CN116402906B - Signal grade coding method and system based on kidney echo - Google Patents

Signal grade coding method and system based on kidney echo Download PDF

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CN116402906B
CN116402906B CN202310676044.5A CN202310676044A CN116402906B CN 116402906 B CN116402906 B CN 116402906B CN 202310676044 A CN202310676044 A CN 202310676044A CN 116402906 B CN116402906 B CN 116402906B
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echo
kidney
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coding
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CN116402906A (en
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巨学明
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Sichuan Peoples Hospital of Sichuan Academy of Medical Sciences
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Sichuan Peoples Hospital of Sichuan Academy of Medical Sciences
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    • G—PHYSICS
    • G10—MUSICAL INSTRUMENTS; ACOUSTICS
    • G10L—SPEECH ANALYSIS OR SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING; SPEECH OR AUDIO CODING OR DECODING
    • G10L25/00—Speech or voice analysis techniques not restricted to a single one of groups G10L15/00 - G10L21/00
    • G10L25/48—Speech or voice analysis techniques not restricted to a single one of groups G10L15/00 - G10L21/00 specially adapted for particular use
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    • G10L25/66—Speech or voice analysis techniques not restricted to a single one of groups G10L15/00 - G10L21/00 specially adapted for particular use for comparison or discrimination for extracting parameters related to health condition
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B8/00—Diagnosis using ultrasonic, sonic or infrasonic waves
    • A61B8/08—Detecting organic movements or changes, e.g. tumours, cysts, swellings
    • A61B8/0833—Detecting organic movements or changes, e.g. tumours, cysts, swellings involving detecting or locating foreign bodies or organic structures
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B8/00—Diagnosis using ultrasonic, sonic or infrasonic waves
    • A61B8/08—Detecting organic movements or changes, e.g. tumours, cysts, swellings
    • A61B8/0891—Detecting organic movements or changes, e.g. tumours, cysts, swellings for diagnosis of blood vessels
    • 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
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T9/00—Image coding
    • G06T9/002—Image coding using neural networks
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T9/00—Image coding
    • G06T9/20—Contour coding, e.g. using detection of edges
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V10/00—Arrangements for image or video recognition or understanding
    • G06V10/40—Extraction of image or video features
    • G06V10/42—Global feature extraction by analysis of the whole pattern, e.g. using frequency domain transformations or autocorrelation
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V10/00—Arrangements for image or video recognition or understanding
    • G06V10/40—Extraction of image or video features
    • G06V10/44—Local feature extraction by analysis of parts of the pattern, e.g. by detecting edges, contours, loops, corners, strokes or intersections; Connectivity analysis, e.g. of connected components
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V10/00—Arrangements for image or video recognition or understanding
    • G06V10/40—Extraction of image or video features
    • G06V10/56—Extraction of image or video features relating to colour
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V10/00—Arrangements for image or video recognition or understanding
    • G06V10/70—Arrangements for image or video recognition or understanding using pattern recognition or machine learning
    • G06V10/764—Arrangements for image or video recognition or understanding using pattern recognition or machine learning using classification, e.g. of video objects
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V10/00—Arrangements for image or video recognition or understanding
    • G06V10/70—Arrangements for image or video recognition or understanding using pattern recognition or machine learning
    • G06V10/82—Arrangements for image or video recognition or understanding using pattern recognition or machine learning using neural networks
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H30/00—ICT specially adapted for the handling or processing of medical images
    • G16H30/20—ICT specially adapted for the handling or processing of medical images for handling medical images, e.g. DICOM, HL7 or PACS
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H30/00—ICT specially adapted for the handling or processing of medical images
    • G16H30/40—ICT specially adapted for the handling or processing of medical images for processing medical images, e.g. editing
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V2201/00—Indexing scheme relating to image or video recognition or understanding
    • G06V2201/03—Recognition of patterns in medical or anatomical images
    • G06V2201/031—Recognition of patterns in medical or anatomical images of internal organs

Abstract

The invention provides a signal level coding method and a system based on kidney echo, wherein a request module of kidney echo coding is configured in the aspect of check coding, kidney echo coding expressed in a sound wave form is converted into a graphic interface, an echo positioning module with an echo positioning coding library, echo positioning coding input and echo signal feedback evaluation functions is configured in the aspect of an echo positioning module, a feature vector level dividing module and an echo signal feedback device are configured, meanwhile, information safety echo positioning of sub-part levels, blood vessel levels and all kidney levels is met, the method and the system are matched with a communication module, feature vector conversion and echo positioning coding input channels of transmission data in a detection kidney are completed, and an automatic echo positioning module is configured to realize safe echo positioning of kidney echo information, so that the artificial influence of safety echo positioning of the detection kidney information is effectively avoided, and the correct requirements for information safety echo positioning results are met.

Description

Signal grade coding method and system based on kidney echo
Technical Field
The invention relates to the technical field of detection intelligent medical treatment. In particular, the invention relates to a signal level coding method and system based on kidney echo.
Background
With the development of technology, big data and deep learning technology have been developed rapidly in recent years. The machine learning technology utilizes a multi-level neural network, and through the training of mass data, a computer can learn and understand complex image, sound and other data and can make corresponding behaviors. Machine learning networks can extract contrast features that are highly complex and difficult for humans to understand.
Chronic kidney disease is not obvious in early clinical symptoms, hidden from disease onset, once the disease is developed, the disease is generally difficult to recover, and if the disease is not effectively treated, the disease is likely to enter uremia finally. Because there is no strong and effective treatment means for CKD at present, early discovery, early treatment and early intervention are critical to the delay of illness. The kidney echo check has important significance for diagnosing chronic kidney diseases, and the echo check has the advantage of noninvasive property, so that the method is the first-choice image check method for kidney diseases at present. Through kidney echo examination, doctors can intuitively and dynamically observe the size, shape, edge and internal pith structure of the kidney, and the diagnosis of illness is assisted. Recent researches show that the image features obtained based on neural network deep learning can remarkably improve the capability of expressing images, but the image features obtained based on neural network deep learning are often large in dimension and are floating point numbers, and the similarity between the image features and the image features is calculated to occupy the calculation space and time.
Compared with natural images, the kidney echo image has single color, blurred edges, high similarity with the texture of other human tissues and common artifact noise. These adverse factors make it difficult to obtain effective features by statistical methods, and the conventional image processing method has large screening and diagnosis difficulty and low accuracy due to large individual variability. However, the deep learning technique often requires a large amount of data support, and has a certain limitation in the case of unbalanced medical image data and small data volume. Therefore, the echo data needs to be compressed and encoded, redundant and irrelevant information is removed on the basis of retaining the data characteristics, so that the data storage space is saved, the data transmission quantity is reduced, and the data transmission efficiency is improved.
Disclosure of Invention
In view of the above, the present invention provides a method and a system for encoding a signal level based on kidney echo.
According to a first aspect of the present invention, the present invention claims a signal level coding method based on kidney echo, applied to detecting kidney after operation, characterized in that the method comprises:
the request module sends a kidney echo positioning request to the kidney module after the operation to be tested;
The kidney module after the operation to be tested sends the kidney echo coding sound wave to the request module according to the kidney echo coding sound wave of the kidney echo positioning request acquisition part;
the request module compresses the kidney echo coded sound wave to generate a kidney echo coded picture, and sends the kidney echo coded picture to the verification terminal for processing;
the request module collects blood flow information of the kidney echo coded sound wave and sends the blood flow information to the control module;
the control module collects the echo positioning codes and sends the echo positioning codes to the kidney module after the operation to be tested through the grading module;
the kidney module after the operation to be tested carries out echo positioning on the part according to the echo positioning code, generates an echo positioning echo signal and sends the echo positioning echo signal to the echo signal feedback module;
the echo signal feedback module analyzes the echo positioning echo signal and sends the analyzed echo positioning analysis result to the control module;
and the control module determines the coding accuracy of the kidney echo coding sound wave according to the echo positioning analysis result and the processing result of the verification terminal.
Further, the kidney echo coded sound wave of the kidney echo positioning request acquisition part is sent to the request module by the kidney module after the operation to be tested according to the kidney echo coded sound wave of the kidney echo positioning request acquisition part, and the method comprises the following steps:
The kidney module after the operation to be tested determines the collected data grade according to the kidney echo positioning request;
when the data level is the level of the independent part, the kidney module after the operation to be tested acquires the kidney echo alternative data of the independent part;
when the data grade is the blood vessel grade, the kidney module after the operation to be tested collects the domain file of the blood vessel and the kidney echo alternative data of the containing part of the blood vessel;
when the data grade is the full kidney grade, the kidney module after the operation to be tested acquires the kidney echo alternative data of the full kidney;
the kidney module after the operation to be tested generates kidney echo coding sound waves according to the kidney echo alternative data of the independent part or the containing part of the blood vessel or the whole kidney, and sends the kidney echo coding sound waves to the request module.
Further, the request module compresses the kidney echo coded sound wave to generate a kidney echo coded image, and sends the kidney echo coded image to the verification terminal for processing, including:
the request module collects key parameters of the kidney echo coded sound wave;
obtaining the kidney echo coding logic relation of the part of the kidney module or the whole kidney after the operation to be tested according to the key parameters;
generating a kidney echo coding diagram according to the kidney echo coding logic relation;
And sending the kidney echo coding diagram to a verification terminal, and verifying the kidney module after the operation to be tested by the verification terminal according to the kidney echo coding diagram.
Further, the grading module is connected with the control module and the part of the kidney module after the operation to be tested;
the grading module comprises data conversion application, and the echo positioning codes sent by the control module are converted into formats and feature vectors corresponding to the parts of the kidney module after the operation to be tested;
the echo signal feedback module is respectively configured with the grading modules of different feature vectors according to the types of the grading modules.
Further, the control module determines the coding accuracy of the kidney echo coded sound wave according to the echo positioning analysis result and the processing result of the verification terminal, and the method comprises the following steps:
collecting echo positioning abnormal results of the part of the kidney module or the whole kidney after the operation to be detected from the echo positioning analysis results;
determining a calibration result sample standard table of the kidney module after the operation to be tested according to the processing result of the calibration terminal;
when the check result sample standard table is matched with the echo positioning abnormal result, the compression processing coding of the kidney echo coding sound wave is determined to be reliable;
and when the check result sample standard table is not matched with the echo positioning abnormal result, adjusting the compression processing code of the kidney echo coding sound wave.
According to a second aspect of the present invention, the present invention claims a signal level coding system based on kidney echo, applied to detecting kidney after operation, characterized in that the system comprises: the device comprises a kidney module after operation to be tested, a request module, a check terminal, a control module, an echo signal feedback module and a grading module;
the request module sends a kidney echo positioning request to the kidney module after the operation to be tested;
the kidney module after the operation to be tested sends the kidney echo coding sound wave to the request module according to the kidney echo coding sound wave of the kidney echo positioning request acquisition part;
the request module compresses the kidney echo coded sound wave to generate a kidney echo coded picture, and sends the kidney echo coded picture to the verification terminal for processing;
the request module collects blood flow information of the kidney echo coded sound wave and sends the blood flow information to the control module;
the control module collects the echo positioning codes and sends the echo positioning codes to the kidney module after the operation to be tested through the grading module;
the kidney module after the operation to be tested carries out echo positioning on the part according to the echo positioning code, generates an echo positioning echo signal and sends the echo positioning echo signal to the echo signal feedback module;
The echo signal feedback module analyzes the echo positioning echo signal and sends the analyzed echo positioning analysis result to the control module;
and the control module determines the coding accuracy of the kidney echo coding sound wave according to the echo positioning analysis result and the processing result of the verification terminal.
Further, the kidney echo coded sound wave of the kidney echo positioning request acquisition part is sent to the request module by the kidney module after the operation to be tested according to the kidney echo coded sound wave of the kidney echo positioning request acquisition part, and the method comprises the following steps:
the kidney module after the operation to be tested determines the collected data grade according to the kidney echo positioning request;
when the data level is the level of the independent part, the kidney module after the operation to be tested acquires the kidney echo alternative data of the independent part;
when the data grade is the blood vessel grade, the kidney module after the operation to be tested collects the domain file of the blood vessel and the kidney echo alternative data of the blood vessel containing part;
when the data grade is the full kidney grade, the kidney module after the operation to be tested acquires the kidney echo alternative data of the full kidney;
the kidney module after the operation to be tested generates kidney echo coding sound waves according to the kidney echo alternative data of the independent part or the containing part of the blood vessel or the whole kidney, and sends the kidney echo coding sound waves to the request module.
Further, the request module compresses the kidney echo coded sound wave to generate a kidney echo coded image, and sends the kidney echo coded image to the verification terminal for processing, including:
the request module collects key parameters of the kidney echo coded sound wave;
obtaining the kidney echo coding logic relation of the part of the kidney module or the whole kidney after the operation to be tested according to the key parameters;
generating a kidney echo coding diagram according to the kidney echo coding logic relation;
and sending the kidney echo coding diagram to a verification terminal, and verifying the kidney module after the operation to be tested by the verification terminal according to the kidney echo coding diagram.
Further, the grading module is connected with the control module and the part of the kidney module after the operation to be tested;
the grading module comprises data conversion application, and the echo positioning codes sent by the control module are converted into formats and feature vectors corresponding to the parts of the kidney module after the operation to be tested;
the echo signal feedback module is respectively configured with the grading modules of different feature vectors according to the types of the grading modules.
The control module determines the coding accuracy of the kidney echo coding sound wave according to the echo positioning analysis result and the processing result of the verification terminal, and comprises the following steps:
Collecting echo positioning abnormal results of the part of the kidney module or the whole kidney after the operation to be detected from the echo positioning analysis results;
determining a calibration result sample standard table of the kidney module after the operation to be tested according to the processing result of the calibration terminal;
when the check result sample standard table is matched with the echo positioning abnormal result, the compression processing coding of the kidney echo coding sound wave is determined to be reliable;
and when the check result sample standard table is not matched with the echo positioning abnormal result, adjusting the compression processing code of the kidney echo coding sound wave.
The invention provides a signal level coding method, a system and equipment based on kidney echo, a request module of kidney echo coding is configured in the aspect of check coding, kidney echo coding expressed in a sound wave form is converted into a graphic interface, kidney echo coding of each sub-part is combined to assist echo positioning personnel to find unnecessary source codes, destination codes, transit codes and data processing codes, an echo positioning module with an echo positioning coding library, echo positioning coding input and echo signal feedback evaluation functions is configured in the aspect of the echo positioning module, a feature vector level dividing module and an echo signal feedback device are configured, meanwhile, information safety echo positioning of sub-part levels, blood vessel levels and all kidney levels is met, the feature vector conversion and echo positioning coding input channels of transmission data in the detection kidney are completed by matching with a communication module, and the automatic echo positioning module is configured to realize safe echo positioning of kidney echo information, so that the artificial influence of the safety echo positioning of the detection kidney information is effectively avoided, and the accurate requirements on information safety echo positioning results are met.
Drawings
FIG. 1 is a flow chart of the operation of a method for encoding signal levels based on kidney echoes according to the present application;
FIG. 2 is a second embodiment workflow diagram of a renal echo based signal level coding method of the present application;
FIG. 3 is a third embodiment workflow diagram of a method of encoding signal levels based on kidney echo in accordance with the present application;
FIG. 4 is a diagram of a third embodiment of a renal echo encoding scheme for a renal echo based signal level coding scheme of the present application;
FIG. 5 is a fourth embodiment workflow diagram of a method of encoding a signal level based on renal echo in accordance with the present application;
fig. 6 is a block diagram of a signal level coding system based on kidney echo according to the present application.
Detailed Description
Exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. It will be understood that the terms "first," "second," and the like, as used herein, may be used to describe various elements, but these elements are not limited by these terms unless otherwise specified. These terms are only used to distinguish one element from another element. While exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be embodied in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art.
The invention aims to provide a signal level coding method, system and equipment based on kidney echo, which are used for solving the problems in the prior art, and performing kidney echo coding safe echo positioning on a kidney sub-part system detected by an echo positioning sample piece, so that the requirements of kidney enterprises, sub-part manufacturers, kidney detection institutions and the like for detecting the safety capacity echo positioning evaluation of the kidney echo coding of the kidney sub-part system can be met.
In the prior art, general kidney echo is only through setting up a kind of kidney echo of simply monitoring data in the whole kidney or the outside of blood vessel of detection kidney, whether the data is risky data such as dirty data, etc. discernment can not specifically form adaptive kidney echo control coding according to the logical relation between position blood vessel itself and the position.
The following is a prior art renal echo DESTINATION control code, which is located in the MRI apparatus:
considering that the original kidney MRI contrast image is small in kidney occupation volume and unfavorable for segmentation, and anatomical forms of kidneys and sub-parts in the MRI contrast images of different patients are different, the method starts from kidney and peripheral part areas related to segmentation of the kidneys and the sub-part areas to obtain rough designated areas, and then a Gaussian neural network based on pyramid pooling and gradual characteristic enhancement modules is utilized to obtain accurate segmentation results. The invention adopts a segmentation algorithm based on multi-template image registration to segment kidney and sub-part areas in an MRI contrast image. The segmentation algorithm based on multi-template image registration mainly utilizes images in an expert database, namely template images, to perform image registration with images to be segmented, and then utilizes spatial deformation parameters obtained by registration to map kidney areas marked by experts on the template images onto the images to be segmented, so that segmentation results of corresponding areas in the images to be segmented are obtained.
And acquiring a normal/kidney injury image acquired by the handheld ultrasonic probe, and performing score coding on the acquired normal/kidney injury image to serve as a training data sample and a testing data sample of the training and testing artificial intelligent model. In the data acquisition process, the ultrasonic pictures with the coded time sequence values are taken into the data set, so that the model can be trained in a targeted manner.
Referring to fig. 1, according to a first embodiment of the present invention, the present invention claims a signal level coding method based on kidney echo, applied to detecting kidney after operation, characterized in that the method includes the steps of:
s101: the request module sends a kidney echo positioning request to the kidney module after the operation to be tested;
s201: the kidney module after the operation to be tested sends the kidney echo coding sound wave to the request module according to the kidney echo coding sound wave of the kidney echo positioning request acquisition part;
s301: the request module compresses the kidney echo coded sound wave to generate a kidney echo coded picture, and sends the kidney echo coded picture to the verification terminal for processing;
s401: the request module collects blood flow information of the kidney echo coded sound wave and sends the blood flow information to the control module;
S501: the control module collects the echo positioning codes and sends the echo positioning codes to the kidney module after the operation to be tested through the grading module;
s601: the kidney module after the operation to be tested carries out echo positioning on the part according to the echo positioning code, generates an echo positioning echo signal and sends the echo positioning echo signal to the echo signal feedback module;
s701: the echo signal feedback module analyzes the echo positioning echo signal and sends the analyzed echo positioning analysis result to the control module;
s801: and the control module determines the coding accuracy of the kidney echo coding sound wave according to the echo positioning analysis result and the processing result of the verification terminal.
The request module of the kidney echo code realizes that the kidney echo code displayed by the sound wave is converted into visual graphic code, so that echo positioning personnel can intuitively and rapidly grasp the processing of the kidney echo on data and data flow direction;
the control module is internally provided with an echo positioning coding library and coding automatic input software, so that semi-automatic echo positioning for detecting the safety of kidney echo information of the kidney and the kidney echo information of the sub-part system of the kidney is realized;
the echo positioning coding library can carry out self-adaption on parameters transmitted by the kidney echo coding request module, so that different echo positioning codes are formed aiming at different echo positioning system architectures;
The control module transmits the generated echo positioning code to code automatic input software to realize semi-automatic echo positioning for detecting kidney and kidney echo information safety of sub-part system thereof after operation
The grading module realizes the conversion of the volume feature vector, the pyramid network feature vector, the ultrasonic pyramid network feature vector and the organ feature vector, and is matched with the communication module to finish the feature vector conversion of the transmission data in the detection kidney and the echo positioning coding input path.
The kidney echo positioning method and module for the detection kidney and the sub-part system thereof can simultaneously meet the information safety echo positioning of the detection kidney from the sub-part level, the blood vessel level and the full kidney level.
Further, referring to fig. 2, in accordance with a second embodiment of the present invention, a method for encoding a signal level based on renal echo, step 201 includes:
s202: the kidney module after the operation to be tested determines the collected data grade according to the kidney echo positioning request;
s203: when the data level is the level of the independent part, the kidney module after the operation to be tested acquires the kidney echo alternative data of the independent part;
s204: when the data grade is the blood vessel grade, the kidney module after the operation to be tested collects the domain file of the blood vessel and the kidney echo alternative data of the containing part of the blood vessel;
S205: when the data grade is the full kidney grade, the kidney module after the operation to be tested acquires the kidney echo alternative data of the full kidney;
s206: the kidney module after the operation to be tested generates kidney echo coding sound waves according to the kidney echo alternative data of the independent part or the containing part of the blood vessel or the whole kidney, and sends the kidney echo coding sound waves to the request module.
The kidney echo positioning request in step S202 is a feature vector format instruction, and includes an echo positioning request type of a kidney module after a measured operation, where the echo positioning request type at least includes a full kidney echo positioning request, a contrast blood vessel echo positioning request, a monitoring blood vessel echo positioning request, and an independent part echo positioning request; the echo positioning request type is identified by a specific request tag ID, the full kidney echo positioning request, the contrast blood vessel echo positioning request and the monitoring blood vessel echo positioning request correspond to corresponding integrated tag IDs, and the independent part echo positioning request is provided with independent tag IDs of parts of each independent echo positioning;
each part of the kidney module after the operation to be tested is provided with an integrated tag ID of the whole kidney echo positioning request and the corresponding blood vessel and an independent tag ID for uniquely identifying the whole kidney echo positioning request.
In step S203, it is indicated that the user performs the independent renal echo safety deployment only for the independent part of the detected kidney after the operation, the detected postoperative renal module sends a calling instruction to the corresponding echo positioning part according to the independent tag ID of the part acquired from the renal echo positioning request, and after the echo positioning part receives the calling instruction, sends a receiving signal to each encoding transmission channel of the echo positioning part itself, so that other modules are allowed to pull the renal echo alternative data;
in step S204, it is indicated that the user performs safe deployment of renal echo for a blood vessel with certain integration of the kidney detected after the operation, the detected postoperative renal module sends a calling instruction to the corresponding blood vessel according to the integrated tag ID of the blood vessel collected from the renal echo positioning request, the blood vessel sends a calling instruction to the affiliated part, and after the echo positioning part receives the calling instruction, the echo positioning part sends a receiving signal to each encoding transmission channel of the echo positioning part, so that other modules are allowed to pull renal echo alternative data;
step S205 indicates that the user performs the safe deployment of the kidney echo for the whole kidney of the detected kidney after the operation, the detected kidney module sends a calling instruction to each blood vessel according to the integrated tag ID of the whole kidney acquired from the kidney echo positioning request, the blood vessel sends a calling instruction to the affiliated part, and after the echo positioning part receives the calling instruction, the echo positioning part sends a receiving signal to each encoding transmission channel of the echo positioning part, and the other modules are allowed to pull the kidney echo candidate data;
Each coding transmission channel of the echo positioning part refers to an open and external coding transmission channel of each part, at least comprises an organ channel or is connected with the echo positioning part through a wireless network, and enters a system of the echo positioning part;
after entering the system, the kidney echo alternative data of the acoustic positioning part can be pulled back through a service or MRI equipment in the system;
in this embodiment, the deep gaussian neural network is used to identify the kidney ultrasound image, the connection layer of the deep gaussian neural network has the characteristics of sparse interaction, parameter sharing, isovariational representation and the like, the input kidney ultrasound image flow is progressively extracted from concrete to abstract, the characteristics from local to whole are extracted from hierarchy, and the gaussian calculation corresponds to the double-block cyclic matrix. The inverse residual connection layer is a special hierarchical structure comprising Gaussian calculation, and uses layer jump addition similar to ResNet blocks, but contrary to ResNet, the inverse residual connection layer adopts first-rise dimension and then-fall dimension, so that feature extraction can be performed in a high-dimension space, and the reduction of a model can be ensured, and the quantity of parameters needing to be learned is small.
In the data acquisition process, ultrasonic pictures with coded time sequence values are taken into a data set so as to train the model in a targeted manner. The core structure of the deep Gaussian neural network is a connecting layer in the network, and filtering is performed through Gaussian check input to extract characteristic information. The network generally comprises a plurality of connecting layers, wherein the layers are connected with each other, and the characteristics of higher abstraction and higher resolution are extracted from the input image step by step so as to facilitate the accurate prediction of the result by the network. Each connection layer contains numerous parameters, requiring a large number of operations to extract features. In order to enable the model to be successfully deployed on a host for use, the model optimizes the connection layer according to a design thought of reducing the number of network parameters and the calculated amount on the premise of keeping the accuracy as far as possible, and reduces the number of parameters and the calculated amount as far as possible within an acceptable accuracy range, so that the best performance of the model is achieved under the condition of limited calculation resources.
In step S206, the kidney module after the operation to be tested combines the corresponding integrated tag ID or independent tag ID according to the acquired kidney echo candidate data to form a kidney echo coded sound wave, and sends the kidney echo coded sound wave to the request module.
According to a specific implementation scenario, the kidney module after the operation to be tested at least comprises a contrast blood vessel and a monitoring blood vessel;
the site of the contrast vessel comprises at least: an ultrasonic color information part and an ultrasonic operation rear end part;
the monitoring of the location of the blood vessel comprises at least: glomerular sites, oxygenation monitoring sites, adipose tissue sites (which may include multiple adipose tissues, such as anterior, posterior, left, and right, but generally do not include intraperitoneal adipose tissue).
When a user performs renal echo safety deployment on the contrast blood vessel of the postoperative detection kidney, the tested postoperative kidney module sends a calling instruction to the contrast blood vessel of the tested postoperative kidney module according to the integrated tag ID of the contrast blood vessel acquired from the renal echo positioning request, the contrast blood vessel sends a calling instruction to the ultrasonic color information part and the ultrasonic postoperative end part, and after the echo positioning part receives the calling instruction, the echo positioning part sends a receiving signal to each coding transmission channel of the echo positioning part, so that other modules are allowed to pull renal echo alternative data.
According to the scheme, on the basis of dividing blood vessels at the position of the kidney detected after operation, targeted integrated control can be carried out on the safe deployment codes of the kidney echoes, the positions of different blood vessels are integrated together, the blood vessels are intensively deployed by the kidney echoes, the code control scheme of the kidney echoes is simplified, and the kidney echo safety guarantee of the kidney detected after operation is enhanced.
Further, referring to fig. 3, a third embodiment of a signal level coding method based on kidney echo according to the present invention is a workflow chart, and step S301 includes:
s302: the request module collects key parameters of the kidney echo coded sound wave;
s303: obtaining the kidney echo coding logic relation of the part of the kidney module or the whole kidney after the operation to be tested according to the key parameters;
s304: generating a kidney echo coding diagram according to the kidney echo coding logic relation;
s305: and sending the kidney echo coding diagram to a verification terminal, and verifying the kidney module after the operation to be tested by the verification terminal according to the kidney echo coding diagram.
In step S302, key parameters acquired from the kidney echo coded sound wave at least include an integrated tag ID or an independent tag ID, and source code and destination code information of a corresponding echo positioning part included in the coding methods such as SOURCE, PROCESS, DESTINATION;
The source code and the destination code information are deployed by collecting data streams in the historical case monitoring information of the kidney module after the operation to be tested;
in step S303, according to the source code and destination code information and the corresponding integrated tag ID of the blood vessel or the independent tag ID of the location, the association relationship of the echo positioning location is collected, and the specific data flow monitoring security code between the echo positioning location and other locations is set in the association relationship.
In step S304, the security code is monitored according to the data flow between the echo positioning part and other parts, a logic relation diagram between the echo positioning part and other parts is obtained, and the logic relation diagram is used as a kidney echo code diagram.
The request module is provided with 2 DICOM channels, a program for converting acoustic wave form kidney echo code acoustic waves into graphic compression echo signals is configured, the acoustic wave form kidney echo code importing module is configured through the DICOM channels, graphic compression kidney echo codes are exported to a computer of a verifier, and characteristic values acquired by the kidney echo code acoustic waves are taken as parameters to be imported into the control module.
In this embodiment, according to the idea that the human excretory system processes the external natural scene, the excretory model excretory information processing and encoding system is divided into three functional modules, namely binocular camera image acquisition, real-time image processing based on the ICD platform, and OLED display. The real-time image processing based on ICD mainly comprises two important processing procedures: extraction of the specified target profile and vascular physiological pattern (urine color indication) coding based on the target profile reduced information.
Data acquisition of a binocular camera: because the current artificial model of the renal tubule cannot realize high-density nerve stimulation, the stimulation channel is limited, and therefore, the pixel requirement of the image sensor is not high. In addition, considering that the excretory function repair system is implantable, it is required that its constituent components must be small in size, light in weight, and low in power consumption. Therefore, the invention selects the binocular camera with low resolution for image acquisition of the excretion model. After the data acquisition is completed, the data are transmitted to a video decoding module, and the video decoding module converts the analog signals acquired by the binocular camera into required image data for the ICD to read. This method is a general method of image acquisition.
Preprocessing an image: according to the actual application requirement, after determining the area where the specified target is located, the specified targets can be extracted through a classical image classification method, and the specified specific targets can be selected in a targeted manner. The invention is concerned with the whole scene rather than details for the scene, so the invention carries out tiny expansion processing on the image, and then carries out smoothing operation, thus ensuring the whole continuity of the image to a certain extent and eliminating some noise points in the category. On the other hand, as the simple model gridding effect still needs to be improved, the invention carries out edge detection on the preprocessed image and detects the straight line in the scene by using the Hough transformation algorithm.
In the following, according to a specific implementation scenario, the region of the contrast vessel comprises at least: an ultrasonic color information part and an ultrasonic operation rear end part;
the monitoring of the location of the blood vessel comprises at least: glomerular sites, oxygenation monitoring sites, adipose tissue sites (which may include multiple adipose tissues, such as anterior, posterior, left, and right, but generally do not include intraperitoneal adipose tissue).
The operation history case monitoring of the kidney module after the operation to be tested shows the corresponding data stream deployment condition:
historical case monitoring 1: the kidney module after the operation to be tested encounters external abnormality in daily operation, the fat tissue part broadcasts the monitored external abnormality to the inside of the kidney module after the operation to be tested through the ultrasonic color information part, and then the ultrasonic color information part is processed and then sends the external abnormality information to the glomerulus part and the end part after the operation.
Historical case monitoring 2: the detected postoperative kidney module detects oxygenation abnormality during daily operation, the oxygenation monitoring system transmits signals to an ultrasonic color information part, prompts appear on a screen of the glomerulus and the ultrasonic color information part, the ultrasonic color information part is processed and then is sent to the glomerulus and an ultrasonic postoperative end part, and the ultrasonic postoperative end part sends the event to the background and sends the event to the background.
In this embodiment, the collected echo data of each part of the kidney module after the operation to be tested and the source (source code) column, destination (destination code) column and TARGET (code) collected in the kidney echo coding file can be compared, and the echo data which cannot be matched with each other are coded, so that safety personnel can check conveniently.
Referring to fig. 4, in this embodiment, a corresponding kidney echo code map is generated specifically according to each location, where echo data of the echo positioning location a is a, and since data input of the corresponding location B, C, D is required during the historical operation of the location a, the SOURCE kidney echo code of the echo positioning location a sets the input of the permission location B, C, D as a SOURCE code (SOURCE); data output to the location E, F is required during the historical operation of the location a, so the DESTINATION kidney echo code setting of the echo location a allows output to the location E, F as a DESTINATION code (DESTINATION); the PROCESS kidney echo coding arrangement of echo location a allows for output to location G, H as source and destination codes (destination) because of the need to transit location G to location H during historical operation of location a.
However, in the subsequent echo positioning process through echo positioning coding, it is found that the neutron part C in the whole blood vessel does not actually output data to a, so that the allowable input of C as the source code of a is redundant, which may bring about a corresponding risk, so that the key coding is performed in the kidney echo coding diagram, and then the security check personnel can judge again, and measures such as corresponding, removing, relieving and the like are selected for the redundancy. Thus, the subsequent echolocation phase of the echolocation encoding adjusts the renal echolocation encoding map. According to the embodiment, the kidney echo codes of the multiple sub-parts are integrated, redundant source codes, destination codes, transfer codes and the like are subjected to key codes, so that safety check staff can conveniently and quickly master each data processing stage of the tested system architecture, and the safety check staff is assisted in carrying out safety treatment codes on each risk.
Wherein in this embodiment, neurophysiological urine color index coding based on target contours is required: and executing real urine color indication modes presented by the tubular cortex under the experimental condition of microelectrode stimulation, wherein the urine color indication modes correspond to different microelectrode stimulation modes respectively. The present invention uses these basic urine color indication patterns to express the contours of a specified target. Thus, each specific target profile is composed of a different urine color indication pattern, corresponding to a specific microelectrode stimulation pattern combination. Thus, the target can be perceived by the specific microelectrode stimulation combination and the coded information of the target can be transmitted to the brain through the blood vessel of the subject.
After the target of the specified pedestrian walkway is extracted from the video image, the gridding and outline extraction of the target and the outline thereof are completed, the urine color indication mode is required to be adopted for combined coding, and the task of the link is completed by adopting a mode matching method. This step can be said to be a reconstruction of the extracted specified target under the framework of urine color indication pattern coding, which can be regarded approximately as an inverse of the image processing.
Further, the grading module is connected with the control module and the part of the kidney module after the operation to be tested;
the grading module comprises data conversion application, and the echo positioning codes sent by the control module are converted into formats and feature vectors corresponding to the parts of the kidney module after the operation to be tested;
the echo signal feedback module is respectively configured with the grading modules of different feature vectors according to the types of the grading modules.
The control module is configured with 2 DICOM channels and pyramid network ports, is configured with echo positioning coding input codes, and inputs the echo positioning codes to the grading module through the DICOM channels.
The control module echo positioning code comprises an echo positioning code generated according to the parameters transmitted by the kidney echo code request module.
The grading module configures a pyramid network to ultrasonic pyramid network feature vector grading module to complete pyramid network to ultrasonic pyramid network feature vector conversion.
And the connection line of the control module and the grading module adopts pyramid network twisted pair for the pyramid network gateway.
The echo signal feedback module configures an ultrasonic pyramid network to pyramid network feature vector grading module.
In this embodiment, an experiment of encoding is performed using a urine fluorescent agent as an example, a binocular camera is used to collect an image of the urine fluorescent agent, and the collected analog signal is converted into a digital signal that can be read by an ICD by using a video decoding module.
The image is preprocessed, and the black urine fluorescent agent is directly adopted in the experiment, so that the gray processing process of the image is avoided. When the urine fluorescent agent image is acquired, the urine fluorescent agent image is inevitably influenced by external factors, so that the median filtering is adopted to protect the edge information of the urine fluorescent agent, the isolated noise point is eliminated, and convenience is provided for the following target extraction.
The specific objective is extracted, and because the problems of the study are specific, the selective drainage attention method of fusion of top-down (based on priori knowledge) and bottom-up (based on image information) is adopted to complete.
After determining the area where the specified targets are located (i.e. urine fluorescent agent), the specified targets need to be extracted by an image gridding method, images are processed based on a Markov random field model, the images are composed of a finite set S corresponding to pixels, different neighborhood structures exist in S, when each pair of different positions in the subset c epsilon S are always adjacent, c is called a potential, and c represents the set of potential sets. The potential energy of the potential set can be used to represent the local interaction between gray scales at adjacent positions. There is a potential set c, the corresponding potential is set, and its value is determined by the gray value of the pixel component of the potential set. Thus, the total energy of an image can be defined as the sum of the potential energies of all potential sets, while the local energy of a location is defined as the sum of the potential energies of all potential sets to which the location belongs.
Further, performing echo positioning for the location in step 601 mainly includes:
and simulating echo positioning, and constructing various complex and dangerous scenes to echo-position the edge scene of the kidney echo safety code. And adding part of the kidney part and the blood vessel part into a simulated echo positioning system, and performing echo positioning aiming at a regulation system for safety control of kidney echo, for example, performing simulated echo positioning on part of a sensor, a controller or an actuator of the kidney part and the blood vessel which is embedded into a simulated loop. The actual kidney echolocation is used for detecting the control of the internal part or the blood vessel on the whole kidney and the real feedback of the kidney part and the blood vessel on the internal part or the blood vessel, but many risk scenes in the actual kidney echolocation cannot be subjected to the echolocation.
The complete kidney part and the vascular system are embedded into the simulation loop to perform simulation echo positioning, and the simulation echo positioning can be understood as a virtual-real combination method combining the simulation echo positioning and the actual kidney echo positioning, so that the actual kidney echo positioning problem in a risk scene can be solved to a certain extent.
The method comprises the steps of carrying out echo positioning on an internal part or a blood vessel by combining real echo positioning kidney part and blood vessel with simulation environment information, simulating scene and sensor information by using simulation software, transmitting the sensor information to the internal part or the blood vessel, controlling the operation of the real echo positioning kidney part and the blood vessel by the internal part or the blood vessel, and synchronizing motion echo signals of the real echo positioning kidney part and the blood vessel into the simulation environment. Thus, by using the real kidney part and the blood vessel, the real kidney part and the blood vessel feedback echo signal and the internal part or the control system of the blood vessel to the real kidney part and the blood vessel can be better detected; in addition, all postoperative participants are virtual, any dangerous scene can be repeatedly constructed to carry out echo positioning, various risks in actual kidney echo positioning are avoided, and actual kidney echo positioning under the dangerous scene is realized.
Simulating a kidney echo attack scene, for example, a postoperative simulation scene, through simulation software, and obtaining a simulation signal through a simulated sensor model; then, the simulation signal is transmitted to the internal part or the blood vessel to be tested, and the operation of the echo positioning kidney part and the blood vessel is controlled by the internal part or the blood vessel. The simulation software can transmit simulation signals to a mobile data center carrying an internal part or a blood vessel, and the blood vessel sends out control instructions to control the operation of the echo positioning kidney part and the blood vessel. The simulation signal may be used to indicate that an obstacle is detected or to indicate a motion profile, etc. The echo positioning kidney part and the motion echo signals on the blood vessel can be fed back to simulation software. For example, the high-precision positioning system on the echo positioning kidney part and the blood vessel outputs the positioning information of the echo positioning kidney part and the blood vessel in real time, and the positioning information can be fed back to the simulation software in the form of a position vector. This ensures that the motion echo signals of the virtual echo-located kidney part and the blood vessel in the simulation software are consistent with those in the real scene, for example, the positions of the virtual echo-located kidney part and the blood vessel are consistent with those of the echo-located kidney part and the blood vessel in the real scene. The simulation software further updates the simulation signals according to the positions of the echo positioning kidney part and the blood vessel, and transmits the simulation signals to the internal part or the blood vessel, so as to form a closed-loop virtual-real combined echo positioning system based on the simulation signals. For example, the motion echo signal of the echolocation kidney location and blood vessel may also include the velocity of the echolocation kidney location and blood vessel, steering wheel steering angle, etc.
For example, the simulation software may also render the simulated kidney echo attack scenario, i.e., the virtual scenario, to generate a compressed perspective output to the echolocation kidney site and the blood vessel, e.g., in video form. Further, referring to fig. 5, the echo signal feedback module in step 701 analyzes the echo positioning echo signal mainly includes:
s702: after sending the echo positioning code to the echo positioning part, receiving an echo positioning analysis result of the echo positioning part;
s703: generating an update confirmation instruction based on the echo positioning analysis result, and sending the update confirmation instruction to the echo signal feedback module for analysis, wherein the update confirmation instruction is used for confirming whether the echo signal feedback module corresponds to the echo positioning analysis result;
s704: receiving an update confirmation instruction returned by the echo signal feedback module;
s705: if the echo signal feedback module is confirmed to correspond to the echo positioning analysis result in the returned updating confirmation instruction, updating the echo positioning code in the code library based on the echo positioning analysis result;
s706: if the echo signal feedback module refuses the corresponding echo positioning analysis result in the returned updating confirmation instruction, the analysis result of the echo positioning analysis result is sent to the echo positioning part until the echo positioning part gives up to feed back again, or the new echo positioning analysis result of the echo positioning part is received and is analyzed by the echo signal feedback module and then the corresponding echo positioning analysis result is confirmed.
Further, step S801 includes:
collecting echo positioning abnormal results of the part of the kidney module or the whole kidney after the operation to be detected from the echo positioning analysis results;
determining a calibration result sample standard table of the kidney module after the operation to be tested according to the processing result of the calibration terminal;
when the check result sample standard table is matched with the echo positioning abnormal result, the compression processing coding of the kidney echo coding sound wave is determined to be reliable;
and when the check result sample standard table is not matched with the echo positioning abnormal result, adjusting the compression processing code of the kidney echo coding sound wave.
According to another embodiment of the present invention, referring to fig. 6, the present invention claims a signal level coding system based on kidney echo, which is applied to detecting kidney after operation, and is characterized in that the system comprises: the device comprises a kidney module after operation to be tested, a request module, a check terminal, a control module, an echo signal feedback module and a grading module;
the request module sends a kidney echo positioning request to the kidney module after the operation to be tested;
the kidney module after the operation to be tested sends the kidney echo coding sound wave to the request module according to the kidney echo coding sound wave of the kidney echo positioning request acquisition part;
The request module compresses the kidney echo coded sound wave to generate a kidney echo coded picture, and sends the kidney echo coded picture to the verification terminal for processing;
the request module collects blood flow information of the kidney echo coded sound wave and sends the blood flow information to the control module;
the control module collects the echo positioning codes and sends the echo positioning codes to the kidney module after the operation to be tested through the grading module;
the kidney module after the operation to be tested carries out echo positioning on the part according to the echo positioning code, generates an echo positioning echo signal and sends the echo positioning echo signal to the echo signal feedback module;
the echo signal feedback module analyzes the echo positioning echo signal and sends the analyzed echo positioning analysis result to the control module;
and the control module determines the coding accuracy of the kidney echo coding sound wave according to the echo positioning analysis result and the processing result of the verification terminal.
Further, the kidney echo coded sound wave of the kidney echo positioning request acquisition part is sent to the request module by the kidney module after the operation to be tested according to the kidney echo coded sound wave of the kidney echo positioning request acquisition part, and the method comprises the following steps:
the kidney module after the operation to be tested determines the collected data grade according to the kidney echo positioning request;
When the data level is the level of the independent part, the kidney module after the operation to be tested acquires the kidney echo alternative data of the independent part;
when the data grade is the blood vessel grade, the kidney module after the operation to be tested collects the domain file of the blood vessel and the kidney echo alternative data of the blood vessel containing part;
when the data grade is the full kidney grade, the kidney module after the operation to be tested acquires the kidney echo alternative data of the full kidney;
the kidney module after the operation to be tested generates kidney echo coding sound waves according to the kidney echo alternative data of the independent part or the containing part of the blood vessel or the whole kidney, and sends the kidney echo coding sound waves to the request module.
Further, the request module compresses the kidney echo coded sound wave to generate a kidney echo coded image, and sends the kidney echo coded image to the verification terminal for processing, including:
the request module collects key parameters of the kidney echo coded sound wave;
obtaining the kidney echo coding logic relation of the part of the kidney module or the whole kidney after the operation to be tested according to the key parameters;
generating a kidney echo coding diagram according to the kidney echo coding logic relation;
and sending the kidney echo coding diagram to a verification terminal, and verifying the kidney module after the operation to be tested by the verification terminal according to the kidney echo coding diagram.
Further, the grading module is connected with the control module and the part of the kidney module after the operation to be tested;
the grading module comprises data conversion application, and the echo positioning codes sent by the control module are converted into formats and feature vectors corresponding to the parts of the kidney module after the operation to be tested;
the echo signal feedback module is respectively configured with the grading modules of different feature vectors according to the types of the grading modules.
The control module determines the coding accuracy of the kidney echo coding sound wave according to the echo positioning analysis result and the processing result of the verification terminal, and comprises the following steps:
collecting echo positioning abnormal results of the part of the kidney module or the whole kidney after the operation to be detected from the echo positioning analysis results;
determining a calibration result sample standard table of the kidney module after the operation to be tested according to the processing result of the calibration terminal;
when the check result sample standard table is matched with the echo positioning abnormal result, the compression processing coding of the kidney echo coding sound wave is determined to be reliable;
and when the check result sample standard table is not matched with the echo positioning abnormal result, adjusting the compression processing code of the kidney echo coding sound wave.
Those skilled in the art will appreciate that various modifications and improvements can be made to the disclosure. For example, the various devices or components described above may be implemented in hardware, or may be implemented in software, firmware, or a combination of some or all of the three.
A flowchart is used in this disclosure to describe the steps of a method according to an embodiment of the present disclosure. It should be understood that the steps that follow or before do not have to be performed in exact order. Rather, the various steps may be processed in reverse order or simultaneously. Also, other operations may be added to these processes.
Those of ordinary skill in the art will appreciate that all or a portion of the steps of the methods described above may be performed by a computer program to instruct associated hardware and that the program may be stored in a computer readable storage medium such as a read only memory, a magnetic or urine disk, etc. Alternatively, all or part of the steps of the above embodiments may be implemented using one or more integrated circuits. Accordingly, each module/unit in the above embodiment may be implemented in the form of hardware, or may be implemented in the form of a software functional module. The present disclosure is not limited to any specific form of combination of hardware and software.
Unless defined otherwise, all terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this disclosure pertains. It will be further understood that terms, such as those defined in commonly used dictionaries, should be interpreted as having a meaning that is consistent with their meaning in the context of the relevant art and will not be interpreted in an idealized or overly formal sense unless expressly so defined herein.
The foregoing is illustrative of the present disclosure and is not to be construed as limiting thereof. Although a few exemplary embodiments of this disclosure have been described, those skilled in the art will readily appreciate that many modifications are possible in the exemplary embodiments without materially departing from the novel teachings and advantages of this disclosure. Accordingly, all such modifications are intended to be included within the scope of this disclosure as defined in the claims. It is to be understood that the foregoing is illustrative of the present disclosure and is not to be construed as limited to the specific embodiments disclosed, and that modifications to the disclosed embodiments, as well as other embodiments, are intended to be included within the scope of the appended claims. The disclosure is defined by the claims and their equivalents.
In the description of the present specification, reference to the terms "one embodiment," "some embodiments," "illustrative embodiments," "examples," "specific examples," or "some examples," etc., means that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the invention. In this specification, schematic representations of the above terms do not necessarily refer to the same embodiments or examples. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.
While embodiments of the present invention have been shown and described, it will be understood by those of ordinary skill in the art that: many changes, modifications, substitutions and variations may be made to the embodiments without departing from the spirit and principles of the invention, the scope of which is defined by the claims and their equivalents.

Claims (6)

1. A signal level coding method based on kidney echo, applied to detecting kidney after operation, characterized in that the method comprises:
the request module sends a kidney echo positioning request to the kidney module after the operation to be tested;
the kidney module after the operation to be tested sends the kidney echo coded sound wave to the request module according to the kidney echo coded sound wave of the kidney echo positioning request acquisition part;
the request module compresses the kidney echo coded sound wave to generate a kidney echo coded picture, and sends the kidney echo coded picture to a verification terminal for processing;
the request module acquires blood flow information of the kidney echo coded sound wave and sends the blood flow information to the control module;
the control module acquires echo positioning codes and sends the echo positioning codes to the kidney module after the operation to be tested through the grading module;
The kidney module carries out echo positioning on the part according to the echo positioning code, generates an echo positioning echo signal and sends the echo positioning echo signal to an echo signal feedback module;
the echo signal feedback module analyzes the echo positioning echo signal and sends an analyzed echo positioning analysis result to the control module;
the control module determines the coding accuracy of the kidney echo coding sound wave according to the echo positioning analysis result and the processing result of the verification terminal;
the grading module is connected with the control module and the part of the kidney module after the operation to be tested;
the grading module comprises a data conversion application, and the echo positioning codes sent by the control module are converted into a format and a feature vector corresponding to the part of the kidney module after the operation to be tested;
the echo signal feedback module is respectively configured with the grading modules of different feature vectors according to the types of the grading modules;
the control module determines the coding accuracy of the kidney echo coding sound wave according to the echo positioning analysis result and the processing result of the check terminal, and comprises the following steps:
Collecting echo positioning abnormal results of the part of the kidney module or the whole kidney after the operation to be detected from the echo positioning analysis results;
determining a calibration result sample standard table of the kidney module after the operation to be tested according to the processing result of the calibration terminal;
when the calibration result sample standard table is matched with the echo positioning abnormal result, the compression processing coding of the kidney echo coding sound wave is confirmed to be reliable;
and when the check result sample standard table is not matched with the echo positioning abnormal result, adjusting the compression processing code of the kidney echo coding sound wave.
2. A method of signal level coding based on renal echo as claimed in claim 1, wherein:
the kidney module after the operation to be tested sends the kidney echo coded sound wave to the request module according to the kidney echo coded sound wave of the kidney echo positioning request acquisition part, and the kidney echo coded sound wave comprises the following components:
the kidney module after the operation to be tested determines the collected data grade according to the kidney echo positioning request;
when the data grade is an independent part grade, the kidney module after the operation to be tested acquires kidney echo alternative data of the independent part;
When the data grade is a blood vessel grade, the kidney module after the operation to be tested acquires a domain file of the blood vessel and kidney echo alternative data of a containing part of the blood vessel;
when the data grade is the full kidney grade, the kidney module after the operation to be tested acquires kidney echo alternative data of the full kidney;
the kidney module after the operation to be tested generates kidney echo coding sound waves according to the kidney echo alternative data of the independent part or the containing part of the blood vessel or the whole kidney, and sends the kidney echo coding sound waves to the request module.
3. A method of signal level coding based on renal echo as claimed in claim 1, wherein:
the request module compresses the kidney echo coded sound wave to generate a kidney echo coded picture, and sends the kidney echo coded picture to a verification terminal for processing, and the method comprises the following steps:
the request module acquires key parameters of the kidney echo coded sound wave;
obtaining the kidney echo coding logic relation of the part of the kidney module or the whole kidney after the operation to be tested according to the key parameters;
generating a kidney echo coding diagram according to the kidney echo coding logic relation;
And sending the kidney echo coding diagram to a verification terminal, and verifying the kidney module after the operation to be tested by the verification terminal according to the kidney echo coding diagram.
4. A signal level coding system based on kidney echo, applied to detecting kidney after operation, characterized in that the system comprises: the device comprises a kidney module after operation to be tested, a request module, a check terminal, a control module, an echo signal feedback module and a grading module;
the request module sends a kidney echo positioning request to a kidney module after the operation to be tested;
the kidney module after the operation to be tested sends the kidney echo coded sound wave to the request module according to the kidney echo coded sound wave of the kidney echo positioning request acquisition part;
the request module compresses the kidney echo coded sound wave to generate a kidney echo coded image, and sends the kidney echo coded image to the verification terminal for processing;
the request module acquires blood flow information of the kidney echo coded sound wave and sends the blood flow information to the control module;
the control module acquires echo positioning codes and sends the echo positioning codes to the kidney module after the operation to be tested through the grading module;
The kidney module after the operation to be tested carries out echo positioning on the part according to the echo positioning code, generates an echo positioning echo signal and sends the echo positioning echo signal to the echo signal feedback module;
the echo signal feedback module analyzes the echo positioning echo signal and sends an analyzed echo positioning analysis result to the control module;
the control module determines the coding accuracy of the kidney echo coding sound wave according to the echo positioning analysis result and the processing result of the verification terminal;
the grading module is connected with the control module and the part of the kidney module after the operation to be tested;
the grading module comprises a data conversion application, and the echo positioning codes sent by the control module are converted into a format and a feature vector corresponding to the part of the kidney module after the operation to be tested;
the echo signal feedback module is respectively configured with the grading modules of different feature vectors according to the types of the grading modules;
the control module determines the coding accuracy of the kidney echo coding sound wave according to the echo positioning analysis result and the processing result of the check terminal, and comprises the following steps:
Collecting echo positioning abnormal results of the part of the kidney module or the whole kidney after the operation to be detected from the echo positioning analysis results;
determining a calibration result sample standard table of the kidney module after the operation to be tested according to the processing result of the calibration terminal;
when the calibration result sample standard table is matched with the echo positioning abnormal result, the compression processing coding of the kidney echo coding sound wave is confirmed to be reliable;
and when the check result sample standard table is not matched with the echo positioning abnormal result, adjusting the compression processing code of the kidney echo coding sound wave.
5. A renal echo based signal level coding system as in claim 4 wherein:
the kidney module after the operation to be tested sends the kidney echo coded sound wave to the request module according to the kidney echo coded sound wave of the kidney echo positioning request acquisition part, and the kidney echo coded sound wave comprises the following components:
the kidney module after the operation to be tested determines the collected data grade according to the kidney echo positioning request;
when the data grade is an independent part grade, the kidney module after the operation to be tested acquires kidney echo alternative data of the independent part;
When the data grade is a blood vessel grade, the kidney module after the operation to be tested acquires a domain file of the blood vessel and kidney echo alternative data of the blood vessel containing part;
when the data grade is the full kidney grade, the kidney module after the operation to be tested acquires kidney echo alternative data of the full kidney;
the kidney module after the operation to be tested generates kidney echo coding sound waves according to the kidney echo alternative data of the independent part or the containing part of the blood vessel or the whole kidney, and sends the kidney echo coding sound waves to the request module.
6. A renal echo based signal level coding system as in claim 5 wherein:
the request module compresses the kidney echo coded sound wave to generate a kidney echo coded image, and sends the kidney echo coded image to the verification terminal for processing, and the method comprises the following steps:
the request module acquires key parameters of the kidney echo coded sound wave;
obtaining the kidney echo coding logic relation of the part of the kidney module or the whole kidney after the operation to be tested according to the key parameters;
generating a kidney echo coding diagram according to the kidney echo coding logic relation;
And sending the kidney echo coding diagram to a verification terminal, and verifying the kidney module after the operation to be tested by the verification terminal according to the kidney echo coding diagram.
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