessel position in each image to form a time sequence and determining the number and type of discontinuous blood flow events; 4) calculating the center of gravity of a region of the capillary vessel in each image and determining the blood flow velocity; 5) determining an estimate of the discrete blood flow events based on the calculated number of discrete blood flow events, the blood flow velocity, the size of the capillaries, and the imaging parameters, the estimate representing the number of discrete blood flow events occurring per unit volume of blood; 6) the estimates of the discrete blood flow events from all capillaries are combined as a single measurement of the discrete blood flow events.
In the step 1), some embodiments respectively irradiate the biological tissue site where the capillary vessel is located with two light sources with different wavelengths and sequentially acquire images. At this time, the step 1 further comprises 1) acquiring a first capillary vessel image a illuminated by a first wavelength light source in a living body with the microscopic imaging unit; 2) acquiring a capillary vessel image sequence B illuminated by a second wavelength light source in a living body by using a microscopic imaging unit; 3) taking one image in the image sequence B as a reference image, carrying out position calibration (registration) on the image A and the reference image, calculating the difference between the reference image and the calibrated image, and taking a threshold value to obtain the position coordinates, the diameter and the length of the pixel occupied by the capillary vessel in the reference image coordinates; 4) in the difference image between the reference image and the calibrated image, the concentration of a substance in the blood is calibrated and measured by the pixel values located at the capillary positions. Such substances include, but are not limited to, red blood cell concentration, red blood cell count, blood oxygen concentration, and blood glucose concentration. Further, the difference image may be a logarithmic difference of pixel values in the reference image and the calibrated image.
In the above method for non-invasively analyzing blood flow rate and composition, the discontinuous blood flow events include white blood cell flow events through capillaries, and the counting and classifying of the discontinuous blood flow events in capillaries includes counting and classifying the number and type of white blood cells.
The invention discloses a system for non-invasively analyzing blood flow rate and components, which comprises the following components:
the microscopic imaging unit consists of a microscopic objective, a digital camera and at least one wavelength light source, wherein the light source illuminates capillary vessels in biological tissues in a field of view of the microscopic objective, and the digital camera acquires images according to instructions when the light source illuminates the capillary vessels;
the system comprises a storage and processing unit consisting of a memory and a processing controller, wherein the memory stores an image acquisition instruction, a processing instruction and a communication instruction, the processing controller analyzes an acquired image according to the processing instruction, extracts the position and other characteristic information of a capillary vessel, determines the information of discontinuous blood flow events in the capillary vessel, estimates the average flow velocity of blood in the capillary vessel, calculates the frequency of the discontinuous blood flow events in unit volume of blood according to imaging parameters, and sends the estimation result to a server, a personal device and a display unit;
and the display unit is used as an interactive interface between the user and the equipment and displays the image acquisition process and the measurement result.
In some embodiments, the microscopic imaging unit employs two different wavelength light sources. The system firstly uses a first wavelength light source to illuminate a capillary vessel in a microscope objective field of view, and a digital camera acquires a first image A of the capillary vessel; then, illuminating the capillary vessel in the field of view of the microscope objective by using a second wavelength light source, and acquiring an image sequence B of the capillary vessel changing along with time by using a digital camera; after the image acquisition is completed, the storage and processing unit calculates the blood flow rate and the blood components by adopting a method comprising the following steps: 1) taking one image in the image sequence B as a reference image, carrying out position calibration (registration) on the image A and the reference image, calculating the difference between the reference image and the calibrated image, and taking a threshold value to obtain the position coordinate, the diameter and the length of a pixel occupied by the capillary vessel in the reference image coordinate; 2) measuring the concentration of a substance in the blood using the pixel values located within the capillary vessel in the difference map of the reference image and the calibrated image; 3) determining a capillary vessel from the sequence of images and calibrating its coordinates to a location in a reference image coordinate system; 4) extracting pixel values of a capillary vessel position in each image to form a time series and determining the number of discontinuous blood flow events; 5) calculating the center of gravity of a region of the capillary vessel in each image and determining the blood flow velocity; 6) determining an estimate of the discrete blood flow events based on the calculated number of discrete blood flow events, the blood flow velocity, the size of the capillaries, and the imaging parameters, the estimate representing the number of discrete blood flow events occurring per unit volume of blood; 7) the estimates of the discrete blood flow events from all capillaries are combined as a single measurement of the discrete blood flow events.
