CN112150370A - Space compound imaging method and device - Google Patents

Space compound imaging method and device Download PDF

Info

Publication number
CN112150370A
CN112150370A CN201910579569.0A CN201910579569A CN112150370A CN 112150370 A CN112150370 A CN 112150370A CN 201910579569 A CN201910579569 A CN 201910579569A CN 112150370 A CN112150370 A CN 112150370A
Authority
CN
China
Prior art keywords
image
kalman
fusion
ultrasonic
data
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.)
Granted
Application number
CN201910579569.0A
Other languages
Chinese (zh)
Other versions
CN112150370B (en
Inventor
杨加成
刘林泉
张强
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.)
SHENZHEN EMPEROR ELECTRONIC TECHNOLOGY CO LTD
Original Assignee
SHENZHEN EMPEROR ELECTRONIC 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 SHENZHEN EMPEROR ELECTRONIC TECHNOLOGY CO LTD filed Critical SHENZHEN EMPEROR ELECTRONIC TECHNOLOGY CO LTD
Priority to CN201910579569.0A priority Critical patent/CN112150370B/en
Publication of CN112150370A publication Critical patent/CN112150370A/en
Application granted granted Critical
Publication of CN112150370B publication Critical patent/CN112150370B/en
Active legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Images

Classifications

    • G06T5/92—
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B8/00—Diagnosis using ultrasonic, sonic or infrasonic waves
    • A61B8/52—Devices using data or image processing specially adapted for diagnosis using ultrasonic, sonic or infrasonic waves
    • A61B8/5215—Devices using data or image processing specially adapted for diagnosis using ultrasonic, sonic or infrasonic waves involving processing of medical diagnostic data
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B8/00—Diagnosis using ultrasonic, sonic or infrasonic waves
    • A61B8/52—Devices using data or image processing specially adapted for diagnosis using ultrasonic, sonic or infrasonic waves
    • A61B8/5269—Devices using data or image processing specially adapted for diagnosis using ultrasonic, sonic or infrasonic waves involving detection or reduction of artifacts
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T5/00—Image enhancement or restoration
    • G06T5/50—Image enhancement or restoration by the use of more than one image, e.g. averaging, subtraction
    • G06T5/70—
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/10—Image acquisition modality
    • G06T2207/10132—Ultrasound image
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/20—Special algorithmic details
    • G06T2207/20212—Image combination
    • G06T2207/20221—Image fusion; Image merging
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/30—Subject of image; Context of image processing
    • G06T2207/30004—Biomedical image processing

Landscapes

  • Health & Medical Sciences (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Engineering & Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • Radiology & Medical Imaging (AREA)
  • Medical Informatics (AREA)
  • Veterinary Medicine (AREA)
  • Biophysics (AREA)
  • Nuclear Medicine, Radiotherapy & Molecular Imaging (AREA)
  • Pathology (AREA)
  • Public Health (AREA)
  • Biomedical Technology (AREA)
  • Heart & Thoracic Surgery (AREA)
  • Computer Vision & Pattern Recognition (AREA)
  • Molecular Biology (AREA)
  • Surgery (AREA)
  • Animal Behavior & Ethology (AREA)
  • General Health & Medical Sciences (AREA)
  • General Physics & Mathematics (AREA)
  • Theoretical Computer Science (AREA)
  • Ultra Sonic Daignosis Equipment (AREA)
  • Image Processing (AREA)

Abstract

A spatial compound imaging method and apparatus, comprising: a data acquisition step: the probe scans the same position along different deflection directions to obtain ultrasonic images at different deflection angles; and (3) coordinate conversion: converting the polar coordinate system of the ultrasonic image into a Cartesian coordinate system; an image fusion step: fusing the ultrasonic images through a Kalman space composite algorithm to generate a fused image; an image correction step: and correcting the fused image. The application utilizes Kalman to have ultrahigh timeliness, has congenital advantages in the ultrasonic field, and has a certain filtering effect on data, Kalman data fusion is introduced into ultrasonic image space compounding, adverse factor influences such as speckle noise and artifacts of ultrasonic images can be effectively inhibited by utilizing Kalman characteristics, Kalman data fusion is performed according to variances of relevant data, and dynamic planning is performed on weighting coefficients by states, so that left-handed data and right-handed data are better fused, and the effects of noise reduction and fusion enhancement are achieved.

