WO2017222283A1 - Method for analyzing health condition on basis of image photographing and providing health condition information - Google Patents

Method for analyzing health condition on basis of image photographing and providing health condition information Download PDF

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Publication number
WO2017222283A1
WO2017222283A1 PCT/KR2017/006478 KR2017006478W WO2017222283A1 WO 2017222283 A1 WO2017222283 A1 WO 2017222283A1 KR 2017006478 W KR2017006478 W KR 2017006478W WO 2017222283 A1 WO2017222283 A1 WO 2017222283A1
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Prior art keywords
image
bone
calculating
fat
muscle
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PCT/KR2017/006478
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French (fr)
Korean (ko)
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원영준
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가톨릭관동대학교 산학협력단
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Publication of WO2017222283A1 publication Critical patent/WO2017222283A1/en

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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
    • A61B5/05—Detecting, measuring or recording for diagnosis by means of electric currents or magnetic fields; Measuring using microwaves or radio waves 
    • A61B5/055—Detecting, measuring or recording for diagnosis by means of electric currents or magnetic fields; Measuring using microwaves or radio waves  involving electronic [EMR] or nuclear [NMR] magnetic resonance, e.g. magnetic resonance imaging
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B6/00—Apparatus or devices for radiation diagnosis; Apparatus or devices for radiation diagnosis combined with radiation therapy equipment
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B6/00—Apparatus or devices for radiation diagnosis; Apparatus or devices for radiation diagnosis combined with radiation therapy equipment
    • A61B6/02—Arrangements for diagnosis sequentially in different planes; Stereoscopic radiation diagnosis
    • A61B6/03—Computed tomography [CT]

Definitions

  • the present invention relates to a method for analyzing health status and providing health status information, and more particularly, to a method for analyzing health status and providing health status information based on an image photographed by a computer or a magnetic resonance imaging apparatus.
  • the bioelectrical impedance diagnosis method is a method of estimating the ratio of fat and muscle as a resistance value, which is problematic in that the accuracy of diagnosis is inferior when a confusion element such as metal is attached to a user's body.
  • the ultrasonic diagnostic method is a method of imaging the ultrasonic wave is reflected back by propagating the ultrasonic waves inside the body, which is limited in the diagnosis site because the delivery rate of the ultrasonic waves in the organ where the air is present.
  • the bioelectrical impedance diagnosis method and the ultrasonic diagnosis method cannot measure the area or volume of the bone, and thus the health condition cannot be diagnosed by including the ratio of the bone as a diagnostic element.
  • Dual energy radiation absorptiometry is a method of measuring bone, fat, and muscle, which is less correlated with central bone density and results for bone mineral density, fat, and muscle mass throughout the body. Cannot be measured.
  • An object of the present invention is to reflect the needs of the user as described above, to provide a health state analysis and health state information providing method of improving the accuracy of the diagnosis by diagnosing the state of health in relation to bone, fat and muscle.
  • a method for analyzing a state of health based on image capturing and providing health state information may include receiving a captured image of a body; Extracting an image of a specific body part from the captured image; Calculating a ratio of bone, fat and muscle in the extracted image; And extracting and displaying the health state information for the calculated ratio from the diagnosis table in which the health state information according to the ratio is stored.
  • Receiving a photographed image in the present invention may be a step of receiving a photographed image taken from a CT (Computed Tomography), MRI (Magnetic Resonance Image) or X-ray (X-Ray).
  • CT Computer Tomography
  • MRI Magnetic Resonance Image
  • X-Ray X-ray
  • Extracting an image in the present invention The step of matching the captured image to a specific reference point of the pre-stored specific body region image; Resizing the captured image such that the body outline displayed on the captured image matches the body outline displayed on the specific body image; And extracting an image of a region overlapping the specific body part image from the captured image.
  • the pre-stored specific body part image may be a standardized image of a rectangular shape which defines a specific body part as an upper limit and a lower limit, and connects an upper limit and a lower limit.
  • Extracting an image from the present invention Thereafter, the method may further include specifying an analysis target region in the extracted image.
