WO2019047365A1 - Système d'analyse de mégadonnées d'image basé sur une plateforme cloud médicale, et procédé - Google Patents

Système d'analyse de mégadonnées d'image basé sur une plateforme cloud médicale, et procédé Download PDF

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Publication number
WO2019047365A1
WO2019047365A1 PCT/CN2017/110476 CN2017110476W WO2019047365A1 WO 2019047365 A1 WO2019047365 A1 WO 2019047365A1 CN 2017110476 W CN2017110476 W CN 2017110476W WO 2019047365 A1 WO2019047365 A1 WO 2019047365A1
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WO
WIPO (PCT)
Prior art keywords
image
user
organ
tissue structure
local
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PCT/CN2017/110476
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English (en)
Chinese (zh)
Inventor
姚育东
钱唯
郑斌
马贺
齐守良
赵明芳
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深圳市前海安测信息技术有限公司
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Publication of WO2019047365A1 publication Critical patent/WO2019047365A1/fr

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Classifications

    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T1/00—General purpose image data processing
    • G06T1/0007—Image acquisition
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T5/00—Image enhancement or restoration
    • G06T5/70—Denoising; Smoothing
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/0002—Inspection of images, e.g. flaw detection
    • G06T7/0012—Biomedical image inspection
    • G06T7/0014—Biomedical image inspection using an image reference approach
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/40—Analysis of texture
    • 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
    • G06T2207/10048—Infrared 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
    • G06T2207/20016—Hierarchical, coarse-to-fine, multiscale or multiresolution image processing; Pyramid transform
    • 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
    • G06T2207/20092—Interactive image processing based on input by user
    • G06T2207/20104—Interactive definition of region of interest [ROI]
    • 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

Definitions

  • the present invention relates to the field of medical image processing and recognition technologies, and in particular, to an image big data analysis system and method based on a medical cloud platform.
  • the main objective of the present invention is to provide an image big data analysis system and method based on a medical cloud platform, which is convenient for users to perform physical body organ health screening, save limited hospital resources, and can assist doctors to improve body parts. The efficiency and accuracy of organ disease detection and screening.
  • the present invention provides an image big data analysis system based on a medical cloud platform, which is applied to a cloud server, and the cloud server is connected to an image collection terminal, a medical cloud platform, and a doctor diagnosis and treatment terminal through a communication network.
  • the image big data analysis system includes:
  • an image acquisition module configured to acquire image data including information about a local tissue structure of a user body from the image capturing terminal, and process image data including information about the local tissue structure of the user body as an inspection image of the user
  • an image processing module configured to perform a distortion-free noise filtering process and perform gray level layering processing on the inspection image
  • an image analysis module configured to acquire a normal image of the body part of the user from an image database of the medical cloud platform, and compare a texture distribution difference between the processed inspection image and the body local normal image to perform the inspection from the inspection Extracting the image texture feature area from the image;
  • an image output module configured to mark the organ texture feature area in the grayscale layered inspection image
  • the image capturing terminal comprises an input unit, an infrared generator, an infrared receiver, an analog to digital converter and a communication port, wherein:
  • the infrared generator is configured to generate infrared light and fluoresce the infrared light to a local organ of the user's body;
  • the infrared receiver is configured to collect infrared light signals transmitted through a local organ of the user's body and process the body part organs Analog electrical signal of organizational structure information;
  • the analog-to-digital converter is configured to perform analog-to-digital conversion of an analog electrical signal, which is collected by an infrared receiver, including local body tissue structure information of the user, into image data including local body tissue structure information of the user;
  • the communication port is configured to send image data including the body tissue structure information of the user to the cloud server through the communication network.
  • the image capturing module records image data in the form of a digital file by using digital image processing software to record image data of the user's body tissue structure information, and generates a user's inspection image according to the image data.
  • the image database stores body part normal images collected by different users in a body part organ health checkup and a general survey
  • the body part normal image is a body part organ image in a user's body part organ health state.
  • the difference in texture distribution includes differences in tissue structure, size difference, and contour difference of local organs of the body.
  • the grayscale layering process comprises dividing the inspection image into different regions according to grayscale and performing color assignment processing on each region.
  • the present invention provides an image big data analysis method based on a medical cloud platform, which is applied to a cloud server, and the cloud server is connected to an image capturing terminal, a medical cloud platform, and a doctor's medical treatment through a communication network.
  • the method includes the steps of: acquiring image data including information about the local tissue structure of the user body from the image capturing terminal; processing the image data including the local tissue structure information of the user body as the inspection image; and performing the distortion-free noise removal on the inspection image Filtering processing and performing grayscale layering processing; acquiring a normal image of the body part of the user from the image database of the medical cloud platform, and comparing the texture distribution difference between the processed inspection image and the body local normal image to Extracting an organ texture feature region from the image; marking the organ texture feature region in the grayscale layered inspection image, and transmitting the inspection image indicating the organ texture feature region to the doctor diagnosis terminal through the communication unit For the doctor to diagnose and screen the body parts for reference.
  • the image capturing terminal includes an input unit, an infrared generator, an infrared receiver, an analog-to-digital converter, and a communication port, and the step of acquiring image data including information about the local tissue structure of the user from the image capturing terminal is performed.
  • the method comprises: generating infrared light through an infrared generator and seeing the infrared light on a local organ of the user body; collecting an infrared light signal transmitted through a local organ of the user body through the infrared receiver and processing the analog electrical signal as the tissue structure information of the body part of the body; Using an analog-to-digital converter, the analog electrical signal collected by the infrared receiver and containing the information about the local tissue structure of the user's body is converted into image data containing local body tissue structure information of the user's body; and the user's body tissue structure is included through the communication port.
  • the image data of the information is sent to the cloud server through the communication network.
  • the step of processing the image data including the user's body tissue structure information as the image inspection comprises: recording the image data of the user's body tissue structure information in the form of a digital file by using digital image processing software Data; generating an inspection image of the user based on the image data.
  • the image database stores body part normal images collected by different users in a body part organ health checkup and screening, and the body part normal image is a body part organ collected by the user's body part organ health state.
  • the image, the difference in texture distribution includes differences in tissue structure, size difference, and contour difference of body parts of the body.
  • the grayscale layering process comprises dividing the inspection image into different regions according to grayscale and performing color assignment processing on each region.
  • the image data analysis system and method based on the medical cloud platform of the present invention are The image collection terminal set up in each community medical workstation collects the user's inspection image, which is convenient for the user to perform physical examination of the body part organ and body part organ screening, thereby saving limited hospital resources.
  • the organ texture feature region is extracted from the processed inspection image and the organ texture feature region is marked in the inspection image and sent to the doctor's medical treatment terminal for the doctor.
  • Provide reference for the diagnosis and screening of local organ diseases so as to help doctors improve the efficiency and accuracy of detection and screening of body parts and diseases, and improve the social efficiency of body partal organ screening.
  • FIG. 1 is a schematic diagram of an application environment of a preferred embodiment of a medical big data analysis system based on a medical cloud platform according to the present invention
  • FIG. 2 is a flow chart of a preferred embodiment of the image big data analysis method based on the medical cloud platform of the present invention.
  • FIG. 1 is a schematic diagram of an application environment of a preferred embodiment of an image big data analysis system based on a medical cloud platform according to the present invention.
  • the image big data analysis system 10 is installed and runs in the cloud server 1.
  • the cloud server 1 establishes a communication connection with the medical cloud platform 2, the image capturing terminal 4, and the doctor's medical treatment terminal 5 via the communication network 3.
  • the cloud server 1 can be a computing device having data processing and communication functions, such as a computer or a server.
  • the medical cloud platform 2 can be a server or a server in a medical information system platform, and provides a data interface for a medical inspection institution such as a regional hospital or a community medical workstation, and can receive inspection images of each medical inspection institution.
  • the medical cloud platform 2 includes an image database 20, and the image database 20 stores body normal images of different body users in the past for performing physical examinations and physical examinations of body parts, and the body part normal images are user body parts. An image of a part of the body collected by the official in a healthy state.
  • the communication network 3 may be an internet network including a local area network, a wide area network, or a wireless transmission network including GSM, GPRS, and CDMA.
  • the doctor's medical treatment terminal 5 is a doctor's workstation computer installed in a body part organ examination center or a large hospital for displaying an examination image, and the doctor diagnoses and screens the user's body part organ health condition according to the examination image.
  • the image capturing terminal 4 is disposed in a medical examination institution such as a community medical workstation, and the image capturing terminal 4 includes an infrared generator 41, an infrared receiver 42, an analog to digital converter 43, and a communication port 44.
  • the infrared generator 41 is configured to generate infrared light and fluoresce the infrared light to a local organ of the user's body;
  • the infrared receiver 42 is configured to collect infrared light signals transmitted through the local organs of the user body and process the image information of the body part organs.
  • the analog-to-digital converter 43 is configured to perform analog-to-digital conversion of the analog electrical signal containing the image information of the local body organ of the user collected by the infrared receiver 42 into a digital signal containing image information of the local body organ of the user;
  • the communication port 44 is configured to transmit user information and a digital signal including the user's body part organ image information to the cloud server 1 through the communication network 3.
  • the communication port 44 can be a wireless communication interface with remote wireless communication functions, such as a communication interface supporting GSM, GPRS, and CDMA.
  • the cloud server 1 includes, but is not limited to, an image big data analysis system 10, a storage unit 11, a processing unit 12, and a communication unit 13.
  • the storage unit 11, the processing unit 12 and the communication unit 13 are all connected to the processing unit 12 via a data bus, and can perform information interaction with the image big data analysis system 10 through the processing unit 12.
  • the storage unit 11 may be a read only storage unit R OM , an electrically erasable storage unit EEPROM or a flash storage unit FLASH or the like.
  • the processing unit 12 can be a central processing unit (CPU), a microprocessor, a microcontroller (MCU), a data processing chip, or an information processing unit having data processing functions.
  • the communication unit 13 can be a wireless communication interface with remote wireless communication functions, such as a communication interface supporting GSM, GPRS, CDMA.
  • the image big data analyzing system 10 includes, but is not limited to, an image capturing module 101, an image processing module 102, an image analyzing module 103, and an image output module 104.
  • the module referred to in the present invention refers to a series of computer program instruction segments that can be executed by the processing unit 12 of the cloud server 1 and that can perform fixed functions, which are stored in the storage unit 11 of the cloud server 1. Following knot Figure 2 is a detailed description of the functions of the modules of the present invention.
  • FIG. 2 is a flow chart of a preferred embodiment of the image data analysis method based on the medical cloud platform of the present invention.
  • the image big data analysis method based on the medical cloud platform in the embodiment together with FIG. 1 includes the following steps:
  • Step S21 Obtain image data including the local tissue structure information of the user body from the image capturing terminal.
  • the image capturing module 101 acquires an image including the local tissue structure information of the user body from the image capturing terminal 4 through the communication unit 13. data.
  • the infrared generator 41 of the image capturing terminal 4 generates infrared light and sees the infrared light to a local organ of the user's body; the infrared receiver 42 of the image capturing terminal 4 collects infrared light signals transmitted through the local organs of the user's body and processes them into local organs of the body.
  • the analog electrical signal of the tissue structure information; the infrared light generated by the infrared generator 41 is fluorinated to a local organ of the user's body, and the infrared light signal received by the infrared receiver 42 carries the infrared transmitted light of the body tissue structure information of the body.
  • the analog-to-digital converter 43 of the image capturing terminal 4 converts the analog electrical signal containing the user's body tissue structure information collected by the infrared receiver 42 into analog image data including the user's body tissue structure information (ie, contains the user's body part).
  • Step S22 processing the image data including the local body tissue structure information of the user into the inspection image of the user.
  • the image capturing module 101 uses the digital image processing software to record image data of the user's body tissue structure information in the form of a digital file, and then generates a user's inspection image according to the image data, and the image is available for use. Digital image of the body part of the body displayed.
  • the principle of infrared body partal organ detection is: Infrared light illuminates the local organs of the human body. Since the local body tissues of the human body exhibit different absorption characteristics through the infrared spectrum passing through them, the infrared light signal and the normal transmission through the lesions are normal.
  • the intensity of the infrared signal of the local organ tissue of the body will be different.
  • By collecting the gray scale, tissue structure, and external dimensions of the infrared image, especially the optical properties of the body part and body tissues it is possible to detect the lesion of the local part of the body. Location and size.
  • Step S23 performing an error-free noise removal filtering process and performing grayscale layering processing on the inspection image.
  • the image processing module 102 performs a distortion-free noise removal by using the Gaussian filter function.
  • the acoustic filtering process removes impurities of the examined image, thereby improving the accuracy of detecting and screening the local organ diseases.
  • the image processing module 102 performs grayscale layering on the uncorrected processed image to obtain a grayscale layered inspection image to enhance the layered display effect of the inspection image.
  • the grayscale layering process is also referred to as density layering processing, which comprises dividing the inspection image into different regions according to grayscale and performing color assignment processing on each region, so that the grayscale image of the body part organ is achieved.
  • density layering processing which comprises dividing the inspection image into different regions according to grayscale and performing color assignment processing on each region, so that the grayscale image of the body part organ is achieved.
  • the effect of layered display the inspection image after the grayscale layering process can more clearly display the texture
  • Step S24 obtaining a normal image of the body part of the user from the image database of the medical cloud platform, and comparing the texture distribution difference between the processed inspection image and the normal image of the body part to extract the organ from the inspection image.
  • the texture feature area specifically, the image analysis module 103 acquires the body part normal image of the user from the image database 20.
  • the image database 20 stores body normal images of different body users who have performed body health examinations and general surveys in the past.
  • the body local normal images are collected by the user's body parts and organs. Local organ image.
  • the image analysis module 103 compares the difference in texture distribution between the test image and the normal image of the body part to extract an organ texture feature region from the test image.
  • the difference in texture distribution includes differences in the structure of the body parts of the body, size differences, and contour differences.
  • the present invention compares the normal breast image as a normal image of the body with the currently scanned body part organ image, and is most effective in detecting abnormalities or abnormalities in the breast tissue, but for infrared images due to parts or individuals There is a big difference, and it is most suitable as a reference image of a past body part organ image that has been diagnosed as abnormal.
  • Step S25 marking the organ texture feature area in the inspection image, and transmitting the inspection image marked with the organ texture feature area to the doctor diagnosis terminal through the communication unit for the doctor to diagnose and screen the body part organ reference.
  • the image output module 104 marks the organ texture feature area in the inspection image, for example, the image texture feature area is marked with an ellipse in the inspection image, thereby assisting the doctor to improve the detection and screening of the body part disease. Check the efficiency and accuracy.
  • the image output module 104 sends the inspection image marked with the organ texture feature area to the doctor diagnosis terminal 5 through the communication unit 13, so as to provide a reference for the doctor to diagnose and screen the body part disease.
  • the image data analysis system and method based on the medical cloud platform provided by the invention collects the inspection image of the user through the image collection terminal installed in each community medical workstation, and is convenient for the user to perform physical examination of the body part organ and the body part organ sieve. Check, save limited hospital resources.
  • the invention can perform noise removal and grayscale layering processing on the inspection image, extract the organ texture feature region from the processed inspection image, and mark the organ texture feature region in the inspection image, and send it to the doctor diagnosis terminal to It provides a reference for doctors to diagnose and screen diseases of body parts and organs, thus assisting doctors to improve the efficiency and accuracy of detection and screening of body parts and diseases, and improve the social efficiency of body partal organ screening.
  • the image data analysis system and method based on the medical cloud platform of the present invention collects the inspection image of the user through the image collection terminal installed in each community medical workstation, so that the user can perform the local body organ. Health checkups and body partal organ screening save valuable hospital resources.
  • the organ texture feature region is extracted from the processed inspection image and the organ texture feature region is marked in the inspection image and sent to the doctor's medical treatment terminal for the doctor.
  • Provide reference for the diagnosis and screening of local organ diseases so as to help doctors improve the efficiency and accuracy of detection and screening of body parts and diseases, and improve the social efficiency of body partal organ screening.

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  • Engineering & Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Theoretical Computer Science (AREA)
  • Computer Vision & Pattern Recognition (AREA)
  • Medical Informatics (AREA)
  • General Health & Medical Sciences (AREA)
  • Nuclear Medicine, Radiotherapy & Molecular Imaging (AREA)
  • Radiology & Medical Imaging (AREA)
  • Quality & Reliability (AREA)
  • Health & Medical Sciences (AREA)
  • Image Processing (AREA)
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Abstract

L'invention concerne un système d'analyse de mégadonnées d'image basé sur une plateforme cloud médicale et un procédé, qui est appliqué à un serveur cloud. Le serveur cloud est connecté au moyen d'un réseau de communication à un terminal de collecte d'image, à une plateforme cloud médicale et à un terminal de diagnostic et de traitement de médecin. Le terminal de collecte d'image comprend une unité d'entrée, un générateur infrarouge, un récepteur infrarouge, un convertisseur analogique-numérique et un port de communication. Le système d'analyse de mégadonnées d'image comporte un module d'obtention d'informations d'utilisateur, un module de collecte d'image, un module de traitement d'image, un module d'analyse d'image et un module de sortie d'image d'organe local du corps. Une image d'examen d'un utilisateur est collectée par l'intermédiaire du terminal de collecte d'image, de sorte que l'utilisateur puisse effectuer commodément un dépistage médical sur un organe local du corps et que des ressources hospitalières soient économisées. De plus, grâce à une élimination de bruit et à un traitement hiérarchique d'échelle de gris sur l'image d'examen, des caractéristiques de texture d'organe local du corps sont extraites de l'image d'examen pour fournir une référence à un médecin afin qu'effectue un diagnostic et un dépistage de maladies d'un organe local du corps, ce qui permet au médecin d'améliorer l'efficacité et la précision du dépistage des maladies d'un organe local du corps.
PCT/CN2017/110476 2017-09-11 2017-11-10 Système d'analyse de mégadonnées d'image basé sur une plateforme cloud médicale, et procédé WO2019047365A1 (fr)

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CN201710813651.6A CN107506605A (zh) 2017-09-11 2017-09-11 基于医疗云平台的影像大数据分析系统及方法
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CN112768015A (zh) * 2019-11-01 2021-05-07 深圳市贵宾科技开发有限公司 一种基于物联网的健康大数据分析系统及其应用方法

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CN109935306A (zh) * 2019-03-08 2019-06-25 菅吉华 一种医学影像管理系统
CN111724893B (zh) * 2019-03-20 2024-04-09 宏碁股份有限公司 医疗影像辨识装置及医疗影像辨识方法
CN110767564A (zh) * 2019-10-28 2020-02-07 苏师大半导体材料与设备研究院(邳州)有限公司 一种晶圆检测方法
CN112951435A (zh) * 2021-03-06 2021-06-11 经纬泰和健康产业投资控股（北京）有限公司 基于人体光波共振热断层成像全息的健康风险筛查设备

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