In some embodiments, the microscopic imaging unit illuminates the capillary vessels in the field of view of the microscopic objective with a light source of one wavelength, and the digital camera acquires a sequence of two-dimensional images of the capillary vessels over time according to the instructions; the storage and processing unit calculates the blood flow rate and composition using a method comprising the steps of: 1) selecting one image in the image sequence as a reference image, extracting the position coordinates of pixels occupied by the capillary vessels in the reference image coordinates by means of feature extraction, threshold value extraction or machine learning capillary vessel library on the reference image, and estimating the diameter and the length of each capillary vessel according to the shape of the capillary vessels; 2) determining a capillary vessel from the sequence of images and calibrating its coordinates to a location in a reference image coordinate system; 3) extracting pixel values of a capillary vessel position in each image to form a time series and determining the number of discontinuous blood flow events; 4) calculating the center of gravity of a region of the capillary vessel in each image and determining the blood flow velocity; 5) determining an estimate of the number of discrete blood flow events per unit volume of blood based on the calculated number of discrete blood flow events, blood flow velocity, capillary size and imaging parameters; 6) the estimates of the number of discrete blood flow events per unit volume of blood obtained from all capillaries are combined as a single measurement.
In the above system for non-invasively analyzing blood flow rate and composition, the discontinuous blood flow events include the phenomenon of white blood cells flowing through capillaries, and the counting and classifying of the discontinuous blood flow events in the capillaries is the counting and classifying of the number and type of white blood cells.
Drawings
Fig. 1 is a flow chart of a method of non-invasively analyzing blood flow rate and composition in accordance with the present invention.
Fig. 2 is an example of capillary extraction using two wavelength light sources in a method for non-invasive analysis of blood flow rate and composition according to the present invention.
Fig. 3 is an example of calculating the number of discrete blood flow events in a capillary vessel in a method of non-invasively analyzing blood flow rate and composition in accordance with the invention.
Fig. 4 is an example of calculating the type of discontinuous blood flow events in a capillary vessel in a method of non-invasively analyzing blood flow rate and composition in accordance with the invention.
Fig. 5 is an example of calculating a distance between barycentric coordinates of the same capillary vessel in adjacent images in a method for non-invasively analyzing a blood flow rate and a blood composition according to the present invention.
FIG. 6 is a schematic diagram of one embodiment of a system for non-invasively analyzing blood flow and composition in accordance with the invention.
FIG. 7 is a schematic diagram of one embodiment of a system for non-invasively analyzing blood flow rates and components in accordance with the invention.
Detailed Description
Preferred embodiments of the present invention will be described with reference to the following drawings. It is to be noted that the embodiments described below are merely exemplary embodiments of the present invention, and the embodiments should not be construed as limiting the scope of the present invention.
Fig. 1 is a flow chart of a method of non-invasively analyzing blood flow rate and composition in accordance with the present invention. A method 100 for non-invasive analysis of blood flow rate and composition according to the present invention includes step 110 of acquiring a sequence of capillary vessel images and extracting the location and shape dimensions of the capillary vessels on a reference image. In some embodiments, when acquiring the capillary vessel image sequence, two light sources with different wavelengths are used for respectively illuminating the biological tissue part where the capillary vessel is located and acquiring the images in sequence. At this point, step 110 further comprises 1) acquiring a first capillary vessel image a illuminated by a first wavelength light source in vivo with the microscopic imaging unit; 2) acquiring a capillary vessel image sequence B illuminated by a second wavelength light source in a living body by using a microscopic imaging unit; 3) taking one image in the image sequence B as a reference image, carrying out position calibration (registration) on the image A and the reference image, calculating the difference between the reference image and the calibrated image, taking a threshold value, obtaining the position coordinates of the pixels occupied by the capillary vessels in the reference image coordinates, and estimating the diameter and the length of each capillary vessel according to the shape of the capillary vessel. After the biological tissues under the illumination of two different wavelengths are optically imaged, the images of the biological tissues have different contrasts at the position with capillary vessels. By calculating the difference between the reference image and the calibrated image, the capillary vessels can be highlighted and the pixel locations (coordinates) where the capillary vessels are located can be extracted. In addition, in the difference map between the reference image and the calibrated image, the pixel values located in the capillary vessel position mainly include the effect of the blood and the illumination light beam, and can be used for measuring the concentration of a substance in the blood, such as the concentration of red blood cells, the number of red blood cells, the blood oxygen, the blood sugar, and the like. Fig. 2 is an example of the extraction of capillaries in