WO2018176718A1 - 乳腺筛查影像智能识别***及方法 - Google Patents

乳腺筛查影像智能识别***及方法 Download PDF

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Publication number
WO2018176718A1
WO2018176718A1 PCT/CN2017/096132 CN2017096132W WO2018176718A1 WO 2018176718 A1 WO2018176718 A1 WO 2018176718A1 CN 2017096132 W CN2017096132 W CN 2017096132W WO 2018176718 A1 WO2018176718 A1 WO 2018176718A1
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Prior art keywords
image
image recognition
breast
recognition result
instruction
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PCT/CN2017/096132
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English (en)
French (fr)
Inventor
王德峰
郑斌
钱唯
石林
韩鸿宾
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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 WO2018176718A1 publication Critical patent/WO2018176718A1/zh

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    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/0002—Remote monitoring of patients using telemetry, e.g. transmission of vital signals via a communication network
    • A61B5/0004—Remote monitoring of patients using telemetry, e.g. transmission of vital signals via a communication network characterised by the type of physiological signal transmitted
    • A61B5/0013—Medical image data
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/0033—Features or image-related aspects of imaging apparatus classified in A61B5/00, e.g. for MRI, optical tomography or impedance tomography apparatus; arrangements of imaging apparatus in a room
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/0059—Measuring for diagnostic purposes; Identification of persons using light, e.g. diagnosis by transillumination, diascopy, fluorescence
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/74—Details of notification to user or communication with user or patient ; user input means
    • A61B5/742—Details of notification to user or communication with user or patient ; user input means using visual displays
    • A61B5/743—Displaying an image simultaneously with additional graphical information, e.g. symbols, charts, function plots

Definitions

  • the present invention relates to the field of medical image processing and recognition technology, and in particular, to a breast screening image intelligent identification system and method.
  • Breast disease is one of the most common diseases in women. Especially with the accelerated pace of modern urban life, women's life pressure and work pressure are increasing. The incidence of breast diseases is increasing year by year. Serious breast diseases may be serious. Lead to breast cancer. According to incomplete survey statistics, the incidence and mortality of breast diseases are also on the rise. In fact, most of the patients who died of breast cancer were killed because they did not find the best treatment opportunity. Therefore, it is necessary for women to have a breast screening, early detection of breast diseases, and early diagnosis for women's health.
  • the main object of the present invention is to provide a breast screening image intelligent recognition system and method, which can obtain the breast screening image recognition result by simply inputting a simple image recognition instruction, and simplify the operation of the breast screening image recognition. Improve the efficiency and accuracy of image recognition.
  • the present invention provides an intelligent screening system for breast screening images, which is applied to medical treatment.
  • the medical terminal device is connected to the breast image capturing terminal and the medical information platform through a communication network
  • the breast screening image intelligent recognition system comprises: an image acquiring module, configured to acquire the object to be detected from the breast image collecting terminal
  • the mammography image signal processes the mammary gland image signal of the subject to be detected as a mammography screening image, and receives the input personal information and image recognition instruction of the subject to be inspected from the input unit of the medical terminal device;
  • the image recognition module is configured to identify the image according to the image
  • the instruction matches the text corresponding to the image recognition instruction in the instruction recognition library of the medical information platform as the image recognition result;
  • the report generation module is configured to generate an image recognition report for displaying the image recognition result according to the matched image recognition result, and
  • the personal information of the inspector is added to the image recognition report;
  • the image matching module is configured to match the breast image data with the similarity of the breast screening image in
  • the breast image collection terminal comprises 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 inspect the infrared light to the person to be detected
  • the infrared receiver is configured to collect infrared light signals transmitted through the breast of the subject to be processed into an analog electrical signal containing breast tissue structure information of the subject to be detected;
  • the analog-to-digital converter is configured to include the to-be-detected The analog electrical signal modulus of the breast tissue structure information is converted into a breast image signal in the form of a digital signal;
  • the communication port is configured to transmit a breast image signal of the subject to be detected to the medical terminal device.
  • the image recognition instruction is a first identification mark, a second identification mark or a third identification mark
  • the image recognition result is a normal image recognition result, a reference image recognition result or an abnormal image recognition result.
  • the image recognition module determines that the image recognition result of the breast screening image is normal, and matches the text corresponding to the normal health of the breast in the instruction recognition library as a normal Image recognition result
  • the image recognition instruction is the second identification mark ⁇
  • the image recognition module matches the corresponding text in the instruction recognition library as a reference image recognition result according to the second identification mark
  • the image recognition instruction is The third identification mark ⁇
  • the image recognition module determines that the image recognition result is an abnormal image recognition result, and matches the corresponding character in the instruction recognition library as an abnormal image recognition result according to the third identification mark.
  • the breast screening image intelligent recognition system further comprises a result indication module, wherein the result indication module is used for normal image recognition result in the image recognition report, abnormal image recognition result or reference The image recognition result is marked, and the normal image recognition result, the abnormal image recognition result or the reference image recognition result in the image recognition report is displayed in the display unit of the medical terminal device in a preset display manner.
  • the image recognition module is further configured to receive the image recognition result input by the doctor from the input unit. Adding to the image recognition report, and adding the input image recognition result to the instruction recognition library.
  • the present invention also provides a method for intelligently identifying a breast screening image, which is applied to a medical terminal device, and the medical terminal device is connected to a breast image capturing terminal and a medical information platform through a communication network, the method comprising the steps of: from the breast image
  • the collecting terminal acquires the mammography image signal of the subject to be detected; processes the mammary gland image signal of the subject to be detected into a mammary gland screening image; receives the input personal information of the subject to be inspected and the image recognition instruction from the input unit of the medical terminal device;
  • the recognition instruction matches the text corresponding to the image recognition instruction in the instruction recognition library of the medical information platform as the image recognition result; and generates an image recognition report for displaying the image recognition result according to the matched image recognition result, and the image to be inspected is
  • the personal information is added to the image recognition report; the breast image data with the similarity of the breast screening image in the preset range is matched in the breast image database of the medical information platform, and the matched breast image data
  • the step of acquiring the mammography image signal of the to-be-detected person from the mammography image collection terminal comprises: generating infrared light by using an infrared generator of the mammography image acquisition terminal and inspecting the infrared light to the mammary gland of the subject to be detected
  • the infrared receiver through the breast image collection terminal collects the infrared light signal passing through the breast of the subject to be processed into an analog electrical signal containing the breast tissue structure information of the subject to be detected; the analog to digital converter using the breast image acquisition terminal Converting an analog electrical signal modulus containing the breast tissue structure information of the subject to be detected into a breast image signal in the form of a digital signal; transmitting a breast image signal of the subject to be detected to the medical through the communication port of the breast image collecting terminal Terminal Equipment.
  • the image recognition instruction is a first identification mark, a second identification mark or a third identification mark
  • the image recognition result is a normal image recognition result, a reference image recognition result or an abnormal image recognition result.
  • the image recognition instruction is the first identification mark ⁇
  • determining that the image recognition result of the breast screening image is normal, and matching the text corresponding to the normal health of the breast in the instruction recognition library
  • the image recognition result is a normal image recognition result
  • the image recognition instruction is the second identification mark
  • the image recognition result is matched with the corresponding text in the instruction recognition library as a reference according to the second identification mark
  • the identification mark ⁇ determines that the image recognition result is an abnormal image recognition result, and matches the corresponding character in the instruction recognition library as an abnormal image recognition result according to the third identification mark.
  • the breast screening image intelligent recognition method further comprises the following steps: identifying a normal image recognition result, an abnormal image recognition result or a reference image recognition result in the image recognition report, and displaying the preset image
  • the method displays a normal image recognition result, an abnormal image recognition result, or a reference image recognition result in the image recognition report in the display unit of the medical terminal device.
  • the method for intelligently identifying the breast screening image further comprises the steps of: receiving a doctor from the input unit when the image recognition result corresponding to the image recognition instruction is not matched in the instruction recognition library; The input image recognition result is added to the image recognition report, and the input image recognition result is added to the instruction recognition library.
  • the breast screening image intelligent recognition system and method of the present invention can identify a preset instruction according to a doctor's input image recognition instruction during a process of performing breast screening image recognition by a doctor.
  • the image matching result corresponding to the image recognition instruction is matched in the library, and the breast image data with the similarity of the breast screening image in the preset range is matched in the preset breast image database, and the image is generated according to the image recognition result and the breast image data. Identify the report.
  • the doctor only needs to input a simple image recognition command to obtain the recognition result of the breast screening image, without the doctor inputting the cumbersome examination conclusion, the operation of the breast image recognition is simplified, and the efficiency and accuracy of the image recognition of the breast are improved. , assisting doctors to improve the efficiency and accuracy of breast disease detection and screening, and improve the social efficiency of breast screening.