  • Receiving a photographed image in the present invention may be a step of receiving a photographed image photographed from the front of the user's body.
  • Calculating a ratio of bone, fat, and muscle in the extracted image of the present invention calculating an area by detecting each area with an attenuation value corresponding to bone, fat, and muscle; And calculating a ratio of each area.
  • Receiving a photographed image in the present invention may be a step of receiving a photographed image photographed from the front, side, top of the user's body.
  • Calculating a ratio of bones, fats and muscles in the extracted image of the present invention calculating a volume by detecting each region with an attenuation value corresponding to bones, fats and muscles; And calculating a ratio of each volume.
  • Extracting and displaying the health state information in the present invention may be the step of displaying the health state information converted into a score.
  • the health state analysis and health state information providing method of the present invention it is possible to diagnose the state of health at a rate occupied by bones, fats, and muscles that are actually distributed in the body, which is more accurate than conventional techniques. Is improved.
  • FIG. 1 is a flow chart illustrating a health state analysis and health state information providing method according to an embodiment of the present invention.
  • FIG. 2 is a flowchart illustrating a method of extracting an image of a specific body part of a health state analysis and health state information providing method according to an exemplary embodiment of the present invention.
  • FIG. 3 is a flowchart illustrating a method of calculating a ratio of bone, fat, and muscle in a health state analysis and health state information providing method according to an exemplary embodiment of the present invention.
  • FIG. 4 is a flowchart illustrating a method of calculating a ratio of bone, fat, and muscle in a health state analysis and health state information providing method according to another exemplary embodiment of the present invention.
  • FIG. 5 is an exemplary diagram of a screen for implementing a method of extracting an image of a specific body part from a captured image according to an exemplary embodiment of the present invention.
  • FIG. 6 is an exemplary view of a screen for implementing a method for calculating the area ratio of bone, fat, and muscle according to an embodiment of the present invention.
  • FIG. 7 is an exemplary view of a screen for implementing a method for calculating a volume ratio of bone, fat, and muscle according to another embodiment of the present invention.
  • the health state analysis and health state information providing method may include receiving a captured image of a body, extracting an image of a specific body part from the captured image, and a ratio of bone, fat, and muscle in the extracted image. Calculating and
  • FIG. 1 is a flow chart illustrating a health state analysis and health state information providing method according to an embodiment of the present invention.
  • the imaging method of the present invention based on the imaging state of the present invention as shown in FIG. 1 and the method for providing health state information, receiving a captured image of the body (S100), extracting an image for a specific body part from the captured image (S200), calculating the ratio of bone, fat and muscle in the extracted image (S300), extracting and displaying the health state information for the ratio calculated from the diagnosis table in which the health state information according to the ratio is stored (S400). ).
  • Receiving the captured image is a step of receiving an image of the body of the test subject.
  • the image of the body of the test subject may be an image captured by CT (Computed Tomography), MRI (Magnetic Resonance Image) or X-ray (X-ray).
  • CT Computer Tomography
  • MRI Magnetic Resonance Image
  • X-ray X-ray
  • MCT computed tomography
  • MRI magnetic resonance image
  • X-rays x-rays
  • bone, fat, and muscles inside the body are attenuated by X-rays (hereinafter referred to as ,
  • Brightness hereinafter, referred to as illuminance value) is differently displayed according to the attenuation value, so that the areas where bone, fat, and muscle are distributed can be easily distinguished.
  • the image of the body of the test subject may be an image of the body of the test subject, or an image of the body of the test subject.
  • images of the subject's body taken from one side of the body can be diagnosed in a relatively short time with the area of bone, fat and muscle, the subject's body is taken from three sides to diagnose the state of health with the volume of bone, fat and muscle.
  • the accuracy of the diagnosis may be less than that.
  • Extracting an image of the specific body part (S200) is a step of extracting only an image of a specific body part to be examined from the captured image, which will be described in detail with reference to FIG. 2.