finger tissue using two wavelength light sources in a method for non-invasive analysis of blood flow rate and composition according to the present invention. Fig. 2A is an image of finger tissue illuminated by a light source having a wavelength of 450 nm, with capillaries indicated at 202, and fig. 2B is an image of finger tissue illuminated by a light source having a wavelength of 420 nm. The capillary is shown at 212. The capillaries in fig. 2A and 2B have different contrast. Fig. 2C is a comparison of pixel values along straight line positions 201 and 211 in fig. 2A and 2B, where dotted curve 231 is along straight line 201 in fig. 2A and curve 232 represents along straight line 211 in fig. 2B. Curves 231 and 232 have a significant difference in the location containing the capillary vessels. Fig. 2D is a difference between fig. 2A and fig. 2B. The difference image may be the difference between the log values of corresponding pixel values in the two images. In the above embodiments, two different wavelength light sources are used to obliquely incident illuminate the capillary vessel site within the field of view of the objective lens of the microimaging unit at similar angles and spot sizes from lateral positions relative to the objective lens of the microimaging unit. In addition, the two light sources with different wavelengths can be illuminated from the objective lens of the microscopic imaging unit after being combined. The light source can also be a light emitting diode light source and a laser light source which integrate two wavelengths, and capillary vessel parts in the field of view of the objective lens of the microscopic imaging unit are sequentially illuminated at similar angles and light spot sizes. The light source may be a continuous light source or a pulsed light source. When a pulsed light source, such as a pulsed laser, is used, the image capture device may be synchronized with the light source.
In some embodiments, a wavelength is used to illuminate a biological tissue site and a sequence of images is acquired. At this time, step 110 selects one image in the image sequence as a reference image, and extracts the position coordinates of the pixels occupied by the capillary vessels in the reference image coordinates by performing, for example, feature extraction, thresholding or machine learning on the reference image, and estimates the diameter and length of each capillary vessel according to the shape of the capillary vessel. In the above-described embodiments, the light source is placed on the front end side of the microscope objective or illuminates the capillary vessel region through the microscope objective. The light source may be a continuous light source or a pulsed light source. When a pulsed light source, such as a pulsed laser, is used, the image capture device may be synchronized with the light source.
A method 100 of non-invasive analysis of blood flow rate and composition of the present invention includes step 120 of determining the coordinates of the location of the capillary vessel in a sequence of images and calibrating the coordinates into a reference image coordinate system. During image acquisition, the same object is imaged at different positions of the two-dimensional sensor due to the movement of the imaging system or the movement of the measured object. Step 120, the other images in the image sequence B and the reference image are respectively subjected to position calibration to form a new image sequence C, and in the reference image coordinate system, the same capillary vessel has the same position coordinate in the image sequence C.
A method 100 for non-invasively analyzing blood flow rate and composition of the invention includes a step 130 of extracting a capillary location to form a time series of pixel values in each image and determining the number of discrete blood flow events. Step 130 further includes 1) selecting at least one pixel position coordinate in a capillary vessel, sequentially extracting pixel values of corresponding positions from the images in the image sequence C, and generating a first time-varying signal using the pixel values, each value in the signal corresponding to one capillary vessel image in the image sequence C; 2) calculating the difference between adjacent values in the first time-varying signal to generate a first difference signal; 3) thresholding the first difference signal to generate a first sequence of logic values; 4) calculating the difference between adjacent values in the first logic value sequence to generate a second difference signal; 5) and taking a threshold value for the second difference signal, and calculating the number of the second difference signal meeting the threshold condition, wherein the numerical value is the estimation of the occurrence frequency of discontinuous blood flow events in the capillary vessel within the corresponding time of the acquired image sequence B. Fig. 3 is an example of calculating the number of discrete blood flow events in a capillary vessel in a method of non-invasively analyzing blood flow rate and composition in accordance with the invention. Curve 301 in fig. 3A is a first time-varying signal generated with corresponding pixel values in an image sequence for a pixel location within a capillary vessel, where each pixel value is normalized to the pixel mean of the corresponding image. Curve 302 in fig. 3A is the absolute value of the first difference signal generated with curve 301. Fig. 3B corresponds to the image sequence 1-65 in fig. 3A. In fig. 3B, a curve 303 is a first logic sequence generated when the curve 302 is greater than the threshold value 0.1, and a curve 304 is a logic sequence generated when the difference signal of the curve 303 is greater than the threshold value 0. The number of times of the discontinuous blood flow events in the capillary vessel within the corresponding time of the acquired image sequence is obtained by calculating the number of the curve 304 with the median value of 1.