  • FIG. 1 is a schematic diagram of an application environment of a preferred embodiment of the breast screening image intelligent identification system of the present invention
  • FIG. 2 is a flow chart of a preferred embodiment of the method for intelligently identifying breast screening images of the present invention.
  • FIG. 1 is a schematic diagram of an application environment of a preferred embodiment of the breast screening image intelligent recognition system of the present invention.
  • the breast screening image intelligent recognition system 10 is installed and operated in the medical terminal device 1.
  • the medical terminal device 1 establishes a communication connection with the medical information platform 2 and the mammography image collecting terminal 4 via the communication network 3.
  • the medical terminal device 1 is provided with a computing device having a data processing and communication function, such as a doctor workstation computer or a server of a breast medical center or a large hospital.
  • the medical information platform 2 may be a server in a medical information system platform, and the medical information platform 2 includes an instruction recognition library 21 and a breast image database 22.
  • the preset instruction recognition library 21 pre-collects medical terms, radiology terms, and common image recognition result templates commonly used for breast health screening. Under normal circumstances, the template corresponds to normal. Image recognition results.
  • the breast image database 22 stores various commonly used normal or abnormal breast image data for reference. After receiving the breast screening image, the breast imaging image and the breast image data in the breast image database can be similar. Degree matching.
  • 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 breast image collection terminal 4 is disposed in a medical examination institution such as a community medical workstation, and establishes a network communication connection with the medical terminal device 1.
  • the breast image collecting 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 generates infrared light and sees the infrared light on the mammary gland of the subject to be detected; the infrared receiver 42 collects the infrared light signal passing through the breast of the subject to be detected and processes the analog electric energy of the breast tissue structure information.
  • the infrared light generated by the infrared generator 41 is fluorinated to the mammary gland of the subject to be detected, and the infrared light signal received by the infrared receiver 42 carries the infrared transmitted light of the breast tissue structure information.
  • the analog-to-digital converter 43 performs analog-to-digital conversion of the analog electrical signal containing the information of the breast tissue structure of the object to be detected collected by the infrared receiver 42 into a breast image signal in the form of a digital signal; the communication port 44 is used to information about the person to be detected. And the mammary gland containing the person to be tested The digital signal of the image information is transmitted to the cloud server 1 via 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, CDMA.
  • the medical terminal device 1 includes, but is not limited to, a breast screening image intelligent recognition system 10, an input unit 11, a storage unit 12, a processing unit 13, a communication unit 14, and a display unit 15.
  • the input unit 11, the storage unit 12, the processing unit 13, the communication unit 14, and the display unit 15 are all connected to the processing unit 13 via a data bus, and can perform information interaction with the breast screening image intelligent recognition system 10 through the processing unit 13.
  • the input unit 11 can be a hardware device such as a keyboard, a touch screen or a mouse.
  • the storage unit 12 is a read only memory unit ROM, an electrically erasable memory unit EEPROM or a flash memory unit FLASH.
  • the processing unit 13 is 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 14 can be a wireless communication interface with remote wireless communication functions, such as a communication interface supporting GSM, GPRS, and CDMA.
  • the display unit 15 is a display for displaying a breast examination report of the person to be examined.
  • the breast screening image intelligent recognition system 10 includes, but is not limited to, an image acquisition module 101, an image recognition module 102, a report generation module 103, an image matching module 104, and a result indication module 105.
  • 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 13 of the medical terminal device 1 and that can perform a fixed function, which are stored in the storage unit 12 of the medical terminal device 1. .
  • the image acquisition module 101 is configured to acquire a mammography image signal of the subject to be detected from the mammography image acquisition terminal 4.
  • the infrared generator 41 generates infrared light and sees the infrared light onto the mammary gland of the subject to be detected; the infrared receiver 42 collects an infrared light signal that passes through the breast of the subject to be detected and processes it into a mammary gland.
  • the analog-to-digital converter 43 converts the analog electrical signal collected by the infrared receiver 42 and contains the information of the breast tissue structure to be detected into a mammography signal in the form of a digital signal;
  • the communication port 44 transmits the mammography image signal of the subject to be detected to the image acquisition module 101.
  • the image acquisition module 101 is further configured to process the breast image signal of the subject to be detected into a breast screening image. Specifically, the image acquisition module 101 uses the digital image processing software to image the breast image of the object to be detected. The image data is recorded in the form of a digital file, and then the breast screening image of the subject to be detected is generated based on the image data.
  • the principle of infrared breast detection is: Infrared light illuminates the human breast region, and since the human breast tissue exhibits different absorption characteristics through the infrared spectrum, the infrared light signal and the normal transmission through the lesion portion are normal. The intensity of the infrared signal of the breast tissue will be different.
  • the location and size of the lesion in the breast can be detected by the gray scale, tissue structure, and external dimensions of the infrared image collected, especially the optical properties of the breast tissue.
  • the image acquisition module 101 is further configured to receive the input personal information of the subject to be inspected and the image recognition instruction from the input unit 11.
  • the doctor inputs the personal information of the subject to be examined from the input unit 11, including information such as name, age, gender, medical history, and the like.
  • the doctor also needs to input an image recognition command for checking the health of the breast from the input unit 11.
  • the image recognition module 102 is configured to match the text corresponding to the image recognition instruction in the instruction recognition library 21 of the medical information platform 2 as the image recognition result according to the image recognition instruction.
  • the image recognition instruction may be a first identification mark, a second identification mark or a third identification mark;
  • the image recognition result may be a normal image recognition result, a reference image recognition result, or an abnormal image. Identify the results.
  • the image recognition instruction includes a preset first identification mark, and the first identification mark is used as an indicator for determining whether the image recognition result is normal, that is, when the first identification mark is included in the image recognition instruction,
  • the image recognition module 102 determines that the image recognition result of the breast screening image is normal, and the content of the first identification mark is generally selected as a word different from related medical terms and radiological terms. For example, when the image recognition command includes "click + breast", it indicates that the image recognition result of the breast screening image is normal. At this time, the text corresponding to the normal breast health can be matched in the instruction recognition library 21 as a normal image recognition result. For example, matching "no abnormalities in the mammary gland" is used as a normal image recognition result.
  • the image recognition instruction includes a preset second identification mark, and the second identification mark is used as an indication mark for determining whether the image recognition result is a reference image recognition result, that is, when the second identification mark is included in the image recognition instruction.
  • the image recognition module 102 needs to match the image recognition result corresponding to the breast screening image, and the image recognition module 102 matches the image corresponding to the breast screening image in the instruction recognition library 21 as the reference image recognition result according to the second identification mark.
  • the content of the second identification mark may be set as a "reference” or the like which can clearly determine the image recognition result whose indication is the reference image recognition result.
  • the image recognition module 102 may determine that the image recognition result is not a normal image recognition result, and match the corresponding text in the instruction recognition library according to the third identification mark. If the matching text corresponding to the third identification mark has nothing to do with the image recognition result of the breast screening image, it indicates that the received image recognition instruction is invalid; on the contrary, it indicates that the image recognition result corresponding to the image recognition instruction is abnormal image recognition. result. For example, if the recognized image recognition command is "a number of soft tissue density lesions on both sides of the breast, and the morphology is consistent with breast cancer", the corresponding text is matched in the instruction recognition library, and the text is used as an abnormal image recognition result.
  • the image recognition module 102 if the image recognition module 102 does not match the image recognition result corresponding to the image recognition instruction in the instruction recognition library 21, it indicates that the corresponding character is not stored in the instruction recognition library 21. At this time, the doctor can input the corresponding image recognition result into the image recognition report through the input unit 11, and the image recognition module 102 adds the input image recognition result to the instruction recognition library 21, so as to receive the same or similar next time. In the case of the image recognition command, the corresponding image recognition result is matched from the command recognition library 21.
  • the report generation module 103 is configured to generate an image recognition report for displaying the image recognition result according to the matched image recognition result, and add the personal information of the to-be-inspected to the image recognition report.
  • the image recognition result is normal, the health status of the breast to be detected is normal; when the image recognition result is abnormal, the doctor receives the indication instruction of the abnormal part and marks the abnormal part of the breast screening image to Provide a reference for doctors to further diagnose and screen breast diseases.
  • the report generation module 103 can embed the name, age, gender, medical history and the like of the object to be inspected into the front part of the image recognition report in a modular form, and can automatically be at the end of the image recognition report.
  • a timestamp is generated; at the same time, the doctor can sign his or her name in the image recognition report.
  • the report generation module 103 After the report generation module 103 generates the image recognition report, if the image recognition result in the image recognition report is found to be incorrect, the erroneous content may be modified or deleted.