  • Extracting an image of a specific body part from the captured image may include matching the captured image with a specific reference point of a pre-stored specific body part image (S201). Resizing the captured image to match the unit (S202) and extracting an image of a region overlapped with a specific body region image from the captured image (S203).
  • Matching the specific reference point is a step of superimposing a specific body part image on the captured image. Since the two images overlap with respect to a specific reference point, the position of a specific body part in the captured image including a region other than the specific body part may be identified as the position where the specific body part image is overlapped. In this case, when a specific reference point is a specific fat or a specific muscle, the formation position may vary depending on the health state of the test subject, and therefore, it is preferable that the formation position is a specific bone or a specific organ.
  • the specific body region image is a standardized image of a rectangular form connecting an upper limit and a lower limit by defining an uppermost end of a specific body part as an upper limit and a lower end as a lower limit.
  • the line connecting the upper limit and the lower limit is located outside the outer part of the body so that it is not formed across the body part.
  • the uppermost end of the femoral ball head may be defined as the upper limit and the lowermost end of the small electron may be defined.
  • the step of resizing when the two images are matched with a specific reference point and the image of the overlapping area is extracted immediately, the large body is extracted from the small part and the small body is extracted from the large part. Since the body outline displayed on the captured image does not exist, the size of the captured image is reduced or increased to match the extraction range of the two images so that the body outline displayed on the specific body region image is matched.
  • Extracting an image of the overlapped region (S203) is extracting only a specific body part image from the captured image.
  • the method may further include designating an analysis target region in the extracted image after the extracting of the image (S203). For example, in the extracted image, the outline of the body and the outline of the bone may be determined, and only an area surrounding the bone may be designated as an analysis target region.
  • FIG. 5A illustrates a specific reference point 12 as the hip joint.
  • the superimposed image of the captured image 10 and the specific body part 11 around the hip joint are illustrated.
  • 5B illustrates a resizing of the captured image 10 so that the body outline of the specific body image 11 and the body outline of the captured image 10 correspond to each other, and from the captured image 10, a specific body image ( 11 shows only the image of the overlapped region.
  • the analysis target region 13 may be designated in the extracted image, and when the analysis target region 13 is designated as a region surrounding the bone, as shown in FIG. Except for the region, only the region around the femur may be designated as the analysis target region 13.
  • the step (S300) of calculating a ratio of bone, muscle, and fat is performed.
  • the calculating of the ratio (S300) is a step for determining the health state of a specific body part by using the ratio of bone, fat and muscle in the body of the test subject, which will be described in detail with reference to FIGS.
  • FIG. 3 is a flowchart illustrating a method of calculating a ratio of bone, fat, and muscle in a health state analysis and health state information providing method according to an exemplary embodiment of the present invention.
  • Calculating the ratio of bone, fat and muscle in the extracted image (S300) includes calculating a bone area (S301), calculating a fat area (S302), calculating a muscle area (S303), and overall Comprising a step (S304) of calculating the ratio of each area of the area (bone area + fat area + muscle area).
  • the step of calculating the bone area in the extracted image is a step of finding and classifying a region corresponding to the attenuation value corresponding to the bone 200 to 900 HU (Hounsfield Unit) by the roughness value and obtaining the area of the region.
  • the step of calculating the fat area is a step of finding and classifying an area corresponding to -30 to -190 Hounsfield Unit (HU), which is an attenuation value corresponding to fat, by the illuminance value, and obtaining an area of the area.
  • HU Hounsfield Unit
  • Computing the muscle area (S303) is a step of finding and classifying an area corresponding to 30 to 70 HU (Hounsfield Unit), which is attenuation value corresponding to the muscle, by dividing the illuminance value and obtaining an area of the area.
  • HU Heunsfield Unit
  • Calculating the ratio of each area of the total area is to calculate the ratio of the area of each of the bones, fats and muscles calculated in the step S301 to S303 in the total area (bone area + fat area + muscle area) Step.
  • the step (S300) of calculating the ratio of bone, fat, and muscle in the extracted image will be described with reference to FIG. 6, which is an exemplary view of a screen for implementing the same, and FIG. 6 shows 200 to 900 HUs in the extracted image.