In step 130 of the method 100 for non-invasive analysis of blood flow rate and composition according to the present invention, some embodiments further include smoothing the first time-varying signal and then thresholding the smoothed first time-varying signal to generate a second sequence of logical values, and calculating lengths of consecutive adjacent logical values, and classifying the lengths by size as a classification of the type of discontinuous blood flow events in the capillary over time corresponding to the sequence of acquired images B. Fig. 4 is an example of calculating the type of discontinuous blood flow events in capillaries in a method for non-invasively analyzing blood flow velocity and composition in accordance with the invention. Curve 401 in fig. 4A is a first time-varying signal generated with corresponding pixel values in an image sequence for a pixel location within a capillary vessel, where each pixel value is normalized to the pixel mean of the corresponding image. The time-dependent signal curve 401 contains information about all discrete blood flow events occurring in the capillary. Classification of discrete blood flow events by directly thresholding curve 401 may lose part of the information. In fig. 4B, the curve 402 is the result of the curve in fig. 4A after being smoothed, and the threshold value is applied to the curve 402, so that information can be better retained. The signal width 403 in the curve 402 that satisfies the threshold condition may be calculated from the logical sequence generated by thresholding the curve 402. Depending on the length of the derived adjacent logical values, the discrete blood flow events may be classified, such as to distinguish the discrete blood flow events caused by leukocytes from other interfering events in the blood flow, or to further classify the leukocytes.
A method 100 for non-invasively analyzing blood flow and composition of the invention includes step 140 of calculating the center of gravity of a region of the capillary vessel in each image and determining blood flow velocity. Step 140 further comprises: 1) selecting a section of area along the capillary vessel, in the image sequence C, using the pixel value of the pixel in the area as the weight, calculating the barycentric coordinate of the area for each image, wherein each pair of barycentric coordinates corresponds to one image in the image sequence C and forms a barycentric sequence; 2) and calculating the distance between two barycentric coordinates by using adjacent barycentric coordinates, taking a threshold value for the distance, calculating the average value of the distances meeting the threshold value condition, and dividing the average value by the single image acquisition time to obtain the blood flow velocity. Fig. 5 is an example of calculating a distance between barycentric coordinates of the same capillary vessel in adjacent images in a method for non-invasively analyzing a blood flow rate and a blood composition according to the present invention. The image data in fig. 5 was obtained by illuminating the epidermis of the finger of the volunteer with a light source having a wavelength of 420 nm. The image acquisition frame rate is 200 frames per second, the image sequence length is 500 frames, each image pixel corresponds to a physical size of 0.65 micron, and the average diameter of the capillary vessel is about 10 pixels. In fig. 5, curve 501 is the distance between the coordinates of the centers of gravity of a region of the same capillary vessel in the adjacent images, and the average blood flow velocity can be calculated to be 1.74 mm/s by taking a threshold value of 10 for the distance.
A method 100 for non-invasively analyzing blood flow rate and composition of the invention includes a step 150 of determining an estimate of discrete blood flow events based on the calculated number of discrete blood flow events, blood flow velocity, capillary size, and imaging parameters. The estimate represents the number of discrete blood flow events per unit volume of blood.
A method 100 for non-invasively analyzing blood flow rate and composition of the invention further comprises step 160 of integrating estimates of discrete blood flow events from all capillaries as a measure of discrete blood flow events per unit volume of blood.
In the method 100 for non-invasively analyzing blood flow rate and composition, the discontinuous blood flow events include the phenomenon of white blood cells flowing through capillaries, and the counting and classifying of the discontinuous blood flow events in the capillaries are the counting and classifying of the number and types of the white blood cells.
FIG. 6 is a schematic diagram of one embodiment of a system for non-invasively analyzing blood flow and composition in accordance with the invention. The embodiment comprises a two-dimensional light sensor 600, two light sources 601 and 602 with different wavelengths, a light source unit 610 consisting of an optical beam combining sheet 603, an optical beam splitting sheet 604, a microscope objective 605, a biological sample 606 and a control processing unit 607. The two-dimensional light sensor 600 may be a CCD, CMOS detector, or other type of two-dimensional light sensor, among others. The biological sample 606 is a site in a human or other animal that contains capillaries, such as a fingertip, earlobe, or oral membranous wall. The light beam emitted by the light source 601 is reflected by the beam combiner 603, reflected by the beam splitter 604, and then irradiated onto the biological sample 606 through the microscope objective lens 605. Light emitted from the light source 602 is reflected by the beam splitter 604 after passing through the beam combiner 603, and is irradiated onto the biological sample 606 through the microscope objective. The shape, divergence angle and intensity distribution of the light beams irradiated on the biological sample by the light sources 601 and 602 are the same or within the error range required by the system. The light source unit 610 may be replaced with an integrated light source system 620. The light source system 620 may be a tunable laser or a light source integrating two LED chips. The light source system 610 or 620 may be a continuous type light source or a pulse type light source. When the light source system 610 or 620 is a pulse type light source, the pulse signal of the light source can be used to synchronize the two-dimensional light sensor 600 for image acquisition. The control processing unit 607 controls image acquisition and processing, and transmits the measurement result to the user and the related person through a display terminal or a network.