  • the image matching module 104 is configured to match the breast image data with the similarity of the breast screening image in the preset breast image database 22, and add the matched breast image data to the corresponding image data.
  • the image recognition report When the similarity is within the preset range, the similar image data in the breast image database 22 is acquired as the breast image data corresponding to the breast screening image, and the preset range may be customized according to the breast related portion, for example, set to be greater than 80%.
  • the image matching module 104 is matched to the mammary screen After checking the image data of the breast corresponding to the image, the matched breast image data is added to the corresponding image recognition report.
  • the image recognition report includes not only the image recognition results of the breast screening images, but also the breast image data of the breast screening images for reference by the doctor and the examinee.
  • the result indication module 105 is configured to identify a normal image recognition result, an abnormal image recognition result or a reference image recognition result in the image recognition report, and display the image recognition report on the display unit 15 in a preset display manner.
  • Normal image recognition results, abnormal image recognition results, or reference image recognition results are different identification on the normal image recognition result and the abnormal image recognition result according to whether the image recognition result is normal or abnormal, and can identify the reference result as being distinguishable from the normal or abnormal image recognition result.
  • Other identifiers such as marking different image recognition results as different fonts or different colors, so that when displayed, the display is displayed in a preset manner, for example, the text content of the abnormal image recognition result is displayed in bold form. Or highlight it.
  • the text content corresponding to the recognition template may be identified as blue after matching the recognition template indicating that the image recognition result is normal.
  • the text content may be identified as a red font after matching the text corresponding to the abnormal image recognition result, and displayed The text content of the red font is displayed in bold or highlighted to remind the examinee to pay attention.
  • the present invention also provides a method for intelligently identifying a breast screening image, which is applied to a medical terminal device.
  • Fig. 2 is a flow chart showing a preferred embodiment of the method for intelligently identifying the breast screening image of the present invention.
  • the embodiment of the present invention is combined with FIG. 1, and the method for intelligently identifying the breast screening image includes the following steps:
  • Step S21 the image acquisition module 101 acquires the mammography image signal of the to-be-detected person from the mammography image acquisition terminal 4, and processes the mammary gland image signal of the object to be detected into a mammary gland screening image;
  • the infrared generator 41 generates infrared light and fluoresces the infrared light onto the mammary gland of the subject to be detected;
  • the infrared receiver 42 collects an infrared light signal that passes through the mammary gland of the subject to be detected and processes the analog electrical signal as information of the mammary gland structure;
  • the analog to digital converter 43 A simulation of the tissue structure of the breast containing the subject to be detected collected by the infrared receiver 42
  • the electrical signal analog-to-digital conversion process is a breast image signal in the form of a digital signal;
  • the communication port 44 transmits the breast image signal of the subject to be detected to the image acquisition module 101.
  • the image acquisition module 101 records the image data of the breast image signal of the object to be
  • Step S22 the image acquisition module 101 receives the input personal information of the subject to be inspected and the image recognition instruction from the input unit 11.
  • the doctor inputs the breast information from the input unit 11 to screen the personal information of the examinee, including information such as name, age, gender, medical history, and the like.
  • the doctor also needs to input an image recognition command for checking the health of the breast from the input unit 11.
  • Step S23 the image recognition module 102 matches the text corresponding to the image recognition instruction in the command recognition library 21 as the image recognition result according to the image recognition instruction.
  • the image recognition instruction may be a first identification mark, a second identification mark or a third identification mark;
  • the image recognition result may be a normal image recognition result, a reference image recognition result, or an abnormal image. Identify the results.
  • the image recognition instruction includes a preset first identification mark, and the first identification mark is used as an indicator for determining whether the image recognition result is normal, that is, when the first identification mark is included in the image recognition instruction,
  • the image recognition module 102 determines that the image recognition result of the breast screening image is normal, and the content of the first identification mark is generally selected as a word different from related medical terms and radiological terms. For example, when the image recognition command includes "click + mammary gland", it indicates that the image recognition result of the breast screening image is normal, and therefore, the text corresponding to the normal health of the breast can be matched in the instruction recognition library 21, for example, matching" No abnormalities in the mammary gland” as a result of normal image recognition.
  • the image recognition instruction includes a preset second identification mark, and the second identification mark is used as an indication mark for determining whether the image recognition result is a reference image recognition result, that is, when the second identification mark is included in the image recognition instruction.
  • the image recognition module 102 needs to match the image recognition result corresponding to the breast screening image, and the image recognition module 102 matches the image corresponding to the breast screening image in the instruction recognition library 21 as the reference image recognition result according to the second identification mark.
  • the content of the second identification mark may be set as a "reference” or the like which can clearly determine the image recognition result whose indication is the reference image recognition result.
  • the image recognition module 102 may determine that the image recognition result is not a normal image recognition result, and match the corresponding text in the instruction recognition library 21 according to the third identification mark. At this time, if the matching text corresponding to the third identification mark has nothing to do with the image recognition result of the breast screening image, it indicates that the received image recognition instruction is invalid; on the contrary, it indicates that the image recognition result corresponding to the image recognition instruction is abnormal. Image recognition results.
  • the recognized image recognition command is "a plurality of soft tissue density lesions on both sides of the breast, and the morphology is consistent with breast cancer"
  • the corresponding recognition text is matched in the instruction recognition library 21, and the character is used as an abnormal image recognition result.
  • the image recognition module 102 if the image recognition module 102 does not match the image recognition result corresponding to the image recognition instruction in the instruction recognition library 21, it indicates that the corresponding file is not stored in the instruction recognition library 21.
  • the doctor can input the corresponding image recognition result into the image recognition report through the input unit 11, and the image recognition module 102 adds the input image recognition result to the instruction recognition library 21, so as to receive the same or similar image recognition next time.
  • the corresponding image recognition result is matched from the instruction recognition library 21.
  • Step S24 the report generation module 103 generates an image recognition report for displaying the image recognition result according to the matched image recognition result, and adds the personal information of the object to be inspected to the image recognition report.
  • the image recognition result is normal, the health status of the breast to be detected is normal; when the image recognition result is abnormal, the doctor receives the indication instruction of the abnormal part and marks the abnormal part of the breast screening image to Provide a reference for doctors to further diagnose and screen breast diseases.
  • the report generation module 103 can embed the name, age, gender, medical history, and the like of the object to be inspected into the front of the image recognition report in a modular form, and can automatically be at the end of the image recognition report.
  • the doctor can sign his or her name in the image recognition report.
  • the report generation module 103 After the report generation module 103 generates the image recognition report, if the image recognition result in the image recognition report is found to be incorrect, the doctor can modify or delete the wrong content.
  • Step S25 the image matching module 104 matches the breast image data with the similarity of the breast screening image in the preset breast image database, and adds the matched breast image data to the corresponding image recognition.
  • the breast image database 22 stores various commonly used normal or abnormal breast image data for reference.
  • the image matching module 104 can screen the image of the breast and The mammography data in the mammography database is similarly matched.
  • the similarity is within the preset range
  • the similar image data in the breast image database is acquired as the breast image data corresponding to the breast screening image, and the preset range may be customized according to the breast related part, for example, set to be greater than 80 ⁇ 3 ⁇ 4 .
  • the image matching module 104 matches the mammary gland corresponding to the breast screening image After the data is like, the breast image data is added to the corresponding image recognition report.
  • the image recognition report includes not only the image recognition result of the breast screening image, but also the breast image data of the breast screening image for reference by the doctor and the examinee.
  • Step S26 the result indication module 105 identifies the normal image recognition result, the abnormal image recognition result or the reference image recognition result in the image recognition report, and displays the image recognition on the display unit 15 in a preset display manner.
  • Normal image recognition results, abnormal image recognition results, or reference image recognition results in the report are different identification on the normal image recognition result and the abnormal image recognition result according to whether the image recognition result is normal or abnormal, and can identify the reference result as being distinguishable from the normal or abnormal image recognition result.
  • Other identifiers such as marking different image recognition results as different fonts or different colors, so that when displayed, the display unit 15 displays in a preset display manner, for example, the text content of the abnormal image recognition result is added. Displayed in bold form or highlighted.
  • the text content identifier corresponding to the recognition template may be matched after matching the recognition template representing that the image recognition result is normal. It is a blue font and is displayed normally; if the image recognition result in the image recognition report is an abnormal image recognition result, the text content may be identified as a red font after matching the text corresponding to the abnormal image recognition result, and In the display, the text content of the red font is displayed in bold or highlighted to remind the examinee to pay attention.
  • the normal image recognition result or the abnormal image recognition result in the image recognition report is differently identified, and the normal image recognition result or the abnormal image recognition result is displayed in a preset display manner, so that The image recognition report is more clear and easy for doctors and examiners to read.