  • the figure shows the muscle area illuminance value corresponding to the attenuation value of the Hounsfield Unit (HU) and indicated by the closed curve.
  • the area occupied by the area is calculated and the ratio of each area is calculated based on the total area (bone area + fat area + muscle area).
  • FIG. 4 is a flowchart illustrating a method of calculating a ratio of bone, fat, and muscle in a health state analysis and health state information providing method according to another exemplary embodiment of the present invention.
  • Calculating the ratio of bone, fat and muscle in the extracted image (S300) is a step of calculating the volume ratio of bone, fat and muscle to determine the health state, calculating the bone volume (S311), fat Comprising a step of calculating the volume (S312), a step of calculating the muscle volume (S313) and the step of giving a ratio of each volume of the total volume (bone volume + fat volume + muscle volume) (S314).
  • a plurality of captured images taken from the front, side, and top of the body of the test subject must be received in step S100 of receiving the captured image.
  • the step of calculating the bone volume from the extracted image is to find and classify the area corresponding to the attenuation value 200 to 900 HU (Hounsfield Unit), which is the attenuation value corresponding to the bone, in each photographed image, and to sum the bone regions of each photographed image. Calculate the bone volume.
  • the attenuation value 200 to 900 HU Heunsfield Unit
  • the area corresponding to the attenuation value -30 to -190 HU (Hounsfield Unit) corresponding to the fat in each photographed image is found by dividing the illumination value, and the fat region of each photographed image is summed. It is a step of calculating the volume of fat.
  • the muscle volume (S313), the area corresponding to the attenuation value 30 to 70 HU (Hounsfield Unit) corresponding to the muscle in each photographed image is found by dividing the illuminance value, and the muscle area of each photographed image is added to the muscle. Calculating the volume of.
  • Calculating the ratio of each volume of the total volume is to calculate the ratio of the volume of each of the bones, fats and muscles calculated in the steps S311 to S313 in the total volume (bone volume + fat volume + muscle volume) Step.
  • FIG. 7 is an exemplary view of a screen for implementing the same.
  • the images taken from the side and the top should be received.
  • 7 (a) is an image of the body of the test subject taken from the upper surface
  • (b) is an image of the body of the test subject taken from the front
  • (C) is an image of the body of the test subject taken from the side.
  • the images taken from the front and side surfaces include four lumbar vertebrae 14, 15, 16, and 17 in one shot.
  • the second lumbar spine 15 to the fourth lumbar spine 17 are covered by the first lumbar spine 14
  • only one lumbar spine may be included in one image, so that each lumbar spine is separately.
  • You need to get a video. 7 is an image of the subject's body taken from the front, side, and top surface and extracted from the first lumbar spine 14 to the fourth lumbar spine 17, and attenuation values corresponding to bones in all extracted images are 200 to 900 HU.
  • the figure shows the bone area of the Hounsfield Unit with the roughness value and displayed as a closed curve.
  • each area is displayed as a closed curve in all the extracted images, and then the displayed areas are summed to calculate the bone volume.
  • the muscles and fats are searched for corresponding illuminance values and displayed as closed curves, and the displayed areas are summed to calculate the respective volume, and the proportion of each area based on the total volume (bone volume + fat volume + muscle volume).
  • step (S400) of extracting and displaying health state information on the ratio calculated from the diagnosis table in which health state information according to the ratio is stored is performed.
  • Extracting and displaying the health state information (S400) is a step of determining a health state with a ratio of bones, fats and muscles calculated in the step (S300), and the ratio of bones, fats and muscles. Extracts and displays only the health status information according to the ratio calculated from the diagnosis table in which the health status information is stored.
  • the health state information may be provided to the test subject by scoring.
  • the health state analysis and the health state information providing method of the present invention it is possible to diagnose the state of health at the proportion of bones, fats, and muscles that are actually distributed in the body, thereby improving the accuracy of diagnosis compared to the prior art.