Fig. 7 is a schematic diagram of another embodiment of a system for non-invasively analyzing blood flow rates and components in accordance with the invention. The embodiment comprises a two-dimensional light sensor 700, a light source unit 710 consisting of two light sources 701 and 702 with different wavelengths and an optical combining beam sheet 703, a microscope objective 705, a biological sample 706 and a control processing unit 707. The two-dimensional light sensor 700 may be a CCD, CMOS detector, or other type of two-dimensional light sensor, among others. The biological sample 706 is a site in a living animal body of a human body containing a capillary blood vessel, such as a fingertip, an earlobe, or an oral cavity membrane wall. The light emitted from the light source 701 passes through the beam combining sheet 703 and then irradiates the biological sample 706, and the light beam emitted from the light source 702 is reflected by the beam combining sheet 703 and then irradiates the biological sample 706. The light beams from the light sources 701 and 702 are of the same shape, divergence angle and intensity distribution on the biological sample or within the error range required by the system. The light source unit 710 may be replaced with an integrated light source system 720. The light source system 720 may be a tunable laser or a light source integrating two LED chips. The light source system 710 or 720 may be a continuous type light source or a pulse type light source. When the light source system 710 or 720 is a pulse type light source, the pulse signal of the light source can be used to synchronize the two-dimensional light sensor 700 for image acquisition. The control processing unit 707 controls image acquisition and processing, and transmits the measurement result to the user and the related person through a display terminal or a network.
In the embodiment illustrated in fig. 6 and 7, a motor may also be included and controlled by the storage and processing unit to adjust the distance between the microscopic imaging unit and the capillary vessel to control the quality of the acquired image.
In the embodiment illustrated in fig. 6 and 7, the light source wavelength range employed is between 380 nanometers and 1510 nanometers; the acquisition frame rate of the adopted digital camera is more than 25 frames per second.
In the embodiment illustrated in fig. 6 and 7, the beam of light used for illumination may be linearly polarized light, and a linear polarizer is disposed between the two-dimensional light sensors 600 and 700 and the objective lenses 605 and 705, near the two-dimensional light sensors 600 and 700, with the polarization direction of the polarizer orthogonal to the polarization direction of the illumination beam.
In some embodiments, the index matching medium is applied to the biological tissue sample, such as pine oil, water.
It is finally noted that the disclosed embodiments are for the purpose of promoting a further understanding of the invention, but it will be understood by those skilled in the art that various alternatives and modifications may be made without departing from the spirit and scope of the invention and the appended claims. Therefore, the invention is not limited to the embodiments disclosed, and the scope of the invention is defined by the claims.