  • the breast screening intelligent identification system and method of the present invention can match and image recognition in a preset instruction recognition library according to a doctor inputting a simple image recognition instruction during a process of performing breast screening image recognition by a doctor.
  • the image recognition result corresponding to the instruction matches the breast image data in the preset breast image database with the similarity of the breast screening image in the preset range, and generates the image recognition report according to the image recognition result and the breast image data, since the doctor only A simple image recognition command is required to obtain a breast screening image recognition result without requiring a doctor to input a cumbersome examination result, thereby simplifying the operation of the breast image recognition, improving the efficiency and accuracy of the breast image recognition, thereby assisting Doctor raises the milk The efficiency and accuracy of gland disease detection and screening, and improve the social efficiency of breast screening.
  • the breast screening image intelligent recognition system and method of the present invention can identify a preset instruction according to a doctor's input image recognition instruction during a process of performing breast screening image recognition by a doctor.
  • the image matching result corresponding to the image recognition instruction is matched in the library, and the breast image data with the similarity of the breast screening image in the preset range is matched in the preset breast image database, and the image is generated according to the image recognition result and the breast image data. Identify the report. Because the doctor only needs to input a simple image recognition command to obtain the recognition result of the breast screening image, without the doctor inputting the cumbersome examination conclusion, the operation of the breast image recognition is simplified, and the efficiency and accuracy of the image recognition of the breast are improved. , assisting doctors to improve the efficiency and accuracy of breast disease detection and screening, and improve the social efficiency of breast screening.

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Abstract

一种乳腺筛查影像智能识别***及方法，应用于医疗终端设备中，该方法包括步骤：从乳腺影像采集终端获取待检测者的乳腺影像信号，将乳腺影像信号处理为乳腺筛查影像（S21）；从输入单元接收待检查者的个人信息和影像识别指令（S22）；根据影像识别指令在指令识别库中匹配对应的文字作为影像识别结果（S23）；根据影像识别结果生成影像识别报告，并将个人信息加入到影像识别报告（S24）；在乳腺影像数据库中匹配与乳腺筛查影像相似度在预置范围内的乳腺影像数据，并将乳腺影像数据加入到对应的影像识别报告（S25）。医生只需输入简单的影像识别指令就能得到乳腺筛查影像的识别结果，简化乳腺筛查影像识别的操作，提高影像识别的效率和准确性。

Description

发明名称:学 L腺筛査影像智能识别***及方法
技术领域
[0001] 本发明涉及医学影像处理与识别技术领域， 尤其涉及一种乳腺筛査影像智能识 别***及方法。
背景技术
[0002] 乳腺疾病是女性的多发病症之一， 特别是随着现代都市生活节奏的加快， 女性 面对的生活压力、 工作压力加重， 乳腺疾病的发病率在逐年升高， 严重的乳腺 疾病可能导致乳腺癌。 据不完全调査统计显示， 乳腺疾病的发病率和死亡率也 都成上升趋势。 其实， 大部分乳腺癌待检查者的死亡原因就是因为没有及吋发 现， 错过了最佳治疗时机， 因此， 对广大女性进行乳腺普查、 乳腺疾病早发现 、 早期诊断对于女性健康是十分必要的。
[0003] 目前， 利用乳腺筛査影像进行辅助诊断已经成为被广泛采用的筛査和诊断早期 乳腺癌的重要方法。 医生在查看乳腺筛査影像时， 不能同步撰写报告， 而是要 切换到报告撰写的界面或程序中进行； 并且， 在撰写报告时， 需要将内容逐字 逐句地输入到计算机中。 对于一些较为常见的检査结果 （如某部位未见异常等 ) ， 仍然需要进行繁琐的输入， 这样就需要消耗相当的精力和吋间， 容易发生 误操作致使乳腺筛査效率下降的现象， 不适合大量乳腺样本的普查情况。 此外 , 由于乳腺影像数量很多， 医生直接对每幅乳腺影像进行识别并手动撰写报告 难以保证效率及准确性， 从而容易造成漏诊和误诊的情况发生。
技术问题
[0004] 本发明的主要目的在于提供一种乳腺筛査影像智能识别***及方法， 只需医生 输入简单的影像识别指令就能得到乳腺筛査影像的识别结果， 简化乳腺筛査影 像识别的操作， 提高影像识别的效率和准确性。
问题的解决方案
技术解决方案
[0005] 为实现上述目的， 本发明提供了一种乳腺筛査影像智能识别***， 应用于医疗 终端设备中， 该医疗终端设备通过通信网络连接至乳腺影像采集终端和医疗信 息平台， 所述乳腺筛查影像智能识别***包括： 影像获取模块， 用于从乳腺影 像釆集终端获取待检测者的乳腺影像信号， 将待检测者的乳腺影像信号处理为 乳腺筛査影像， 以及从医疗终端设备的输入单元接收输入的待检查者的个人信 息和影像识别指令； 影像识别模块， 用于根据影像识别指令在医疗信息平台的 指令识别库中匹配与影像识别指令对应的文字作为影像识别结果； 报告生成模 块， 用于根据匹配出的影像识别结果生成用于显示影像识别结果的影像识别报 告， 并将待检査者的个人信息加入到影像识别报告中； 影像匹配模块， 用于在 医疗信息平台的乳腺影像数据库中匹配与乳腺筛査影像相似度在预置范围内的 乳腺影像数据， 并将该匹配出的乳腺影像数据加入到对应的影像识别报告中。