Description

Space compound imaging method and device
Technical Field
The present application relates to image processing, and more particularly, to a method and apparatus for spatial compound imaging.
Background
In recent years, with the continuous progress and development of medical technology, imaging technology has been rapidly developed. The ultrasound technology, as an important component of medical imaging technology, shows the characteristics of real-time performance, non-invasiveness, low cost, simple operation and the like in the practical application process, is widely applied clinically, and becomes one of the most common modes of medical diagnosis. The basic principle of ultrasonic imaging is to utilize reflected or scattered pulse signals generated when ultrasonic pulses encounter an interface with changed acoustic impedance, and to receive and process the signals to obtain images of internal organs. Therefore, early diagnosis and treatment are of great importance.
The existing ultrasonic composite imaging mode has the following defects: the problem of low signal-to-noise ratio exists after imaging; low resolution and low contrast problems; two-dimensional images present speckle noise and artifacts.
Disclosure of Invention
The application provides a spatial compound imaging method and a spatial compound imaging device.
According to a first aspect of the present application, there is provided a spatial compound imaging method comprising:
a data acquisition step: the probe scans the same position along different deflection directions to obtain ultrasonic images at different deflection angles;
and (3) coordinate conversion: converting the polar coordinate system of the ultrasonic image into a Cartesian coordinate system;
an image fusion step: fusing the ultrasonic images through a Kalman space composite algorithm to generate a fused image;
an image correction step: and correcting the fused image.
According to a second aspect of the present application, there is provided a spatial compound imaging apparatus comprising:
the data acquisition module is used for scanning the same position along different deflection directions by using the probe to acquire ultrasonic images at different deflection angles;
the coordinate conversion module is used for converting the polar coordinate system of the ultrasonic image into a Cartesian coordinate system;
the image fusion module is used for fusing the ultrasonic images through a Kalman space composite algorithm to generate a fusion image;
and the image correction module is used for correcting the fused image.
According to a third aspect of the present application, there is provided an ultrasonic doppler fluid signal processing apparatus comprising:
a memory for storing a program;
a processor for implementing the method as described above by executing the program stored by the memory.
According to a fourth aspect of the present application, there is provided a computer readable storage medium comprising a program executable by a processor to implement a method as described above.
Due to the adoption of the technical scheme, the beneficial effects of the application are as follows:
in a specific embodiment of the application, the method comprises the steps of fusing an ultrasonic image through a Kalman spatial compounding algorithm, generating a fused image and correcting the fused image; this application utilizes the kalman to have super high timeliness, has the advantage of congenital in the supersound field, and there is certain filtering effect to data, introduce the ultrasonic image space complex with kalman data fusion, can utilize the effectual speckle noise of suppression ultrasonic image of kalman's characteristic, adverse factor influences such as artifact, therefore the problem of low resolution and low contrast has been solved, kalman data fusion carries out dynamic programming to the weighting factor in addition, thereby make the left deviation, right deviation data better fuse, reach and fall and make an uproar and fuse the reinforcing effect.
Drawings
FIG. 1 is a schematic diagram of a conventional Kalman filtering process;
FIG. 2 is a flow chart of the method of the present application in one embodiment;
FIG. 3 is a flow chart of image processing in one embodiment of the method of the present application;
FIG. 4 is a schematic diagram of program modules of an apparatus of the present application in one embodiment.
Detailed Description
The present invention will be described in further detail with reference to the following detailed description and accompanying drawings. The present application may be embodied in many different forms and is not limited to the embodiments described in the present embodiment. The following detailed description is provided to facilitate a more thorough understanding of the present disclosure, and the words used to indicate orientation, top, bottom, left, right, etc. are used solely to describe the illustrated structure in connection with the accompanying figures.
One skilled in the relevant art will recognize, however, that one or more of the specific details can be omitted, or other methods, components, or materials can be used. In some instances, some embodiments are not described or not described in detail.