Claims (10)
1. A method for non-invasively analyzing blood flow rate and composition, comprising:
acquiring a first capillary vessel image A illuminated by a first wavelength light source in a living body by using a microscopic imaging unit;
acquiring a capillary vessel image sequence B illuminated by a second wavelength light source in the living body by using a microscopic imaging unit;
taking one image in the image sequence B as a reference image, carrying out position calibration (registration) on the image A and the reference image, calculating the difference between the reference image and the calibrated image, taking a threshold value to obtain the position coordinates of pixels occupied by the capillary vessels in a reference image coordinate system, and estimating the diameter and the length of each capillary vessel according to the shape of the capillary vessels;
respectively carrying out position calibration on the capillary vessels of other images in the image sequence B and the capillary vessels of the reference image to form a new image sequence C, wherein in a reference image coordinate system, the same capillary vessel has the same position coordinate in the image sequence C;
selecting a position occupying at least one pixel in a capillary vessel, sequentially extracting pixel values of corresponding positions from the images in the image sequence C, and generating a first signal changing according to time by using a statistical characteristic of the pixel values, wherein each value in the signal corresponds to a capillary vessel image in the image sequence C;
calculating the difference between adjacent values in the first time-varying signal to generate a first difference signal;
thresholding the first difference signal to generate a first sequence of logic values;
calculating the difference between adjacent values in the first logic value sequence to generate a second difference signal;
taking a threshold value for the second difference signal, and calculating the number of the second difference signal meeting the threshold value condition, wherein the number is the frequency of discontinuous blood flow events at the position in the image of the capillary vessel within the time corresponding to the collected image sequence B;
smoothing the first time-varying signal and taking a threshold value to generate a second logic value sequence;
calculating the length of continuous adjacent logic values in the second logic sequence, and classifying the length according to the size to be used as the classification of discontinuous blood flow events at the same position in the images of the capillary vessel in the corresponding time of the collected image sequence B;
selecting a section of area along the capillary vessel, in the image sequence C, using the pixel value of the pixel in the area as the weight, calculating the barycentric coordinates of the area, wherein each pair of barycentric coordinates corresponds to one image in the image sequence C and forms a barycentric sequence;
calculating the distance between two barycentric coordinates by using adjacent barycentric coordinates in the barycentric sequence, taking a threshold value for the distance, calculating the average value of the distances meeting the threshold value condition, and dividing the average value by the acquisition time of a single image to be used as the blood flow velocity;
calculating the number of discrete blood flow events per unit volume of blood using the blood flow velocity, vessel diameter, imaging parameters and the number of discrete blood flow events obtained from the capillary vessel;
repeating the calculation for other capillaries, using the average of the number of discontinuous blood flow events occurring in the unit volume of blood calculated from all capillaries as the number of discontinuous blood flow events occurring in the final unit volume of blood, and using the type of discontinuous blood flow events occurring in the unit volume of blood calculated from all capillaries as the estimated value of the type of discontinuous blood flow events occurring in the unit volume of blood.
2. A method of non-invasive analysis of blood flow rate and composition according to claim 1, wherein the discrete blood flow events occurring at the same location in the images of capillaries are leukocyte flow-through capillary events.
3. A method of non-invasive analysis of blood flow rate and composition according to claim 1, wherein the concentration of a substance in the blood is measured using a statistic of the difference between the logarithm of the reference image and the logarithm of the calibrated image, the substance being one of red blood cells, blood oxygen, and blood glucose.
4. A method of non-invasive analysis of blood flow rate and composition according to claim 1, wherein the digital camera has a frame rate of acquisition greater than 25 frames per second.
5. An apparatus for non-invasive analysis of blood flow rate and composition, comprising:
the digital camera acquires images according to instructions when the two light sources respectively illuminate the capillary vessels; the two light sources with different wavelengths sequentially illuminate capillary vessel parts in the field of view of the objective lens of the microscopic imaging unit at similar angles and light spot sizes from adjacent positions relative to the objective lens of the microscopic imaging unit, and acquire corresponding images;
a storage and processing unit consisting of a memory and a processing controller, the memory storing an image acquisition instruction, a processing instruction and a communication instruction, the processing controller analyzing the acquired image according to the processing instruction, extracting the position and other characteristic information of the capillary vessel, analyzing the blood in the capillary vessel, the storage and processing unit analyzing the flow rate and composition of the blood in the capillary vessel by a method comprising the steps of:
acquiring a first capillary vessel image A illuminated by a first wavelength light source in a living body by using a microscopic imaging unit;
acquiring a capillary vessel image sequence B illuminated by a second wavelength light source in the living body by using a microscopic imaging unit;