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Abstract

The present invention relates to a method for analyzing a health condition and providing health condition information and, particularly, to a method for analyzing a health condition on the basis of an image taken by a computer or a magnetic resonance imaging apparatus and providing health condition information, the method comprising: a step of receiving the image taken of a body; a step of extracting an image for a specific body part from the image taken; a step of calculating bone, fat and muscle percentages from the extracted image; and a step of extracting and displaying, from a diagnostic table in which health condition information according to the percentages is stored, the health condition information for the calculated percentages. The method for analyzing a health condition and providing health condition information of the present invention as described above allows for the diagnosis of a health condition on the basis of bone, fat and muscle percentages actually distributed in the body, thereby improving accuracy in diagnosis as compared to the conventional art.

Description

영상촬영 기반의 건강상태 분석 및 건강상태 정보 제공 방법How to analyze health status based on imaging and provide health status information
본 발명은 건강상태 분석 및 건강상태 정보 제공 방법에 관한 것으로서, 특히, 컴퓨터 또는 자기공명 촬영장치로 촬영된 영상을 기반으로 건강상태를 분석하고 건강상태 정보를 제공하는 방법에 관한 것이다.The present invention relates to a method for analyzing health status and providing health status information, and more particularly, to a method for analyzing health status and providing health status information based on an image photographed by a computer or a magnetic resonance imaging apparatus.
종래에는 건강상태를 진단하기 위해서 지방 및 근육의 비율을 측정하는 것이 일반적이였으며, 이와 관련된 진단기술로는 생체전기 임피던스 진단법 및 초음파 진단법이 있다. 생체전기 임피던스 진단법은 저항값으로 지방 및 근육의 비율을 추정하는 방법인데, 이는 금속과 같이 저항값을 혼동시키는 요소가 사용자의 몸에 부착된 경우 진단의 정확도가 떨어지는 문제점이 있다. 또한, 초음파 진단법은 초음파를 신체내부로 전파시켜 반사되어 되돌아오는 초음파를 영상화하는 방법인데, 이는 내부에 공기가 존재하는 장기에서는 초음파의 전달율이 떨어지기 때문에 진단부위의 제약이 있다. In the past, it was common to measure the ratio of fat and muscle to diagnose a health condition, and related diagnostic techniques include bioelectrical impedance diagnosis and ultrasound diagnosis. The bioelectrical impedance diagnosis method is a method of estimating the ratio of fat and muscle as a resistance value, which is problematic in that the accuracy of diagnosis is inferior when a confusion element such as metal is attached to a user's body. In addition, the ultrasonic diagnostic method is a method of imaging the ultrasonic wave is reflected back by propagating the ultrasonic waves inside the body, which is limited in the diagnosis site because the delivery rate of the ultrasonic waves in the organ where the air is present.
건강상태 진단 시에 지방 및 근육이 차지하는 비율뿐만 아니라 뼈가 차지하는 비율도 중요한 진단요소이다. 그런데 생체전기 임피던스 진단법, 초음파 진단법 은 뼈의 면적이나 부피에 대해서 계측이 불가하여 뼈가 차지하는 비율을 진단요소로 포함하여 건강상태를 진단할 수 없다.In the diagnosis of health status, the percentage of fat and muscle as well as the percentage of bone is an important diagnostic factor. However, the bioelectrical impedance diagnosis method and the ultrasonic diagnosis method cannot measure the area or volume of the bone, and thus the health condition cannot be diagnosed by including the ratio of the bone as a diagnostic element.
뼈, 지방 및 근육을 계측할 수 있는 방법으로는 이중 에너지 방사선 흡수 측정법이 있는데, 이는 전신의 골밀도, 지방, 근육량에 대한 결과와 중심성 골밀도와의 상관성이 떨어지고, 중심성 골밀도와 그 주변부 근육, 지방과의 관계는 측정할 수 없다.Dual energy radiation absorptiometry is a method of measuring bone, fat, and muscle, which is less correlated with central bone density and results for bone mineral density, fat, and muscle mass throughout the body. Cannot be measured.