The numbering of the components as such, e.g., "first", "second", etc., is used herein only to distinguish the objects as described, and does not have any sequential or technical meaning.
Furthermore, the technical features, aspects or characteristics described herein may be combined in any suitable manner in one or more embodiments. It will be readily appreciated by those of skill in the art that the order of the steps or operations of the methods associated with the embodiments provided herein may be varied. Thus, any sequence in the figures and examples is for illustrative purposes only and does not imply a requirement in a certain order unless explicitly stated to require a certain order.
The Kalman filtering method comprises the following specific steps of:
Figure BDA0002112794450000034
the equations are the state transition equation and the measurement equation, respectively, where k represents time, x (k) is the state vector, z (k) is the measurement vector, matrix A is the state transition matrix of the system, matrix H is the measurement moment of the sensorV (k) is state noise representing noise existing in the motion process of the ultrasonic probe, w (k) is measurement noise representing noise introduced in the measurement process of the ultrasonic probe, and the variance of the system noise is set as Q and the variance of the measurement noise is set as R. FIG. 1 is a schematic view of a Kalman filtering process.
1. Deducing a state at the moment k +1 according to the state at the moment k, and updating the variance P of the state vector:
Figure BDA0002112794450000031
P(k+1|k)＝AP(k)AT+Q
2. correcting the estimated value according to the measurement information, and correcting the variance:
Figure BDA0002112794450000032
P(k+1)＝(I-K(k+1)Hk)P(k+1|k)
where the matrix K is the Kalman gain:
Figure BDA0002112794450000033
the process can finish the state estimation from the time k to the time k +1, so that the real-time estimation of the state can be finished according to the measurement information at each time as long as the initial state of the time zero is given.
The first embodiment is as follows:
as shown in fig. 2 and 3, an embodiment of the spatial compound imaging method of the present application includes the following steps:
step 202: a data acquisition step: the probe scans the same position along different deflection directions to obtain ultrasonic images at different deflection angles.
The pixel values outside the normal range of the ultrasound image are called abnormal values, and in general, the abnormal values are values outside the range of 3 standard deviations before and after the average value. Outliers in the image are classified as high and low outliers, typically caused by strong and weak echoes reflected by tissue. For ultrasound, high outliers are generally manifested in the form of lateral blurring, specular artifacts, or noise. Low outliers usually occur in areas where shadows or missing reflection information, and are generally less common. The scanning of the target object from different angles also results in differences in the set of pixel values obtained for the same target point. For the reasons, in the ultrasound field, multiple angles or multiple images are subjected to compound imaging, so that blurring and artifacts can be effectively reduced, and an ultrasound non-scannable partial area can be better visualized.
Further, step 202 may include obtaining a left-biased image, a non-biased image, and a right-biased image from the hardware layer.
Step 204: and (3) coordinate conversion: and converting the polar coordinate system of the ultrasonic image into a Cartesian coordinate system. For converting the data form into a real form, i.e. a matrix sector.
Step 206: an image fusion step: and fusing the ultrasonic images through a Kalman space composite algorithm to generate a fused image.
When Kalman fusion is carried out, fusion is carried out according to matrix arrays, and due to the fact that two-dimensional Kalman difficulty and calculation amount are large, each array is scanning data only according to actual requirements in coordinate conversion, and a large part of initial values of the data after the coordinate conversion are all 0, so that certain inhibiting effect is carried out on the Karman fusion to the fact that the initial values are too sensitive to each other to a great extent.
Further, step 206 may include: performing Kalman data fusion on the left deviation image and the right deviation image to generate the fusion image
Step 208: an image correction step: and correcting the fused image.
Further, step 208 may include:
and performing weighted superposition on the fused image and the unbiased image, wherein the weighting coefficients of the fused image and the unbiased image can be dynamically adjusted, and in the embodiment, the weighting coefficients of the fused image and the unbiased image are both 0.5.
The standard space compound method has great inhibition effect on artifacts, blurring and abnormal values.
The application utilizes Kalman to have ultrahigh timeliness, has congenital advantages in the ultrasonic field, and has a certain filtering effect on data, Kalman data fusion is introduced into ultrasonic image space compounding, adverse factor influences such as speckle noise and artifacts of ultrasonic images can be effectively inhibited by utilizing Kalman characteristics, Kalman data fusion is performed according to variances of relevant data, and dynamic planning is performed on weighting coefficients by states, so that left-handed data and right-handed data are better fused, and the effects of noise reduction and fusion enhancement are achieved.
Example two:
as shown in fig. 4, an embodiment of the spatial compound imaging apparatus according to the present application includes a data acquisition module, a coordinate transformation module, an image fusion module, and an image modification module.
The data acquisition module is used for scanning the same position along different deflection directions by using the probe to acquire ultrasonic images at different deflection angles;
and the coordinate conversion module is used for converting the polar coordinate system of the ultrasonic image into a Cartesian coordinate system.
The pixel values outside the normal range of the ultrasound image are called abnormal values, and in general, the abnormal values are values outside the range of 3 standard deviations before and after the average value. Outliers in the image are classified as high and low outliers, typically caused by strong and weak echoes reflected by tissue. For ultrasound, high outliers are generally manifested in the form of lateral blurring, specular artifacts, or noise. Low outliers usually occur in areas where shadows or missing reflection information, and are generally less common. The scanning of the target object from different angles also results in differences in the set of pixel values obtained for the same target point. For the reasons, in the ultrasound field, multiple angles or multiple images are subjected to compound imaging, so that blurring and artifacts can be effectively reduced, and an ultrasound non-scannable partial area can be better visualized.
And the image fusion module is used for fusing the ultrasonic images through a Kalman space composite algorithm to generate a fusion image.
When Kalman fusion is carried out, fusion is carried out according to matrix arrays, and due to the fact that two-dimensional Kalman difficulty and calculation amount are large, each array is scanning data only according to actual requirements in coordinate conversion, and a large part of initial values of the data after the coordinate conversion are all 0, so that certain inhibiting effect is carried out on the Karman fusion to the fact that the initial values are too sensitive to each other to a great extent.
And the image correction module is used for correcting the fused image.
The standard space compound method has great inhibition effect on artifacts, blurring and abnormal values.
Further, the data acquisition module can be used for acquiring a left-handed image, a right-handed image and a non-handed image from the hardware layer.
Further, the image fusion module can be used for performing Kalman data fusion on the left deviation image and the right deviation image to generate a fusion image.
Further, the image correction module can be further used for performing weighted superposition on the fused image and the unbiased image. The weighting coefficients of the fused image and the unbiased image can be dynamically adjusted, and in the embodiment, the weighting coefficients of the fused image and the unbiased image are both 0.5.
The application utilizes Kalman to have ultrahigh timeliness, has congenital advantages in the ultrasonic field, and has a certain filtering effect on data, Kalman data fusion is introduced into ultrasonic image space compounding, adverse factor influences such as speckle noise and artifacts of ultrasonic images can be effectively inhibited by utilizing Kalman characteristics, Kalman data fusion is performed according to variances of relevant data, and dynamic planning is performed on weighting coefficients by states, so that left-handed data and right-handed data are better fused, and the effects of noise reduction and fusion enhancement are achieved.
Example three:
the spatial compound imaging apparatus of the present application, one embodiment of which includes a memory and a processor.
A memory for storing a program;
and the processor is used for executing the program stored in the memory to realize the method in the first embodiment.
Example four:
a computer-readable storage medium containing a program which can be executed by a processor to implement the method of the first embodiment.
Those skilled in the art will appreciate that all or part of the steps of the various methods in the above embodiments may be implemented by instructions associated with hardware via a program, which may be stored in a computer-readable storage medium, and the storage medium may include: read-only memory, random access memory, magnetic or optical disk, and the like.
The foregoing is a more detailed description of the present application in connection with specific embodiments thereof, and it is not intended that the present application be limited to the specific embodiments thereof. It will be apparent to those skilled in the art from this disclosure that many more simple derivations or substitutions can be made without departing from the spirit of the disclosure.

Claims (10)

1. A method of spatially compounded imaging, comprising:
a data acquisition step: the probe scans the same position along different deflection directions to obtain ultrasonic images at different deflection angles;
and (3) coordinate conversion: converting the polar coordinate system of the ultrasonic image into a Cartesian coordinate system;
an image fusion step: fusing the ultrasonic images through a Kalman space composite algorithm to generate a fused image;
an image correction step: and correcting the fused image.
2. The method of claim 1, wherein the data acquisition step comprises acquiring a left-biased image, a non-biased image, and a right-biased image from a hardware layer.
3. The method of claim 2, wherein the image fusion step comprises:
and performing Kalman data fusion on the left deviation image and the right deviation image to generate the fused image.
4. The method of claim 3, wherein the image modification step comprises:
and performing weighted superposition on the fused image and the unbiased image, wherein the weighting coefficients of the fused image and the unbiased image are both 0.5.
5. A spatial compound imaging apparatus, comprising:
the data acquisition module is used for scanning the same position along different deflection directions by using the probe to acquire ultrasonic images at different deflection angles;
the coordinate conversion module is used for converting the polar coordinate system of the ultrasonic image into a Cartesian coordinate system;
the image fusion module is used for fusing the ultrasonic images through a Kalman space composite algorithm to generate a fusion image;
and the image correction module is used for correcting the fused image.
6. The apparatus of claim 5, wherein the data acquisition module is further to obtain a left-biased image, a non-biased image, and a right-biased image from a hardware layer.
7. The apparatus of claim 6, wherein the image fusion module is further configured to perform Kalman data fusion on the left-hand image and the right-hand image to generate the fused image.
8. The apparatus of claim 7, wherein the image modification module is further configured to perform weighted overlap of the fused image and the unbiased image, and weighting coefficients of the fused image and the unbiased image are both 0.5.
9. An ultrasonic doppler fluid signal processing apparatus, comprising:
a memory for storing a program;
a processor for implementing the method of any one of claims 1-4 by executing a program stored by the memory.
10. A computer-readable storage medium, comprising a program executable by a processor to implement the method of any one of claims 1-4.
CN201910579569.0A 2019-06-28 2019-06-28 Space compound imaging method and device Active CN112150370B (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN201910579569.0A CN112150370B (en) 2019-06-28 2019-06-28 Space compound imaging method and device

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN201910579569.0A CN112150370B (en) 2019-06-28 2019-06-28 Space compound imaging method and device

Publications (2)

Publication Number Publication Date
CN112150370A true CN112150370A (en) 2020-12-29
CN112150370B CN112150370B (en) 2024-02-06

Family

ID=73891623

Family Applications (1)

Application Number Title Priority Date Filing Date
CN201910579569.0A Active CN112150370B (en) 2019-06-28 2019-06-28 Space compound imaging method and device

Country Status (1)

Country Link
CN (1) CN112150370B (en)

Citations (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN102949205A (en) * 2011-08-25 2013-03-06 深圳市蓝韵实业有限公司 Method and system for space composite imaging
CN103505288A (en) * 2012-06-29 2014-01-15 通用电气公司 Ultrasonic imaging method and ultrasonic imaging device
CN103584882A (en) * 2012-08-13 2014-02-19 深圳市蓝韵实业有限公司 Spatial compound imaging method and device and ultrasonic imaging system
CN106605257A (en) * 2014-06-09 2017-04-26 美国西门子医疗解决公司 Landmark detection with spatial and temporal constraints in medical imaging
CN107238396A (en) * 2016-03-28 2017-10-10 美国西门子医疗解决公司 The pose recovery of ultrasonic transducer
WO2018129737A1 (en) * 2017-01-16 2018-07-19 深圳迈瑞生物医疗电子股份有限公司 Method for measuring parameters in ultrasonic image and ultrasonic imaging system
US20190180438A1 (en) * 2015-08-14 2019-06-13 Elucid Bioimaging Inc. Methods and systems for utilizing quantitative imaging

Patent Citations (8)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN102949205A (en) * 2011-08-25 2013-03-06 深圳市蓝韵实业有限公司 Method and system for space composite imaging
CN103505288A (en) * 2012-06-29 2014-01-15 通用电气公司 Ultrasonic imaging method and ultrasonic imaging device
CN103584882A (en) * 2012-08-13 2014-02-19 深圳市蓝韵实业有限公司 Spatial compound imaging method and device and ultrasonic imaging system
CN106605257A (en) * 2014-06-09 2017-04-26 美国西门子医疗解决公司 Landmark detection with spatial and temporal constraints in medical imaging
US20190180438A1 (en) * 2015-08-14 2019-06-13 Elucid Bioimaging Inc. Methods and systems for utilizing quantitative imaging
CN107238396A (en) * 2016-03-28 2017-10-10 美国西门子医疗解决公司 The pose recovery of ultrasonic transducer
WO2018129737A1 (en) * 2017-01-16 2018-07-19 深圳迈瑞生物医疗电子股份有限公司 Method for measuring parameters in ultrasonic image and ultrasonic imaging system
CN110177504A (en) * 2017-01-16 2019-08-27 深圳迈瑞生物医疗电子股份有限公司 The method and ultrasonic image-forming system of parameter measurement in ultrasound image

Non-Patent Citations (4)

* Cited by examiner, † Cited by third party
Title
S. A. QUADRI 等: "Pixel-Level Image Fusion using Kalman Algorithm", 《INTERNATIONAL JOURNAL OF SIGNAL PROCESSING, IMAGE PROCESSING AND PATTERN RECOGNITION》, pages 75 - 86 *
SHU TING GOH 等: "A Weighted Measurement Fusion Kalman Filter implementation for UAV navigation", 《 AEROSPACE SCIENCE AND TECHNOLOGY》, pages 1 - 20 *
张冬梅 等: "通信受限下网络化多传感器系统序贯卡尔曼滤波加权融合", 《控制与决策》, vol. 32, no. 12, pages 2162 - 2168 *
戴光智 等: "小波图像融合改善超声图像分辨率", 《光学精密工程》, vol. 16, no. 11, pages 2290 - 2295 *

Also Published As

Publication number Publication date
CN112150370B (en) 2024-02-06

Similar Documents

Publication Publication Date Title
EP1046058B1 (en) Method for correcting blurring of spatially compounded ultrasonic diagnostic images
US9451932B2 (en) Clutter suppression in ultrasonic imaging systems
RU2653274C2 (en) Coupled segmentation in conventional and contrast ultrasound 3d images
JP4831565B2 (en) Method and system for motion correction of ultrasonic volumetric data sets
US20080146931A1 (en) Method and apparatus of real time spatial compound imaging
US9123139B2 (en) Ultrasonic image processing with directional interpolation in order to increase the resolution of an image
US20130343627A1 (en) Suppression of reverberations and/or clutter in ultrasonic imaging systems
JP2009172381A (en) Contrast agent enhanced medical ultrasound diagnostic imaging method, computer-readable storage medium and contrast agent enhanced medical ultrasound diagnostic imaging apparatus
WO2013128301A2 (en) Clutter suppression in ultrasonic imaging systems
US9081097B2 (en) Component frame enhancement for spatial compounding in ultrasound imaging
Yao et al. Multi-view 3D echocardiography compounding based on feature consistency
US8070683B2 (en) Scan conversion for ultrasonic imaging and apparatus using the same
CN113412087A (en) Method and system for valve regurgitation assessment
US9384568B2 (en) Method and system for enhanced frame rate upconversion in ultrasound imaging
JP2023513970A (en) Methods and systems for fetal heart evaluation
US8343054B1 (en) Methods and apparatus for ultrasound imaging
CN110731795B (en) Processing method and device for spatial compound imaging
Touil et al. Analysis of motion tracking in echocardiographic image sequences: Influence of system geometry and point-spread function
JP2021529035A (en) Methods and systems for quantifying transvalvular pressure
Mirarkolaei et al. Frame rate up-conversion in cardiac ultrasound
JP6998477B2 (en) Methods and systems for color Doppler ultrasound imaging
US11529125B2 (en) Methods and systems for processing an ultrasound image
CN112150370A (en) Space compound imaging method and device
Yao et al. Spatial compounding of large sets of 3D echocardiography images
US20200237345A1 (en) Methods and systems for processing an unltrasound image

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
GR01 Patent grant
GR01 Patent grant