taking one image in the image sequence B as a reference image, carrying out position calibration (registration) on the image A and the reference image, calculating the difference between the reference image and the calibrated image, taking a threshold value to obtain the position coordinates of the pixels occupied by the capillary vessels in a reference image coordinate system, and estimating the diameter and the length of each capillary vessel according to the shape of the capillary vessels;
respectively carrying out position calibration on the capillary vessels of other images in the image sequence B and the capillary vessels of the reference image to form a new image sequence C, wherein in a reference image coordinate system, the same capillary vessel has the same position coordinate in the image sequence C;
selecting a position occupying at least one pixel in a capillary vessel, sequentially extracting pixel values of corresponding positions from the images in the image sequence C, and generating a first signal changing according to time by using a statistical characteristic of the pixel values, wherein each value in the signal corresponds to a capillary vessel image in the image sequence C;
calculating the difference between adjacent values in the first time-varying signal to generate a first difference signal;
thresholding the first difference signal to generate a first sequence of logic values;
calculating the difference between adjacent values in the first logic value sequence to generate a second difference signal;
taking a threshold value for the second difference signal, and calculating the number of the second difference signal meeting the threshold value condition, wherein the number is the frequency of discontinuous blood flow events at the position in the image of the capillary vessel within the time corresponding to the collected image sequence B;
taking a threshold value for the first time-varying signal to generate a second logic value sequence;
calculating the length of continuous adjacent logic values in the second logic sequence, and classifying the length according to the size to be used as the classification of discontinuous blood flow events at the same position in the images of the capillary vessel in the corresponding time of the collected image sequence B;
selecting a section of area along the capillary vessel, in the image sequence C, using the pixel value of the pixel in the area as the weight, calculating the barycentric coordinate of the area for each image, wherein each pair of barycentric coordinates corresponds to one image in the image sequence C and forms a barycentric sequence;
calculating the distance between two barycentric coordinates by using adjacent barycentric coordinates in the barycentric sequence, taking a threshold value for the distance, calculating the average value of the distances meeting the threshold value condition, and dividing the average value by the acquisition time of a single image to be used as the blood flow velocity;
calculating the number of discrete blood flow events per unit volume of blood using the blood flow velocity, vessel diameter, imaging parameters and the number of discrete blood flow events obtained from the capillary vessel;
repeating the above calculation for other capillaries, using the mean of the number of discrete blood flow events occurring in the unit volume of blood calculated from all capillaries as the final measure of the number of discrete blood flow events occurring in the unit volume of blood, and using the type of discrete blood flow events occurring in the unit volume of blood calculated from all capillaries as the measure of the type of discrete blood flow events occurring in the unit volume of blood;
and the display unit is used as an interactive interface between the user and the equipment and displays the image acquisition process and the white blood cell counting result.
6. A system for non-invasive analysis of blood flow rate and composition according to claim 5, wherein the discrete blood flow events occurring at the same location in the images of the capillaries are leukocyte flow-through capillary events.
7. A system for non-invasive analysis of blood flow rate and composition according to claim 5, wherein the statistics of the difference between the logarithm of the reference image and the logarithm of the calibrated image is used to measure the concentration of a substance in the blood, the substance being one of red blood cells, blood oxygen, and blood glucose.
8. A system for non-invasive analysis of blood flow rate and composition according to claim 5, wherein the digital camera has a frame rate of acquisition greater than 25 frames per second.
9. A system for non-invasive analysis of blood flow rate and composition according to claim 5, wherein the light source has a wavelength of 380 nm to 1510 nm.
10. An apparatus for non-invasively analyzing blood flow rate and white blood cell count, comprising:
the microscopic imaging unit consists of a microscopic objective, a digital camera and a light source, wherein the light source illuminates capillary vessels in the field of view of the microscopic objective, the wavelength of the light source is 380 nm to 1510 nm, the digital camera acquires images according to instructions when the light source illuminates the capillary vessels, and the frame rate of the digital camera acquiring the images is more than 25 frames per second;
a storage and processing unit consisting of a memory and a processing controller, the memory storing image acquisition instructions, processing instructions and communication instructions, the processing controller analyzing the acquired images according to the processing instructions, extracting the position and other characteristic information of the capillaries, the storage and processing unit analyzing the blood flow rate and the white blood cell count in the capillaries by a method comprising the steps of:
a) acquiring a capillary vessel image sequence B illuminated by a light source in a living body by using a microscopic imaging unit;
b) taking one image in the image sequence B as a reference image, extracting the position coordinates of the pixels occupied by the capillary vessels in the reference image coordinates from the reference image, and estimating the diameter and the length of each capillary vessel according to the shape of the capillary vessel;
c) respectively carrying out position calibration on other images in the image sequence B and a reference image to form a new image sequence C, wherein in a reference image coordinate system, the same capillary vessel has the same position coordinate in the image sequence C;