따라서, 뼈, 지방, 근육과의 관계로 건강상태를 진단하여 진단의 정확성이 향상된 건강상태 분석 및 건강상태 정보 제공 방법에 대한 요구가 생기게 되었다.Therefore, there is a need for a method of analyzing health status and providing health status information in which a diagnosis of a health condition is improved by a relationship with bones, fats, and muscles, thereby improving the accuracy of diagnosis.
본 발명의 목적은 상기와 같은 사용자의 요구를 반영한 것으로, 뼈, 지방 및 근육과의 관계로 건강상태를 진단하여 진단의 정확성이 향상된 건강상태 분석 및 건강상태 정보 제공 방법을 제공하는데 있다.An object of the present invention is to reflect the needs of the user as described above, to provide a health state analysis and health state information providing method of improving the accuracy of the diagnosis by diagnosing the state of health in relation to bone, fat and muscle.
본 발명의 실시예에 따른 영상촬영 기반의 건강상태 분석 및 건강상태 정보 제공 방법은 신체의 촬영 영상을 수신하는 단계; 상기 촬영 영상에서 특정 신체부위에 대한 영상을 추출하는 단계; 상기 추출된 영상에서 뼈, 지방 및 근육의 비율을 산출하는 단계; 및 비율에 따른 건강상태 정보가 저장된 진단 테이블로부터 상기 산출된 비율에 대한 건강상태 정보를 추출하여 표시하는 단계;를 포함하는 것을 특징으로 한다.According to an exemplary embodiment of the present invention, a method for analyzing a state of health based on image capturing and providing health state information may include receiving a captured image of a body; Extracting an image of a specific body part from the captured image; Calculating a ratio of bone, fat and muscle in the extracted image; And extracting and displaying the health state information for the calculated ratio from the diagnosis table in which the health state information according to the ratio is stored.
본 발명에서 촬영 영상을 수신하는 단계;는 CT(Computed Tomography), MRI(Magnetic Resonance Image) 또는 엑스선(X-Ray)으로부터 촬영된 촬영 영상을 수신하는 단계;일 수 있다.Receiving a photographed image in the present invention; may be a step of receiving a photographed image taken from a CT (Computed Tomography), MRI (Magnetic Resonance Image) or X-ray (X-Ray).
본 발명에서 영상을 추출하는 단계;는 촬영 영상을 기저장된 특정 신체부위 영상의 특정 기준점에 일치시키는 단계; 상기 촬영 영상에 표시된 신체 외곽부가 상기 특정 신체부위 영상에 표시된 신체 외곽부와 일치하도록 촬영 영상을 리사이징(resizing) 하는 단계; 및 상기 촬영 영상 중 상기 특정 신체부위 영상과 중첩된 영역의 영상을 추출하는 단계;를 포함할 수 있다.Extracting an image in the present invention; The step of matching the captured image to a specific reference point of the pre-stored specific body region image; Resizing the captured image such that the body outline displayed on the captured image matches the body outline displayed on the specific body image; And extracting an image of a region overlapping the specific body part image from the captured image.
본 발명에서 기저장된 특정 신체부위 영상은 특정 신체부위를 상한선과 하한선으로 규정하고 상한선과 하한선을 이은 직사각형 형태의 표준화 영상일 수 있다.In the present invention, the pre-stored specific body part image may be a standardized image of a rectangular shape which defines a specific body part as an upper limit and a lower limit, and connects an upper limit and a lower limit.
본 발명에서 영상을 추출하는 단계; 이후, 추출된 영상에서 분석대상 영역을 지정하는 단계;를 더 포함할 수 있다.Extracting an image from the present invention; Thereafter, the method may further include specifying an analysis target region in the extracted image.
본 발명에서 촬영 영상을 수신하는 단계;는 사용자의 신체를 정면에서 촬영한 촬영 영상을 수신하는 단계;일 수 있다.Receiving a photographed image in the present invention; may be a step of receiving a photographed image photographed from the front of the user's body.