[0006] 优选的， 所述乳腺影像釆集终端包括红外发生器、 红外接收器、 模数转换器以 及通信端口， 其中： 所述红外发生器用于产生红外光并将红外光透视到待检测 者的乳腺上； 所述红外接收器用于釆集透过待检测者的乳腺的红外光信号处理 为包含待检测者的乳腺组织结构信息的模拟电信号； 所述模数转换器用于将包 含待检测者的乳腺组织结构信息的模拟电信号模数转换为数字信号形式的乳腺 影像信号； 所述通信端口用于将待检测者的乳腺影像信号发送至所述医疗终端 设备。
[0007] 优选的， 所述影像识别指令为第一识别标志、 第二识别标志或第三识别标志， 所述影像识别结果为正常的影像识别结果、 参考的影像识别结果或异常的影像 识别结果， 其中： 当所述影像识别指令为第一识别标志吋， 所述影像识别模块 判断乳腺筛査影像的影像识别结果为正常， 并在指令识别库中匹配与乳腺健康 正常对应的文字作为正常的影像识别结果； 当所述影像识别指令为第二识别标 志吋， 所述影像识别模块根据第二识别标志在指令识别库中匹配对应的文字作 为参考的影像识别结果； 当所述影像识别指令为第三识别标志吋， 所述影像识 别模块判断影像识别结果是异常的影像识别结果， 并根据第三识别标志在指令 识别库中匹配对应的文字作为异常的影像识别结果。
[0008] 优选的， 所述乳腺筛査影像智能识别***还包括结果标示模块， 该结果标示模 块用于对影像识别报告中的正常的影像识别结果、 异常的影像识别结果或参考 影像识别结果进行标识， 以预置的显示方式在医疗终端设备的显示单元中显示 影像识别报告中的正常的影像识别结果、 异常的影像识别结果或参考影像识别 结果。
[0009] 优选的， 当所述指令识别库中未匹配出与所述影像识别指令对应的影像识别结 果时， 所述影像识别模块还用于从所述输入单元接收医生输入的影像识别结果 并添加至所述影像识别报告中， 并将输入的影像识别结果添加至所述指令识别 库中。
[0010] 本发明还提供一种乳腺筛查影像智能识别方法， 应用于医疗终端设备中， 该医 疗终端设备通过通信网络连接至乳腺影像采集终端和医疗信息平台， 该方法包 括步骤： 从乳腺影像采集终端获取待检测者的乳腺影像信号； 将待检測者的乳 腺影像信号处理为乳腺筛査影像； 从医疗终端设备的输入单元接收输入的待检 査者的个人信息和影像识别指令； 根据影像识别指令在医疗信息平台的指令识 别库中匹配与影像识别指令对应的文字作为影像识别结果； 根据匹配出的影像 识别结果生成用于显示影像识别结果的影像识别报告， 并将待检査者的个人信 息加入到影像识别报告中； 在医疗信息平台的乳腺影像数据库中匹配与乳腺筛 査影像相似度在预置范围内的乳腺影像数据， 并将该匹配出的乳腺影像数据加 入到对应的影像识别报告中。
[0011] 优选的， 所述从乳腺影像釆集终端获取待检测者的乳腺影像信号的步骤包括： 利用乳腺影像采集终端的红外发生器产生红外光并将红外光透视到待检测者的 乳腺上； 通过乳腺影像釆集终端的红外接收器釆集透过待检测者的乳腺的红外 光信号处理为包含待检测者的乳腺组织结构信息的模拟电信号； 利用乳腺影像 采集终端的模数转换器将包含待检测者的乳腺组织结构信息的模拟电信号模数 转换为数字信号形式的乳腺影像信号； 通过乳腺影像釆集终端的通信端口用于 将待检测者的乳腺影像信号发送至所述医疗终端设备。
[0012] 优选的， 所述影像识别指令为第一识别标志、 第二识别标志或第三识别标志， 所述影像识别结果为正常的影像识别结果、 参考的影像识别结果或异常的影像 识别结果， 其中： 当所述影像识别指令为第一识别标志吋， 判断乳腺筛査影像 的影像识别结果为正常， 并在指令识别库中匹配与乳腺健康正常对应的文字作 为正常的影像识别结果； 当所述影像识别指令为第二识别标志时， 根据第二识 别标志在指令识别库中匹配对应的文字作为参考的影像识别结果； 当所述影像 识别指令为第三识别标志吋， 判断影像识别结果是异常的影像识别结果， 并根 据第三识别标志在指令识别库中匹配对应的文字作为异常的影像识别结果。
[0013] 优选的， 所述乳腺筛査影像智能识别方法还包括如下步骤： 对影像识别报告中 的正常的影像识别结果、 异常的影像识别结果或参考影像识别结果进行标识， 以预置的显示方式在医疗终端设备的显示单元中显示影像识别报告中的正常的 影像识别结果、 异常的影像识别结果或参考影像识别结果。
[0014] 优选的， 所述乳腺筛査影像智能识别方法还包括如下步骤： 当所述指令识别库 中未匹配出与所述影像识别指令对应的影像识别结果时， 从所述输入单元接收 医生输入的影像识别结果并添加至影像识别报告中， 并将输入的影像识别结果 添加至所述指令识别库中。
发明的有益效果
有益效果
[0015] 相较于现有技术， 本发明所述乳腺筛査影像智能识别***及方法能够在医生在 进行乳腺筛査影像识别的过程中， 根据医生输入的影像识别指令在预置的指令 识别库中匹配与影像识别指令对应的影像识别结果， 在预置的乳腺影像数据库 中匹配与乳腺筛査影像相似度在预置范围内的乳腺影像数据， 以及根据影像识 别结果及乳腺影像数据生成影像识别报告。 由于医生只需输入简单的影像识别 指令就能得到乳腺筛査影像的识别结果， 而无需医生输入繁琐的检査结论， 从 而简化了乳腺影像识别的操作， 提高了乳腺影像识别的效率和准确性， 辅助医 生提高对乳腺疾病检测与筛査的效率及准确性， 提高乳腺筛査的社会效率。 对附图的简要说明
附图说明
[0016] 图 1是本发明乳腺筛査影像智能识别***优选实施例的应用环境示意图；
[0017] 图 2是本发明乳腺筛查影像智能识别方法优选实施例的流程图。
[0018] 本发明目的实现、 功能特点及优点将结合具体实施方式， 参照附图做进一步说 明。 实施该发明的最佳实施例
本发明的最佳实施方式
[0019] 为更进一步阐述本发明为达成上述目的所采取的技术手段及功效， 以下结合附 图及较佳实施例， 对本发明的具体实施方式、 结构、 特征及其功效进行详细说 明。 应当理解， 此处所描述的具体实施例仅仅用以解释本发明， 并不用于限定 本发明。
[0020] 参照图 1所示， 图 1是本发明乳腺筛査影像智能识别***优选实施例的应用环境 示意图。 在本实施例中， 所述乳腺筛査影像智能识别*** 10安装并运行于医疗 终端设备 1中。 所述医疗终端设备 1通过通信网络 3与医疗信息平台 2以及乳腺影 像采集终端 4建立通信连接。 所述医疗终端设备 1设置在乳腺体检中心或大型医 院的医生工作站计算机、 服务器等具有数据处理和通信功能的计算装置。 所述 医疗信息平台 2可以是一种医疗信息***平台中的一台服务器， 该医疗信息平台 2包括指令识别库 21以及乳腺影像数据库 22。 在本实施例中， 所述预置的指令识 别库 21中预先收集了乳腺健康筛査常用的医学术语、 放射学术语以及常见的影 像识别结果模版， 在通常情况下， 模版所对应的为正常的影像识别结果。 所述 乳腺影像数据库 22中存储了常用的各种正常或异常的乳腺影像数据可供参考， 在接收到乳腺筛査影像后， 可以对乳腺筛査影像和乳腺影像数据库中的乳腺影 像数据进行相似度匹配。 所述通信网络 3可以是一种包括局域网、 广域网的网际 网络， 或者是一种包括 GSM、 GPRS、 CDMA的无线传输网络。
[0021] 所述乳腺图像采集终端 4设置在社区医疗工作站等医疗检査机构内， 并与医疗 终端设备 1建立网络通信连接。 在本实施例中， 所述乳腺图像釆集终端 4包括红 外发生器 41、 红外接收器 42、 模数转换器 43以及通信端口 44。 所述红外发生器 4 1产生红外光并将红外光透视到待检测者的乳腺上； 红外接收器 42釆集透过待检 测者的乳腺的红外光信号并处理为乳腺组织结构信息的模拟电信号； 红外发生 器 41产生的红外光透视到待检测者乳腺上， 红外接收器 42接收的红外光信号携 带了乳腺组织结构信息的红外透射光。 模数转换器 43将红外接收器 42采集到的 包含待检测者乳腺组织结构信息的模拟电信号模数转换处理为数字信号形式的 乳腺影像信号； 所述通信端口 44用于将待检测者信息以及包含待检测者的乳腺 图像信息的数字信号通过通信网络 3发送至云服务器 1。 所述通信端口 44可以为 一种具有远程无线通讯功能的无线通讯接口， 例如支持 GSM、 GPRS^ CDMA的 通讯接口。
[0022] 在本实施例中， 所述医疗终端设备 1包括， 但不仅限于， 乳腺筛査影像智能识 别*** 10、 输入单元 11、 存储单元 12、 处理单元 13、 通信单元 14和显示单元 15 。 所述输入单元 11、 存储单元 12、 处理单元 13、 通信单元 14和显示单元 15均通 过数据总线连接至处理单元 13 , 并能通过处理单元 13与乳腺筛査影像智能识别 *** 10进行信息交互。 所述输入单元 11可以为键盘、 触摸屏或鼠标等硬件设备 。 所述存储单元 12为一种只读存储单元 ROM, 电可擦写存储单元 EEPROM或快 闪存储单元 FLASH等存储器。 所述处理单元 13为一种中央处理器 （CPU) 、 微 处理器、 微控制器 （MCU) 、 数据处理芯片、 或者具有数据处理功能的信息处 理单元。 所述通信单元 14可以为一种具有远程无线通讯功能的无线通讯接口， 例如支持 GSM、 GPRS、 CDMA的通讯接口。 所述显示单元 15为显示器， 用于显 示待检査者的乳腺检査报告。