d) selecting a position occupying at least one pixel in a capillary vessel, sequentially extracting pixel values of corresponding positions from the images in the image sequence C, and generating a first signal changing according to time by using a statistical characteristic of the pixel values, wherein each value in the signal corresponds to a capillary vessel image in the image sequence C;
e) calculating the difference between adjacent values in the first time-varying signal to generate a first difference signal;
f) thresholding the first difference signal to generate a first sequence of logic values;
g) calculating the difference between adjacent values in the first logic value sequence to generate a second difference signal;
h) taking a threshold value for the second difference signal, and calculating the number of the second difference signal which meets the threshold condition, wherein the number corresponds to the number of the leukocyte events which flow through the capillary vessel in the time corresponding to the collected image sequence B;
i) taking a threshold value for the first time-varying signal to generate a second logic value sequence;
j) calculating the lengths of the continuous adjacent logic values in the second logic sequence, and classifying the lengths according to the sizes to be used as the classification of the leukocyte events flowing through the capillary vessel in the corresponding time of the acquired image sequence B;
k) selecting a section of area along the capillary vessel, in the image sequence C, using the pixel value of the pixel in the area as the weight, calculating the barycentric coordinate of the area for each image, wherein each pair of barycentric coordinates corresponds to one image in the image sequence C and forms a barycentric sequence;
l) calculating the distance between two barycentric coordinates by using adjacent barycentric coordinates, taking a threshold value for the distance, calculating the average value of the distances meeting the threshold value condition, and dividing the average value by the single image acquisition time to be used as the blood flow velocity;
m) calculating the number of leukocyte events occurring per unit volume of blood using the blood flow velocity, vessel diameter, imaging parameters and the number of leukocyte events obtained from the capillary;
n) repeating the above calculation for other capillaries, using the mean of the number of leukocyte events occurring per unit volume of blood calculated from all capillaries as the final number of leukocytes per unit volume of blood, and using the type of leukocyte events occurring per unit volume of blood calculated from all capillaries as an estimate of the type of leukocyte events occurring per unit volume of blood;
and the display unit is used as an interactive interface between the user and the equipment and displays the image acquisition process and the white blood cell counting result.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202011415191.XA CN114587324A (en) | 2020-12-07 | 2020-12-07 | System and method for non-invasive analysis of blood flow velocity and components |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202011415191.XA CN114587324A (en) | 2020-12-07 | 2020-12-07 | System and method for non-invasive analysis of blood flow velocity and components |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN114587324A true CN114587324A (en) | 2022-06-07 |
Family
ID=81813533
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202011415191.XA Pending CN114587324A (en) | 2020-12-07 | 2020-12-07 | System and method for non-invasive analysis of blood flow velocity and components |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN114587324A (en) |
-
2020
- 2020-12-07 CN CN202011415191.XA patent/CN114587324A/en active Pending
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| US11850065B2 (en) | Vessel imaging system and method | |
| CN105188523B (en) | Deep tissue blood flow meter using speckle contrast analysis | |
| AP931A (en) | Method and apparatus for reflected imaging analysis. | |
| US7264794B2 (en) | Methods of in vivo cytometry | |
| US20060181791A1 (en) | Method and apparatus for determining a property of a fluid which flows through a biological tubular structure with variable numerical aperture | |
| CA2149392A1 (en) | Non-invasive blood analyzer | |
| WO2008033909A2 (en) | Apparatus, probe and method for providing depth assessment in an anatomical structure | |
| CN107320112B (en) | Multi-parameter imaging detection method and device for microcirculation | |
| CN111870230A (en) | Multi-parameter tumor blood vessel normalization detection system and detection method | |
| CN107773217A (en) | Biological tissue microcirculation is metabolized dynamic measurement device and method | |
| RU2510506C2 (en) | Method for determining optical and biophysical tissue parameters | |
| US20040024296A1 (en) | System, method and computer program product for screening a spectral image | |
| US9844320B2 (en) | System and method for observing an object in a blood vessel | |
| CN114587324A (en) | System and method for non-invasive analysis of blood flow velocity and components | |
| CN206261606U (en) | A kind of external nasopharyngeal cavity vena systemica blood oxygen saturation imaging device | |
| CA2428866A1 (en) | Measuring haematocrit in blood vessels | |
| CN106963392B (en) | Optical noninvasive blood glucose detection two-dimensional correlation calibration method and system | |
| RU77144U1 (en) | DEVICE FOR NON-INVASIVE DETERMINATION OF BLOOD PARAMETERS | |
| Winkelman | Noninvasive blood cell measurements by imaging of the microcirculation | |
| WO2023145810A1 (en) | System and method for measuring concentration of component included in body fluid | |
| KR20130062858A (en) | Apparatus for monitoring health condition and method for providing service of monitoring health condition with multi-wavelength optical scanning | |
| JP2013140126A (en) | Concentration assaying device, concentration assaying method and program | |
| RU2373846C1 (en) | Device for non-invasive determining of blood parametres | |
| Chen et al. | Application Conditions of Laser Speckle Contrast Imaging Analyzer Based on Dynamic Scattering Material | |
| JPH09173300A (en) | Blood analyzer |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication |