CN111035396A - Intelligent brain function blood oxygen saturation monitoring and measuring simulation algorithm - Google Patents

Intelligent brain function blood oxygen saturation monitoring and measuring simulation algorithm Download PDF

Info

Publication number
CN111035396A
CN111035396A CN201911371976.9A CN201911371976A CN111035396A CN 111035396 A CN111035396 A CN 111035396A CN 201911371976 A CN201911371976 A CN 201911371976A CN 111035396 A CN111035396 A CN 111035396A
Authority
CN
China
Prior art keywords
velocity
blood oxygen
oxygen saturation
photoacoustic
measuring
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
Application number
CN201911371976.9A
Other languages
Chinese (zh)
Inventor
谢传建
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Hangzhou Chuanyi Technology Co ltd
Original Assignee
Hangzhou Chuanyi Technology Co ltd
Priority date (The priority date 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 date listed.)
Filing date
Publication date
Application filed by Hangzhou Chuanyi Technology Co ltd filed Critical Hangzhou Chuanyi Technology Co ltd
Priority to CN201911371976.9A priority Critical patent/CN111035396A/en
Publication of CN111035396A publication Critical patent/CN111035396A/en
Pending legal-status Critical Current

Links

Images

Classifications

    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/145—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
    • A61B5/14553—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 specially adapted for cerebral tissue
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/72—Signal processing specially adapted for physiological signals or for diagnostic purposes

Landscapes

  • Health & Medical Sciences (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Physics & Mathematics (AREA)
  • Engineering & Computer Science (AREA)
  • Public Health (AREA)
  • Medical Informatics (AREA)
  • Veterinary Medicine (AREA)
  • General Health & Medical Sciences (AREA)
  • Animal Behavior & Ethology (AREA)
  • Biophysics (AREA)
  • Pathology (AREA)
  • Biomedical Technology (AREA)
  • Heart & Thoracic Surgery (AREA)
  • Surgery (AREA)
  • Molecular Biology (AREA)
  • Psychiatry (AREA)
  • Computer Vision & Pattern Recognition (AREA)
  • Physiology (AREA)
  • Artificial Intelligence (AREA)
  • Signal Processing (AREA)
  • Neurology (AREA)
  • Spectroscopy & Molecular Physics (AREA)
  • Optics & Photonics (AREA)
  • Measurement Of The Respiration, Hearing Ability, Form, And Blood Characteristics Of Living Organisms (AREA)

Abstract

The invention provides an intelligent brain function blood oxygen saturation monitoring and measuring simulation algorithm, which constructs a measuring simulation space; measuring the distribution optical characteristic and the spatial distribution, calculating the energy deposition from the spatial distribution; obtaining an initial overpressure source under the constraint condition of thermoelastic stress; when the laser pulse length is less than the thermal relaxation time, the medium is uniform and the sound velocity is constant, a photoacoustic velocity wavelength propagation formula is obtained; fitting by adopting a Green function to obtain a positive solution of the photoacoustic velocity wavelength; modeling a frequency response curve of the transducer as a Gaussian function, and constructing a mapping model between the photoacoustic velocity with wavelength limitation and the number of the detection points to obtain a light distribution theoretical value model; and solving the optimized value of the minimum value of the error function and monitoring and measuring the cerebral function blood oxygen saturation. The invention adopts the Green function and Monte Carlo radiant flux to simulate and reconstruct the optical parameter distribution algorithm of the tissue, and effectively constructs the monitoring and measuring standard of the blood oxygen saturation of the brain function.

Description

Intelligent brain function blood oxygen saturation monitoring and measuring simulation algorithm
Technical Field
The invention belongs to the technical field of medical equipment, and particularly relates to an intelligent brain function blood oxygen saturation monitoring and measuring simulation algorithm.
Background
Near infrared spectroscopy is a noninvasive detection method which is developed in recent years, is portable, real-time, continuous, simple to operate and relatively cheap and is provided for clinic. Clinically, a cerebral oximeter is an ideal monitoring instrument for obtaining cerebral blood oxygen reserve information, and can provide a noninvasive intracranial cerebral oxygen level observation window for neurosurgeons. Especially when the blood circulation stops and the normal work of many monitoring instruments will have certain difficulties, the brain oximeter can still work as usual, so the brain oximeter can be widely applied to various occasions of monitoring the blood oxygen of the brain.
Erythrocytes play an important physiological role while affecting hemodynamics. Under static or low shear rate flow conditions, red blood cells form aggregates of red blood cells. Erythrocyte aggregation can alter blood flow velocity, affect hemodynamics, cause vascular resistance and tissue engorgement, and furthermore, abnormalities in erythrocyte aggregation are common in a variety of pathologies, such as deep vein thrombosis, diabetes or stroke. In terms of physiological functions, erythrocytes deliver oxygen to biological tissues and exchange carbon dioxide, the transport of oxygen being mainly controlled by the blood oxygen saturation, a measure of the maximum carrying capacity of oxygen in erythrocytes, an important physiological indicator in clinical diagnostics, which reflects the oxygen supply capacity of the body. The traditional function index detection method is mostly limited to lossy detection, or the detection resolution is not high, and the traditional function index detection method cannot provide effective monitoring capability for the blood oxygen index of a specific position.
In evaluating the physiological function of red blood cells, in pulse oximeters, readings are prone to error due to insufficient effective scattering radii caused by hypotension, hypothermia, electromyography abnormalities and body movement, and blood being a very high concentration medium. Factors influencing the monitoring of the blood oxygen saturation of brain functions mainly come from the interference of head movement, noise introduced by a signal processing channel, noise introduced by an optical fiber sensor, sensitivity drift of a detection instrument and insufficient stability of photoelectric conversion. The main factors causing the detection sensitivity drift and affecting the photoelectric conversion stability are the detection sensitivity drift caused by the ambient temperature, and in the optical detection process, the macroscopic photocurrent is a statistical result obtained under a certain temperature thermal balance, so the detection photocurrent is not only related to the number of absorbed photons (incident optical power), but also closely related to the ambient temperature.
Disclosure of Invention
The technical problem that monitoring results are inconsistent due to various interference factors in the process of monitoring the blood oxygen saturation of the brain function is solved, the method can be used for carrying out model reconstruction according to multipoint data obtained by measurement sampling, and an algorithm for simulating and reconstructing optical parameter distribution of tissues by adopting a Green function and Monte Carlo radiant flux is adopted, so that the monitoring and measuring standard of the blood oxygen saturation of the brain function is effectively constructed.
The invention provides the following technical scheme: the intelligent brain function blood oxygen saturation monitoring and measuring simulation algorithm comprises the following steps:
1) constructing a measurement simulation space;
2) measuring the distributed optical characteristics of each tissue surface element in the measurement simulation space by using a detector, and recording the number of detection points as a vector phi (phi)1,Φ2,Φ3,……,ΦM)TThe distribution optical characteristic is light absorption coefficient
Figure BDA0002339899370000021
Coefficient of light scattering
Figure BDA0002339899370000022
Light scattering anisotropy m;
3) measuring the spatial distribution F (x) of the simulated space, and calculating the energy deposition W (x) according to the spatial distribution, wherein the formula is as follows:
Figure BDA0002339899370000023
4) under the constraint condition of thermoelastic stress, generating an initial overpressure source in the medium, neglecting heat conduction and stress propagation therein, and obtaining an initial overpressure source p0(x)：
Figure BDA0002339899370000024
Wherein β (x) is the coefficient of thermal expansion, C is the speed of sound, C is the coefficient of thermal expansionp(x) Constant pressure heat capacity;
5) when the laser pulse length is less than the thermal relaxation time, the medium is uniform and the sound velocity is constant, a photoacoustic velocity wavelength propagation formula is obtained:
Figure BDA0002339899370000031
wherein p (x, t) is the photoacoustic velocity wavelength pressure, and δ (t) is the dirac pulse function;
6) fitting by adopting a Green function to obtain a positive solution of the photoacoustic velocity wavelength:
Figure BDA0002339899370000032