[0023] 在本实施例中， 所述乳腺筛査影像智能识别*** 10包括， 但不局限于， 影像获 取模块 101、 影像识别模块 102、 报告生成模块 103、 影像匹配模块 104以及结果 标示模块105。 本发明所称的模块是指一种能够被所述医疗终端设备 1的处理单 元 13执行并且能够完成固定功能的一系列计算机程序指令段， 其存储在所述医 疗终端设备 1的存储单元 12中。
[0024] 所述影像获取模块 101用于从乳腺影像采集终端 4获取待检测者的乳腺影像信号 。 在本实施例中， 所述红外发生器 41产生红外光并将红外光透视到待检测者的 乳腺上； 所述红外接收器 42采集透过待检测者的乳腺的红外光信号并处理为乳 腺组织结构信息的模拟电信号； 所述模数转换器 43将红外接收器 42采集到的包 含待检测者乳腺组织结构信息的模拟电信号模数转换处理为数字信号形式的乳 腺影像信号； 所述通信端口 44将待检测者的乳腺影像信号发送至影像获取模块 1 01。
[0025] 所述影像获取模块 101还用于将待检测者的乳腺影像信号处理为乳腺筛査影像 。 具体地， 影像获取模块 101利用数字影像处理软件将待检测者的乳腺影像信号 以数字文件的形式记录影像数据， 然后根据该影像数据产生待检测者的乳腺筛 査影像。 在本实施例中， 红外乳腺检测的原理是： 红外光线照射人体乳腺部位 ， 由于人体乳腺组织对通过其中的红外光谱呈现出不同的吸收特性 , 所以透过 病变部位的红外光信号与透过正常乳腺组织的红外信号的强度会有所不同， 通 过釆集到的红外影像的灰度、 组织结构、 外形尺寸特别是乳腺组织的光学特性 , 就可以检测到乳腺部位发生病变的位置和尺寸。
[0026] 所述影像获取模块 101还用于从输入单元 11接收输入的待检査者的个人信息和 影像识别指令。 在本实施例中， 医生从输入单元 11输入乳腺筛査待检査者的个 人信息， 包括姓名、 年龄、 性别、 病史等信息。 在识别乳腺筛査影像时， 医生 还需从输入单元 11用于输入检査乳腺健康状况的影像识别指令。
[0027] 所述影像识别模块 102用于根据影像识别指令在医疗信息平台 2的指令识别库 21 中匹配与影像识别指令对应的文字作为影像识别结果。 在本实施例中， 所述影 像识别指令可以为第一识别标志、 第二识别标志或第三识别标志； 所述影像识 别结果可以为正常的影像识别结果、 参考的影像识别结果或异常的影像识别结 果。 具体地， 如所述影像识别指令中包括预置的第一识别标志， 该第一识别标 志作为判断影像识别结果是否为正常的指示标志， 即当影像识别指令中包括该 第一识别标志时， 影像识别模块 102判断乳腺筛査影像的影像识别结果为正常， 该第一识别标志的内容通常选择为异于相关的医学术语和放射学术语的词语。 例如， 当影像识别指令包括 "点击 +乳腺"， 则表明乳腺筛査影像的影像识别结果 为正常， 此时， 可在指令识别库 21中匹配与乳腺健康正常对应的文字作为正常 的影像识别结果， 例如匹配"乳腺未见异常"作为正常的影像识别结果。 如所述影 像识别指令中包括预置的第二识别标志， 该第二识别标志作为判断影像识别结 果是否为参考的影像识别结果的指示标志， 即当影像识别指令中包括该第二识 别标志时， 表示此吋需匹配与乳腺筛査影像对应的参考的影像识别结果， 影像 识别模块 102根据第二识别标志在指令识别库 21中匹配与乳腺筛查影像对应的文 字作为参考的影像识别结果。 第二识别标志的内容可设置为"参考"等可以明显确 定其指示的影像识别结果为参考的影像识别结果的词语。 例如， 当影像识别指 令为"参考"， 则在指令识别库中匹配与影像识别报告的结论对应的文字， 将该文 字作为参考的影像识别结果。 如所述影像识别指令第三识别标志， 则影像识别 模块 102可判断影像识别结果不是正常的影像识别结果， 并根据第三识别标志在 指令识别库中匹配与其对应的文字。 如匹配到的第三识别标志对应的文字与对 乳腺筛査影像的影像识别结果无关， 则表明接收到的影像识别指令无效； 相反 ， 则表明影像识别指令对应的影像识别结果为异常的影像识别结果。 例如， 识 别出的影像识别指令为"***两侧可见数个软组织密度灶， 形态与乳腺癌相符"， 则在指令识别库中匹配相应的文字， 将该文字作为异常的影像识别结果。
[0028] 在本实施例中， 所述影像识别模块 102如在指令识别库 21中未匹配出与影像识 别指令对应的影像识别结果， 则表明该指令识别库 21中未存储有相应的文字， 此时， 医生可通过输入单元 11输入相应的影像识别结果至影像识别报告中， 影 像识别模块 102则将输入的影像识别结果添加至指令识别库 21中 , 以备在下次接 收到相同或相似的影像识别指令时， 从指令识别库 21中匹配对应的影像识别结 果。
[0029] 所述报告生成模块 103用于根据匹配出的影像识别结果生成用于显示影像识别 结果的影像识别报告， 并将待检査者的个人信息加入到影像识别报告中。 当影 像识别结果为正常吋， 则显示待检测者乳腺健康状况为正常； 当影像识别结果 为异常时， 则接收医生输入异常部位的标示指令并在该乳腺筛査影像的异常部 位进行标示， 以供医生对乳腺疾病进一步进行诊断与筛査提供参考。 在生成影 像识别报告吋， 报告生成模块 103可以将待检査者的姓名、 年龄、 性别、 病史等 信息以模块化的形式嵌入到影像识别报告的前部， 并且可在影像识别报告的末 尾自动生成时间戳； 同时， 医生可以在影像识别报告中签署自己的姓名。 在报 告生成模块 103生成影像识别报告后， 如发现影像识别报告中的影像识别结果有 误， 则可对错误的内容进行修改或刪除操作。
[0030] 所述影像匹配模块 104用于在预置的乳腺影像数据库 22中匹配与乳腺筛査影像 相似度在预置范围内的乳腺影像数据， 并将该匹配出的乳腺影像数据加入到对 应的影像识别报告中。 当相似度在预设范围内时， 获取乳腺影像数据库 22中的 相似影像数据作为乳腺筛査影像对应的乳腺影像数据， 预设范围可以根据*** 相关部位自定义设置， 例如设置为大于 80%。 当影像匹配模块 104匹配到乳腺筛 査影像对应的乳腺影像数据后， 将匹配到的乳腺影像数据加入到对应的影像识 别报告中。 影像识别报告不仅包括乳腺筛査影像的影像识别结果， 还包括该乳 腺筛查影像的乳腺影像数据， 以供医生和待检查者参考。
[0031] 所述结果标示模块 105用于对影像识别报告中的正常的影像识别结果、 异常的 影像识别结果或参考影像识别结果进行标识， 以预置的显示方式在显示单元 15 显示影像识别报告中的正常的影像识别结果、 异常的影像识别结果或参考影像 识别结果。 具体地， 结果标示模块 105根据影像识别结果是正常还是异常对正常 的影像识别结果和异常的影像识别结果进行不同的标识， 同时可以将参考结果 标识为能够与正常或异常的影像识别结果区分的其他标识， 如将不同的影像识 别结果标记为不同的字体或不同的颜色， 以便在显示时， 以预置的显示方式进 行显示， 例如， 对异常的影像识别结果的文字内容以加粗形式显示或进行突出 显示。 在本实施例中， 如影像识别报告中的影像识别结果为正常的影像识别结 果， 则可以在匹配到代表影像识别结果为正常的识别模版后， 对该识别模版对 应的文字内容标识为蓝色字体， 并正常显示； 如影像识别报告中的影像识别结 果为异常的影像识别结果， 则可以在匹配到异常的影像识别结果对应的文字后 , 将该文字内容标识为红色字体， 并在显示时将该红色字体的文字内容以加粗 形式显示或进行突出显示， 以提醒待检査者注意。 在生成影像识别报告时， 对 影像识别报告中的正常的影像识别结果或异常的影像识别结果进行不同的标识 , 并以预置的显示方式显示正常的影像识别结果或异常的影像识别结果， 使得 影像识别报告显示更为清晰， 方便医生和待检测者阅读。
[0032] 本发明还提供了一种乳腺筛査影像智能识别方法， 应用于医疗终端设备中。 如 图 2所示， 图 2是本发明乳腺筛査影像智能识别方法优选实施例的流程图。 本实 施例一并结合图 1所示， 所述乳腺筛査影像智能识别方法包括步骤：
[0033] 步骤 S21， 影像获取模块 101从乳腺影像采集终端 4获取待检测者的乳腺影像信 号， 并将待检测者的乳腺影像信号处理为乳腺筛査影像； 在本实施例中， 红外 发生器 41产生红外光并将红外光透视到待检测者的乳腺上； 红外接收器 42采集 透过待检测者的乳腺的红外光信号并处理为乳腺组织结构信息的模拟电信号； 模数转换器 43将红外接收器 42采集到的包含待检测者乳腺组织结构信息的模拟 电信号模数转换处理为数字信号形式的乳腺影像信号； 通信端口 44将待检测者 的乳腺影像信号发送至影像获取模块 101。 影像获取模块 101利用数字影像处理 软件将待检测者的乳腺影像信号以数字文件的形式记录影像数据， 然后根据该 影像数据产生待检测者的乳腺筛査影像。
[0034] 步骤 S22, 影像获取模块 101从输入单元 11接收输入的待检査者的个人信息和影 像识别指令。 在本实施例中， 医生从输入单元 11输入乳腺筛査待检査者的个人 信息， 包括姓名、 年龄、 性别、 病史等信息。 在识别乳腺筛查影像时， 医生还 需从输入单元 11用于输入检查乳腺健康状况的影像识别指令。
[0035] 步骤 S23， 影像识别模块 102根据影像识别指令在指令识别库 21中匹配与影像识 别指令对应的文字作为影像识别结果。 在本实施例中， 所述影像识别指令可以 为第一识别标志、 第二识别标志或第三识别标志； 所述影像识别结果可以为正 常的影像识别结果、 参考的影像识别结果或异常的影像识别结果。 具体地， 如 所述影像识别指令中包括预置的第一识别标志， 该第一识别标志作为判断影像 识别结果是否为正常的指示标志， 即当影像识别指令中包括该第一识别标志时 , 影像识别模块 102判断乳腺筛査影像的影像识别结果为正常， 该第一识别标志 的内容通常选择为异于相关的医学术语和放射学术语的词语。 例如， 当影像识 另幅令包括"点击 +乳腺"， 则表明乳腺筛査影像的影像识别结果为正常， 此吋， 可在指令识别库 21中匹配与乳腺健康正常对应的文字， 例如匹配"乳腺未见异常" 作为正常的影像识别结果。 如所述影像识别指令中包括预置的第二识别标志， 该第二识别标志作为判断影像识别结果是否为参考的影像识别结果的指示标志 , 即当影像识别指令中包括该第二识别标志时， 表示此吋需匹配与乳腺筛査影 像对应的参考的影像识别结果， 影像识别模块 102根据第二识别标志在指令识别 库 21中匹配与乳腺筛査影像对应的文字作为参考的影像识别结果。 第二识别标 志的内容可设置为"参考"等可以明显确定其指示的影像识别结果为参考的影像识 别结果的词语。 例如， 当影像识别指令为"参考"， 则在指令识别库 21中匹配与影 像识别报告的结论对应的文字， 将该文字作为参考的影像识别结果。 如所述影 像识别指令第三识别标志， 则影像识别模块 102可判断影像识别结果不是正常的 影像识别结果， 并根据第三识别标志在指令识别库 21中匹配与其对应的文字。 此时， 如匹配到的第三识别标志对应的文字与对乳腺筛査影像的影像识别结果 无关， 则表明接收到的影像识别指令无效； 相反， 则表明影像识别指令对应的 影像识别结果为异常的影像识别结果。 例如， 识别出的影像识别指令为"***两 侧可见数个软组织密度灶， 形态与乳腺癌相符"， 则在指令识别库 21中匹配相应 的文字， 将该文字作为异常的影像识别结果。
[0036] 在本实施例中， 影像识别模块 102如在指令识别库 21中未匹配出与影像识别指 令对应的影像识别结果， 则表明该指令识别库 21中未存储有相应的文字， 此时 ， 医生可通过输入单元 11输入相应的影像识别结果至影像识别报告中， 影像识 别模块 102则将输入的影像识别结果添加至指令识别库 21中， 以备在下次接收到 相同或相似的影像识别指令时， 从指令识别库 21中匹配对应的影像识别结果。
[0037] 步骤 S24, 报告生成模块 103根据匹配出的影像识别结果生成用于显示影像识别 结果的影像识别报告， 并将待检査者的个人信息加入到影像识别报告中。 当影 像识别结果为正常吋， 则显示待检测者乳腺健康状况为正常； 当影像识别结果 为异常时， 则接收医生输入异常部位的标示指令并在该乳腺筛査影像的异常部 位进行标示， 以供医生对乳腺疾病进一步进行诊断与筛査提供参考。 在生成影 像识别报告时， 报告生成模块 103可以将待检査者的姓名、 年龄、 性别、 病史等 信息以模块化的形式嵌入到影像识别报告的前部 , 并且可在影像识别报告的末 尾自动生成吋间戳； 同吋， 医生可以在影像识别报告中签署自己的姓名。 报告 生成模块 103生成影像识别报告后， 如发现影像识别报告中的影像识别结果有误 , 医生则可对错误的内容进行修改或刪除操作。
[0038] 步骤 S25， 影像匹配模块 104在预置的乳腺影像数据库中匹配与乳腺筛査影像相 似度在预置范围内的乳腺影像数据， 并将匹配出的乳腺影像数据加入到对应的 影像识别报告中。 在本实施例中， 所述乳腺影像数据库 22中存储了常用的各种 正常或异常的乳腺影像数据可供参考， 在接收到乳腺筛査影像后， 影像匹配模 块 104可以对乳腺筛查影像和乳腺影像数据库中的乳腺影像数据进行相似度匹配 。 当相似度在预设范围内时， 获取乳腺影像数据库中的相似影像数据作为该乳 腺筛査影像对应的乳腺影像数据， 预设范围可以根据***相关部位自定义设置 , 例如设置为大于 80<¾。 影像匹配模块 104在匹配到乳腺筛査影像对应的乳腺影 像数据后， 根据该乳腺影像数据加入到对应的影像识别报告中。 所述影像识别 报告不仅包括乳腺筛查影像的影像识别结果， 还包括该乳腺筛査影像的乳腺影 像数据， 以供医生和待检查者参考。
[0039] 步骤 S26, 结果标示模块 105对影像识别报告中的正常的影像识别结果、 异常的 影像识别结果或参考影像识别结果进行标识， 以预置的显示方式在显示单元 15 显示所述影像识别报告中的正常的影像识别结果、 异常的影像识别结果或参考 影像识别结果。 具体地， 结果标示模块 105根据影像识别结果是正常还是异常对 正常的影像识别结果和异常的影像识别结果进行不同的标识， 同时可以将参考 结果标识为能够与正常或异常的影像识别结果区分的其他标识， 如将不同的影 像识别结果标记为不同的字体或不同的颜色， 以便在显示时， 以预置的显示方 式显示单元 15进行显示， 例如， 对异常的影像识别结果的文字内容以加粗形式 显示或进行突出显示。
[0040] 在本实施例中， 如影像识别报告中的影像识别结果为正常的影像识别结果， 则 可以在匹配到代表影像识别结果为正常的识别模版后， 对该识别模版对应的文 字内容标识为蓝色字体， 并正常显示； 如影像识别报告中的影像识别结果为异 常的影像识别结果， 则可以在匹配到异常的影像识别结果对应的文字后， 将该 文字内容标识为红色字体， 并在显示吋将该红色字体的文字内容以加粗形式显 示或进行突出显示， 以提醒待检査者注意。 在生成影像识别报告吋， 对影像识 别报告中的正常的影像识别结果或异常的影像识别结果进行不同的标识， 并以 预置的显示方式显示正常的影像识别结果或异常的影像识别结果， 使得影像识 别报告显示更为清晰， 方便医生和待检查者阅读。
[0041] 本发明所述乳腺筛査智能识别***及方法 , 能够在医生在进行乳腺筛査影像识 别的过程中， 根据医生输入简单的影像识别指令在预置的指令识别库中匹配与 影像识别指令对应的影像识别结果， 在预置的乳腺影像数据库中匹配与乳腺筛 査影像相似度在预置范围内的乳腺影像数据， 以及根据影像识别结果及乳腺影 像数据生成影像识别报告， 由于医生只需输入简单的影像识别指令就能得到乳 腺筛査影像的识别结果， 而无需医生输入繁琐的检査结论， 从而简化了乳腺影 像识别的操作， 提高了乳腺影像识别的效率和准确性， 从而辅助医生提高对乳 腺疾病检测与筛査的效率及准确性， 提高乳腺筛査的社会效率。
[0042] 以上仅为本发明的优选实施例， 并非因此限制本发明的专利范围， 凡是利用本 发明说明书及附图内容所作的等效结构或等效功能变换， 或直接或间接运用在 其他相关的技术领域， 均同理包括在本发明的专利保护范围内。
工业实用性
[0043] 相较于现有技术， 本发明所述乳腺筛査影像智能识别***及方法能够在医生在 进行乳腺筛査影像识别的过程中， 根据医生输入的影像识别指令在预置的指令 识别库中匹配与影像识别指令对应的影像识别结果， 在预置的乳腺影像数据库 中匹配与乳腺筛査影像相似度在预置范围内的乳腺影像数据， 以及根据影像识 别结果及乳腺影像数据生成影像识别报告。 由于医生只需输入简单的影像识别 指令就能得到乳腺筛査影像的识别结果， 而无需医生输入繁琐的检査结论， 从 而简化了乳腺影像识别的操作， 提高了乳腺影像识别的效率和准确性， 辅助医 生提高对乳腺疾病检测与筛査的效率及准确性， 提高乳腺筛査的社会效率。

Claims

[权利要求 1] 一种乳腺筛査影像智能识别***， 应用于医疗终端设备中， 该医疗终 端设备通过通信网络连接至乳腺影像采集终端和医疗信息平台， 其特 征在于， 所述乳腺筛査影像智能识别***包括： 影像获取模块， 用于 从乳腺影像采集终端获取待检测者的乳腺影像信号， 将待捡测者的乳 腺影像信号处理为乳腺筛査影像 , 以及从医疗终端设备的输入单元接 收输入的待检査者的个人信息和影像识别指令； 影像识别模块， 用于 根据影像识别指令在医疗信息平台的指令识别库中匹配与影像识别指 令对应的文字作为影像识别结果； 报告生成模块， 用于根据匹配出的 影像识别结果生成用于显示影像识别结果的影像识别报告， 并将待检 査者的个人信息加入到影像识别报告中； 影像匹配模块， 用于在医疗 信息平台的乳腺影像数据库中匹配与乳腺筛査影像相似度在预置范围 内的乳腺影像数据， 并将该匹配出的乳腺影像数据加入到对应的影像 识别报告中。
[权利要求 2] 如权利要求 1所述的乳腺筛査影像智能识别***， 其特征在于， 所述 乳腺影像采集终端包括红外发生器、 红外接收器、 模数转换器以及通 信端口， 其中： 所述红外发生器用于产生红外光并将红外光透视到待 检测者的乳腺上； 所述红外接收器用于釆集透过待检测者的乳腺的红 外光信号处理为包含待检测者的乳腺组织结构信息的模拟电信号； 所 述模数转换器用于将包含待检测者的乳腺组织结构信息的模拟电信号 模数转换为数字信号形式的乳腺影像信号； 所述通信端口用于将待检 测者的乳腺影像信号发送至所述医疗终端设备。