wherein the content of the first and second substances,
Figure BDA0002339899370000033
7) performing convolution calculation on the photoacoustic velocity wavelength obtained in the step 6) to convert the photoacoustic velocity wavelength into a photoacoustic velocity P with wavelength limitationMC(x, t), the formula is as follows:
Figure BDA0002339899370000034
wherein the content of the first and second substances,
Figure BDA0002339899370000035
represents the convolution calculation, h (t) represents the impulse response of the receiver;
8) modeling the frequency response curve of the transducer as a Gaussian function, h (t) and
Figure BDA0002339899370000036
specifically, the formula is as follows:
Figure BDA0002339899370000037
Figure BDA0002339899370000038
wherein, ω is0σ is the bandwidth of the receiver, which is the center frequency of the transducer.
9) Constructing a mapping model between the photoacoustic velocity with wavelength limitation and the number of the detection points to obtain a light distribution theoretical value model:
Φi＝f(PMC(x,t))，i＝1,2,……M；
10) construction of theoretical value of light distribution phiiWith actual detection value phinError function between:
Figure BDA0002339899370000041
wherein | | · | | is an inner product function;
11) solving the optimized value of the minimum value of the error function to obtain the optical parameter distribution P of the reconstructed tissueH(x, t), the formula is as follows:
Figure BDA0002339899370000042
obtained PH(x, t) is more than or equal to 0, namely the reference standard for monitoring and measuring the blood oxygen saturation of the brain function.
Further, the simulation space is formed by a plurality of three-dimensional Cartesian coordinate system voxel grids.
Further, the number of the voxel grids in the three-dimensional Cartesian coordinate system is (800-1000) × (500-550).
Further, the three-dimensional size of the three-dimensional cartesian coordinate system voxel grid is: length x width x height (15-20 mm) × (10-12 mm).
Further, the volume of the element is (20 to 30 μm) × (20 to 30 μm).
Further, the measurement condition of the detector adopted in the step 2) is that measurement is carried out under the pulse flow rate and with the beat frequency of 60-80 bpm and the step of 10-15 nm.
Further, the sonic velocity measurement of 21 flowing blood wavelengths from 700nm to 900nm was performed using the probe measurement conditions.
Further, the number of photons per wavelength of the 21 wavelengths exceeds 2000 ten thousand.
The invention has the beneficial effects that:
1) the method and the device perform algorithm research aiming at the problem that the photoacoustic imaging technology capable of non-invasively measuring the blood oxygen saturation of the brain does not have a uniform monitoring standard in the measurement result, and adopt the construction of the analog measurement with a plurality of three-dimensional Cartesian coordinate system voxel grids, so that the method and the device have higher ultrasonic spatial resolution and optical contrast, and the standard constructed by the obtained analog algorithm has higher sensitivity for deeper (several centimeters) tissues.
2) The calculation of the photoacoustic signal obtained by measurement is based on the combination of the Green function and Monte Carlo radiant flux simulation, three parameters of light absorption coefficient, light scattering coefficient and light scattering anisotropy are given in the energy deposition process, the energy deposition in the space distribution can be comprehensively defined by utilizing the space distribution, the laser pulse length is less than the thermal relaxation time, the medium is uniform, the sound velocity is constant in the calculation process of the photoacoustic velocity wavelength propagation formula, the noise error of a model formed by measurement simulation can be effectively avoided, and the thermoelastic stress constraint is adopted, so that the noise interference of photoacoustic velocity wavelength propagation calculation caused by heat conduction and stress propagation is effectively shielded.
3) By the shielding of the sample collection interference noise in the measurement space, a mapping model between the photoacoustic velocity with wavelength limitation and the number of the detection points is effectively constructed to obtain a corresponding light intensity distribution theoretical value, the corresponding light intensity distribution theoretical value is compared with an actual value, the distribution of optical parameters is calculated according to a certain fitting model, and a distribution image of the optical parameters of the mechanism to be measured is obtained.
4) By constructing the error function E (phi)i，Φn) The difference between the measured actual value and the theoretical value of the constructed model is reflected, the minimum optimization problem of the error function is solved, the reconstructed optical parameter vector and the distribution image of the measurement simulation space can be obtained, and finally the optimal solution is obtained, namely the standard reference standard of the monitoring and measuring of the blood oxygen saturation of the brain function.
Drawings
Fig. 1 is a schematic flow chart of an intelligent brain function blood oxygen saturation monitoring and measuring simulation algorithm provided by the invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Example 1
The intelligent brain function blood oxygen saturation monitoring and measuring simulation algorithm provided by the embodiment comprises the following steps:
1) constructing a measurement simulation space, wherein the simulation space is formed by a plurality of three-dimensional Cartesian coordinate system voxel grids, the number of the simulation space is 915 multiplied by 535, and the three-dimensional size of the grids is 17mm multiplied by 11 mm;
2) measuring the distributed optical characteristics of each tissue surface element in the simulated space by adopting a detector, and recording the number of detection points as a vector phi (phi)1,Φ2,Φ3,……,ΦM)TThe optical characteristic is assigned to the light absorption coefficient
Figure BDA0002339899370000061
Coefficient of light scattering
Figure BDA0002339899370000062
Light scattering anisotropy m, the volume of the element is 25 μm × 25 μm × 25 μm; under the measuring condition, the sonic velocity measurement is carried out on 21 flowing blood with the wavelength from 700nm to 900nm by taking 12nm as steps at a beat frequency of 70bpm under the pulse flow, and the number of photons of each wavelength in the 21 wavelengths exceeds 2000 ten thousand;
3) measuring the spatial distribution F (x) of the simulated space, and calculating the energy deposition W (x) according to the spatial distribution, wherein the formula is as follows:
Figure BDA0002339899370000063
4) under the constraint condition of thermoelastic stress, generating an initial overpressure source in the medium, neglecting heat conduction and stress propagation therein, and obtaining an initial overpressure source p0(x)：
Figure BDA0002339899370000064
Wherein β (x) is the coefficient of thermal expansion, C is the speed of sound, C is the coefficient of thermal expansionp(x) Constant pressure heat capacity;
5) when the laser pulse length is less than the thermal relaxation time, the medium is uniform and the sound velocity is constant, a photoacoustic velocity wavelength propagation formula is obtained:
Figure BDA0002339899370000071
wherein p (x, t) is the photoacoustic velocity wavelength pressure, and δ (t) is the dirac pulse function;
6) fitting by adopting a Green function to obtain a positive solution of the photoacoustic velocity wavelength:
Figure BDA0002339899370000072
wherein the content of the first and second substances,
Figure BDA0002339899370000073
7) the photoacoustic velocity wavelength obtained in the step 6) is converted into the photoacoustic velocity P with the wavelength limitation by the convolution calculationMC(x, t), the formula is as follows:
Figure BDA0002339899370000074
wherein the content of the first and second substances,
Figure BDA0002339899370000075
represents the convolution calculation, h (t) represents the impulse response of the receiver;
8) modeling the frequency response curve of the transducer as a Gaussian function, h (t) and
Figure BDA0002339899370000076
specifically, the formula is as follows:
Figure BDA0002339899370000077
Figure BDA0002339899370000078
wherein, ω is0σ is the bandwidth of the receiver, which is the center frequency of the transducer.
9) Constructing a mapping model between the photoacoustic speed and the number of detection points with wavelength limitation to obtain a light distribution theoretical value model:
Φi＝f(PMC(x,t))，i＝1,2,……M；
10) construction of theoretical value of light distribution phiiWith actual detection value phinError function between:
Figure BDA0002339899370000081
where | · | | is an inner product function, such as vector x ═ x (x)1,x2,…..,xm)T，
Then
Figure BDA0002339899370000082
Wherein
Figure BDA0002339899370000083
Is xiThe complex conjugate of (a).
11) Solving the optimized value of the minimum value of the error function to obtain the optical parameter distribution P of the reconstructed tissueH(x, t), the formula is as follows:
Figure BDA0002339899370000084
obtained PH(x, t) is more than or equal to 0, namely the reference standard for monitoring and measuring the blood oxygen saturation of the brain function.
Example 2
The present embodiment differs from embodiment 1 only in that the number of voxel grids in the three-dimensional cartesian coordinate system is 800 × 500 × 500, and the three-dimensional size of the voxel grid: length × width × height ═ 15mm × 10mm × 10 mm; the volume of the element is 20. mu. m.times.20. mu.m.
The measurement condition in step 2) by using a detector is that the optical sound velocity measurement is carried out on 21 flowing blood with the wavelength from 700nm to 900nm under the pulse flow rate and with the beat frequency of 60bpm and the step of 10 nm.
Example 3
The present embodiment differs from embodiments 1 and 2 only in that the number of voxel grids of the three-dimensional cartesian coordinate system is 1000 × 550 × 550, the three-dimensional size of the voxel grid: length × width × height ═ 20mm × 12mm × 12 mm; the volume of the element is 30. mu. m.times.30. mu.m.
The measurement condition in step 2) by using a detector is that the optical sound velocity measurement is carried out on 21 flowing blood with the wavelength from 700nm to 900nm under the pulse flow rate and with the beat frequency of 80bpm and the step of 15 nm.
While the invention has been described with reference to a preferred embodiment, various modifications may be made and equivalents may be substituted for elements thereof without departing from the scope of the invention. In particular, the technical features mentioned in the embodiments can be combined in any way as long as there is no structural conflict. It is intended that the invention not be limited to the particular embodiments disclosed, but that the invention will include all embodiments falling within the scope of the appended claims.

Claims (8)

1. The intelligent brain function blood oxygen saturation monitoring and measuring simulation algorithm is characterized by comprising the following steps:
1) constructing a measurement simulation space;
2) measuring the distributed optical characteristics of each tissue surface element in the measurement simulation space by using a detector, and recording the number of detection points as a vector phi (phi)1,Φ2,Φ3,……,ΦM)TThe distribution optical characteristic is light absorption coefficient
Figure FDA0002339899360000015
Coefficient of light scattering
Figure FDA0002339899360000016
Light scattering anisotropy m;
3) measuring the spatial distribution F (x) of the simulated space, and calculating the energy deposition W (x) according to the spatial distribution, wherein the formula is as follows:
Figure FDA0002339899360000017
4) under the constraint condition of thermoelastic stress, generating an initial overpressure source in the medium, neglecting heat conduction and stress propagation therein, and obtaining an initial overpressure source p0(x)：
Figure FDA0002339899360000011
Wherein β (x) is the coefficient of thermal expansion, C is the speed of sound, C is the coefficient of thermal expansionp(x) Constant pressure heat capacity;
5) when the laser pulse length is less than the thermal relaxation time, the medium is uniform and the sound velocity is constant, a photoacoustic velocity wavelength propagation formula is obtained:
Figure FDA0002339899360000012
wherein p (x, t) is the photoacoustic velocity wavelength pressure, and δ (t) is the dirac pulse function;
6) fitting by adopting a Green function to obtain a positive solution of the photoacoustic velocity wavelength:
Figure FDA0002339899360000013
wherein the content of the first and second substances,
Figure FDA0002339899360000014
7) performing convolution calculation on the photoacoustic velocity wavelength obtained in the step 6) to convert the photoacoustic velocity wavelength into a photoacoustic velocity P with wavelength limitationMC(x, t), the formula is as follows:
Figure FDA0002339899360000021
wherein the content of the first and second substances,
Figure FDA0002339899360000026
represents the convolution calculation, h (t) represents the impulse response of the receiver;
8) modeling the frequency response curve of the transducer as a Gaussian function, h (t) and
Figure FDA0002339899360000027
specifically, the formula is as follows:
Figure FDA0002339899360000022
Figure FDA0002339899360000023
wherein, ω is0σ is the bandwidth of the receiver, which is the center frequency of the transducer.
9) Constructing a mapping model between the photoacoustic velocity with wavelength limitation and the number of the detection points to obtain a light distribution theoretical value model:
Φi＝f(PMC(x,t))，i＝1,2,……M；
10) construction of theoretical value of light distribution phiiWith actual detection value phinError function between:
Figure FDA0002339899360000024
wherein | | · | | is an inner product function;
11) solving the optimized value of the minimum value of the error function to obtain the optical parameter distribution P of the reconstructed tissueH(x, t), the formula is as follows:
Figure FDA0002339899360000025
obtained PH(x, t) is more than or equal to 0, namely the reference standard for monitoring and measuring the blood oxygen saturation of the brain function.
2. The intelligent algorithm for simulating measurement of blood oxygen saturation monitoring of brain function according to claim 1, wherein said simulation space is composed of a plurality of three-dimensional cartesian coordinate system voxel grids.
3. The intelligent algorithm for simulating measurement of blood oxygen saturation monitoring for brain function according to claim 2, wherein the number of voxel grids in the three-dimensional Cartesian coordinate system is (800-1000) × (500-550).
4. The intelligent brain function oximetry measurement simulation algorithm according to claim 2, wherein the three dimensions of the three-dimensional cartesian coordinate system voxel grid are: length x width x height (15-20 mm) × (10-12 mm).
5. The intelligent simulation algorithm for monitoring and measuring blood oxygen saturation level of brain function according to claim 2, wherein the volume of said element is (20-30 μm) x (20-30 μm).
6. The intelligent algorithm for simulating measurement of blood oxygen saturation monitoring of brain function according to claim 1, wherein the measurement condition with the detector in step 2) is measurement under pulse flow rate at a beat frequency of 60-80 bpm and in steps of 10-15 nm.
7. The intelligent algorithm for simulating measurement of blood oxygen saturation monitoring for brain function according to claim 6, wherein the sound velocity measurement of 21 wavelengths from 700nm to 900nm is performed by using the measurement condition of the detector.
8. The intelligent brain function oximetry measurement simulation algorithm of claim 7, wherein the number of photons at each of the 21 wavelengths exceeds 2000 million.
CN201911371976.9A 2019-12-27 2019-12-27 Intelligent brain function blood oxygen saturation monitoring and measuring simulation algorithm Pending CN111035396A (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN201911371976.9A CN111035396A (en) 2019-12-27 2019-12-27 Intelligent brain function blood oxygen saturation monitoring and measuring simulation algorithm

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN201911371976.9A CN111035396A (en) 2019-12-27 2019-12-27 Intelligent brain function blood oxygen saturation monitoring and measuring simulation algorithm

Publications (1)

Publication Number Publication Date
CN111035396A true CN111035396A (en) 2020-04-21

Family

ID=70239183

Family Applications (1)

Application Number Title Priority Date Filing Date
CN201911371976.9A Pending CN111035396A (en) 2019-12-27 2019-12-27 Intelligent brain function blood oxygen saturation monitoring and measuring simulation algorithm

Country Status (1)

Country Link
CN (1) CN111035396A (en)

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN112168180A (en) * 2020-09-24 2021-01-05 上海交通大学 Tissue blood oxygen imaging detection method based on two-stage space mapping
CN114839795A (en) * 2022-04-24 2022-08-02 上海交通大学 Glasses optical filter design method with blood oxygen information enhancement function and glasses

Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN101526465A (en) * 2009-04-22 2009-09-09 天津大学 Quick multi-wavelength tissue optical parameter measuring device and trans-construction method
US20090227997A1 (en) * 2006-01-19 2009-09-10 The Regents Of The University Of Michigan System and method for photoacoustic imaging and monitoring of laser therapy
US20130317331A1 (en) * 2012-05-03 2013-11-28 Vioptix, Inc. Monte Carlo and Iterative Methods for Determination of Tissue Oxygen Saturation
CN108577810A (en) * 2018-03-21 2018-09-28 华北电力大学（保定） Solve the intravascular photoacoustic image rebuilding method and system of velocity of sound problem of non-uniform

Patent Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20090227997A1 (en) * 2006-01-19 2009-09-10 The Regents Of The University Of Michigan System and method for photoacoustic imaging and monitoring of laser therapy
CN101526465A (en) * 2009-04-22 2009-09-09 天津大学 Quick multi-wavelength tissue optical parameter measuring device and trans-construction method
US20130317331A1 (en) * 2012-05-03 2013-11-28 Vioptix, Inc. Monte Carlo and Iterative Methods for Determination of Tissue Oxygen Saturation
CN108577810A (en) * 2018-03-21 2018-09-28 华北电力大学（保定） Solve the intravascular photoacoustic image rebuilding method and system of velocity of sound problem of non-uniform

Non-Patent Citations (2)

* Cited by examiner, † Cited by third party
Title
ROMAN HOCHULI: "Monte Carlo Methods in Quantitative Photoacoustic Tomography", 《UNIVERSITY COLLEGE LONDON PHDTHESIS》 *
TAE-HOON BOK 等: "In vitro photoacoustic spectroscopy of pulsatile blood flow: Probing the interrelationship between red blood cell aggregation and oxygen saturation", 《J. BIOPHOTONICS》 *

Cited By (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN112168180A (en) * 2020-09-24 2021-01-05 上海交通大学 Tissue blood oxygen imaging detection method based on two-stage space mapping
CN112168180B (en) * 2020-09-24 2022-01-18 上海交通大学 Tissue blood oxygen imaging detection method based on two-stage space mapping
CN114839795A (en) * 2022-04-24 2022-08-02 上海交通大学 Glasses optical filter design method with blood oxygen information enhancement function and glasses

Similar Documents

Publication Publication Date Title
Gröhl et al. Deep learning for biomedical photoacoustic imaging: A review
Zourabian et al. Trans-abdominal monitoring of fetal arterial blood oxygenation using pulse oximetry
Pellicer et al. Near-infrared spectroscopy: a methodology-focused review
Laufer et al. Quantitative spatially resolved measurement of tissue chromophore concentrations using photoacoustic spectroscopy: application to the measurement of blood oxygenation and haemoglobin concentration
CN110123339B (en) Noninvasive blood glucose measuring device and method
US20040116789A1 (en) Fetal pulse oximetry
CN104146714B (en) Organizer local oxyhemoglobin saturation variation topology imaging device and method
CN107613858A (en) System and method for non-invasive monitoring intracranial pressure
US9498133B2 (en) Optoacoustic-ultrasonic system for coregistered functional and morphological imaging of placentas
CN108478192B (en) Measuring system for estimating skin tissue micro-vessel depth
CN111035396A (en) Intelligent brain function blood oxygen saturation monitoring and measuring simulation algorithm
US20230172565A1 (en) Systems, devices, and methods for developing a model for use when performing oximetry and/or pulse oximetry and systems, devices, and methods for using a fetal oximetry model to determine a fetal oximetry value
Nitzan et al. Physical and physiological interpretations of the PPG signal
CN106923814A (en) A kind of noninvasive cerebral blood flow (CBF) measuring system and measuring method
Beard et al. Quantitative photoacoustic imaging: measurement of absolute chromophore concentrations for physiological and molecular imaging
CN111973169B (en) Method for evaluating effective hepatic blood flow index, detection device and storage medium
JP4586680B2 (en) Method for preparing calibration curve for quantitative analysis of in-vivo components, and quantitative analyzer using the calibration curve
Vazquez-Jaccaud et al. Wavelength selection method with standard deviation: application to pulse oximetry
CN113598761A (en) Dual-wavelength infrared blood oxygen detection system based on CCD
Zahedi et al. Applicability of adaptive noise cancellation to fetal heart rate detection using photoplethysmography
CN111671436A (en) Temperature-compensated photoacoustic noninvasive hemoglobin detection device and detection method
JP3876322B2 (en) Non-invasive brain activity measurement method
Benaron et al. Imaging (NIRI) and quantitation (NIRS) in tissue using time-resolved spectrophotometry: the impact of statistically and dynamically variable optical path lengths
Zherebtsov et al. Impact of blood volume on the diffuse reflectance spectra of human skin in visible and NIR spectral ranges
Zhao et al. Anatomical and functional images of in vitro and in vivo tissues by NIR time-domain diffuse optical tomography

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination
WD01 Invention patent application deemed withdrawn after publication

Application publication date: 20200421

WD01 Invention patent application deemed withdrawn after publication