[权利要求 3] 如权利要求 1所述的乳腺筛査影像智能识别***， 其特征在于， 所述 影像识别指令为第一识别标志、 第二识别标志或第三识别标志， 所述 影像识别结果为正常的影像识别结果、 参考的影像识别结果或异常的 影像识别结果， 其中： 当所述影像识别指令为第一识别标志时， 所述 影像识别模块判断乳腺筛査影像的影像识别结果为正常， 并在指令识 别库中匹配与乳腺健康正常对应的文字作为正常的影像识别结果； 当 所述影像识别指令为第二识别标志吋， 所述影像识别模块根据第二识 别标志在指令识别库中匹配对应的文字作为参考的影像识别结果； 当 所述影像识别指令为第三识别标志吋， 所述影像识别模块判断影像识 别结果是异常的影像识别结果， 并根据第三识别标志在指令识别库中 匹配对应的文字作为异常的影像识别结果。
[权利要求 4] 如权利要求 3所述的乳腺筛査影像智能识别***， 其特征在于， 该系 统还包括结果标示模块， 用于对影像识别报告中的正常的影像识别结 果、 异常的影像识别结果或参考影像识别结果进行标识， 以预置的显 示方式在医疗终端设备的显示单元中显示影像识别报告中的正常的影 像识别结果、 异常的影像识别结果或参考影像识别结果。
[权利要求 5] 如权利要求 1所述的乳腺筛査影像智能识别***， 其特征在于， 当所 述指令识别库中未匹配出与所述影像识别指令对应的影像识别结果时
, 所述影像识别模块还用于从所述输入单元接收医生输入的影像识别 结果并添加至所述影像识别报告中， 并将输入的影像识别结果添加至 所述指令识别库中。
[权利要求 6] —种乳腺筛查影像智能识别方法， 应用于医疗终端设备中， 该医疗终 端设备通过通信网络连接至乳腺影像釆集终端和医疗信息平台， 其特 征在于， 该方法包括步骤： 从乳腺影像采集终端获取待检测者的乳腺 影像信号； 将待检测者的乳腺影像信号处理为乳腺筛査影像； 从医疗 终端设备的输入单元接收待检查者的个人信息和影像识别指令； 根据 影像识别指令在医疗信息平台的指令识别库中匹配与影像识别指令对 应的文字作为影像识别结果； 根据匹配出的影像识别结果生成用于显 示影像识别结果的影像识别报告， 并将待检査者的个人信息加入到影 像识别报告中； 在医疗信息平台的乳腺影像数据库中匹配与乳腺筛查 影像相似度在预置范围内的乳腺影像数据， 并将该匹配出的乳腺影像 数据加入到对应的影像识别报告中。
[权利要求 7] 如权利要求 6所述的乳腺筛査影像智能识别方法， 其特征在于， 所述 从乳腺影像采集终端获取待检测者的乳腺影像信号的步骤包括： 利用 乳腺影像采集终端的红外发生器产生红外光并将红外光透视到待检测 者的乳腺上； 通过乳腺影像采集终端的红外接收器采集透过待检测者 的乳腺的红外光信号处理为包含待检测者的乳腺组织结构信息的模拟 电信号； 利用乳腺影像采集终端的模数转换器将包含待检测者的乳腺 组织结构信息的模拟电信号模数转换为数字信号形式的乳腺影像信号 ； 通过乳腺影像采集终端的通信端口用于将待检测者的乳腺影像信号 发送至所述医疗终端设备。
如权利要求 6所述的乳腺筛査影像智能识别方法， 其特征在于， 所述 影像识别指令为第一识别标志、 第二识别标志或第三识别标志， 所述 影像识别结果为正常的影像识别结果、 参考的影像识别结果或异常的 影像识别结果， 其中： 当所述影像识别指令为第一识别标志时， 判断 乳腺筛査影像的影像识别结果为正常， 并在指令识别库中匹配与乳腺 健康正常对应的文字作为正常的影像识别结果； 当所述影像识别指令 为第二识别标志吋， 并根据第二识别标志在指令识别库中匹配对应的 文字作为参考的影像识别结果； 当所述影像识别指令为第三识别标志 时， 判断影像识别结果是异常的影像识别结果， 并根据第三识别标志 在指令识别库中匹配对应的文字作为异常的影像识别结果。
如权利要求 8所述的乳腺筛査影像智能识别方法， 其特征在于， 该方 法还包括如下步骤： 对影像识别报告中的正常的影像识别结果、 异常 的影像识别结果或参考影像识别结果进行标识； 以预置的显示方式在 医疗终端设备的显示单元中显示影像识别报告中的正常的影像识别结 果、 异常的影像识别结果或参考影像识别结果。
如权利要求 6所述的乳腺筛査影像智能识别方法， 其特征在于， 该方 法还包括如下步骤： 当所述指令识别库中未匹配出与所述影像识别指 令对应的影像识别结果时， 从所述输入单元接收医生输入的影像识别 结果并添加至影像识别报告中， 并将输入的影像识别结果添加至所述 指令识别库中。
PCT/CN2017/096132 2017-03-25 2017-08-05 乳腺筛查影像智能识别***及方法 WO2018176718A1 (zh)

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Publication number Priority date Publication date Assignee Title
CN107506604A (zh) * 2017-09-11 2017-12-22 深圳市前海安测信息技术有限公司 基于人工智能的影像识别***及方法
CN107506605A (zh) * 2017-09-11 2017-12-22 深圳市前海安测信息技术有限公司 基于医疗云平台的影像大数据分析***及方法
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Citations (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
TW200421151A (en) * 2003-04-11 2004-10-16 Ebm Technologies Inc Medical graphics report generation method and device thereof
CN101658413A (zh) * 2009-06-19 2010-03-03 中卫莱康科技发展（北京）有限公司 移动通信终端、诊断服务器及乳腺疾病检测***
US20120101733A1 (en) * 2010-10-21 2012-04-26 Samsung Electronics Co., Ltd Method and apparatus for processing image and medical image system performing the method
TW201301075A (zh) * 2011-06-29 2013-01-01 Medincom Technology Corp 醫療影像知識管理系統與其知識內容產生方法
CN104361245A (zh) * 2014-11-22 2015-02-18 张姬娟 检测数据处理***和方法
CN105559749A (zh) * 2015-11-19 2016-05-11 小红象医疗科技有限公司 一种基于红外医学影像的乳腺健康自动分析***和方法
CN105956391A (zh) * 2016-04-28 2016-09-21 深圳市前海安测信息技术有限公司 基于大数据的乳腺筛查***和方法

Patent Citations (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
TW200421151A (en) * 2003-04-11 2004-10-16 Ebm Technologies Inc Medical graphics report generation method and device thereof
CN101658413A (zh) * 2009-06-19 2010-03-03 中卫莱康科技发展（北京）有限公司 移动通信终端、诊断服务器及乳腺疾病检测***
US20120101733A1 (en) * 2010-10-21 2012-04-26 Samsung Electronics Co., Ltd Method and apparatus for processing image and medical image system performing the method
TW201301075A (zh) * 2011-06-29 2013-01-01 Medincom Technology Corp 醫療影像知識管理系統與其知識內容產生方法
CN104361245A (zh) * 2014-11-22 2015-02-18 张姬娟 检测数据处理***和方法
CN105559749A (zh) * 2015-11-19 2016-05-11 小红象医疗科技有限公司 一种基于红外医学影像的乳腺健康自动分析***和方法
CN105956391A (zh) * 2016-04-28 2016-09-21 深圳市前海安测信息技术有限公司 基于大数据的乳腺筛查***和方法

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