본 발명에서 추출된 영상에서 뼈, 지방 및 근육의 비율을 산출하는 단계;는 뼈, 지방 및 근육에 해당하는 감쇠 값으로 각 영역을 검출하여 면적을 계산하는 단계; 및 각 면적의 비율을 산출하는 단계;를 포함할 수 있다.Calculating a ratio of bone, fat, and muscle in the extracted image of the present invention; calculating an area by detecting each area with an attenuation value corresponding to bone, fat, and muscle; And calculating a ratio of each area.
본 발명에서 촬영 영상을 수신하는 단계;는 사용자의 신체를 정면, 측면, 상면에서 촬영한 촬영 영상을 수신하는 단계;일 수 있다.Receiving a photographed image in the present invention; may be a step of receiving a photographed image photographed from the front, side, top of the user's body.
본 발명에서 추출된 영상에서 뼈, 지방 및 근육의 비율을 산출하는 단계;는 뼈, 지방 및 근육에 해당하는 감쇠 값으로 각 영역을 검출하여 부피를 계산하는 단계; 및 각 부피의 비율을 산출하는 단계;를 포함할 수 있다.Calculating a ratio of bones, fats and muscles in the extracted image of the present invention; calculating a volume by detecting each region with an attenuation value corresponding to bones, fats and muscles; And calculating a ratio of each volume.
본 발명에서 건강상태 정보를 추출하여 표시하는 단계;는 건강상태 정보를 점수로 환산하여 표시하는 단계;일 수 있다.Extracting and displaying the health state information in the present invention; may be the step of displaying the health state information converted into a score.
전술한 바와 같이 본 발명의 건강상태 분석 및 건강상태 정보 제공 방법을 이용하면, 실제로 체내에 분포되어 있는 뼈, 지방 및 근육이 차지하는 비율로 건강상태를 진단할 수 있어, 종래의 기술보다 진단의 정확도가 향상된다.As described above, by using the health state analysis and health state information providing method of the present invention, it is possible to diagnose the state of health at a rate occupied by bones, fats, and muscles that are actually distributed in the body, which is more accurate than conventional techniques. Is improved.
도 1은 본 발명의 실시예에 따른 건강상태 분석 및 건강상태 정보 제공 방법을 도시하는 순서도이다.1 is a flow chart illustrating a health state analysis and health state information providing method according to an embodiment of the present invention.
도 2는 본 발명의 실시예에 따른 건강상태 분석 및 건강상태 정보 제공 방법 중 특정 신체부위에 대한 영상 추출 방법을 도시하는 순서도이다.2 is a flowchart illustrating a method of extracting an image of a specific body part of a health state analysis and health state information providing method according to an exemplary embodiment of the present invention.
도 3은 본 발명의 실시예에 따른 건강상태 분석 및 건강상태 정보 제공 방법 중 뼈, 지방 및 근육의 비율을 계산 방법을 도시하는 순서도이다. 3 is a flowchart illustrating a method of calculating a ratio of bone, fat, and muscle in a health state analysis and health state information providing method according to an exemplary embodiment of the present invention.
도 4는 본 발명의 다른 실시예에 따른 건강상태 분석 및 건강상태 정보 제공 방법 중 뼈, 지방 및 근육의 비율을 계산 방법을 도시하는 순서도이다.4 is a flowchart illustrating a method of calculating a ratio of bone, fat, and muscle in a health state analysis and health state information providing method according to another exemplary embodiment of the present invention.
도 5는 본 발명의 실시예에 따라 촬영 영상에서 특정 신체부위에 대한 영상을 추출하는 방법을 구현하는 화면의 예시도이다.5 is an exemplary diagram of a screen for implementing a method of extracting an image of a specific body part from a captured image according to an exemplary embodiment of the present invention.
도 6은 본 발명의 실시예에 따라 뼈, 지방 및 근육의 면적 비율 계산방법을 구현하는 화면의 예시도이다.6 is an exemplary view of a screen for implementing a method for calculating the area ratio of bone, fat, and muscle according to an embodiment of the present invention.
도 7은 본 발명의 다른 실시예에 따라 뼈, 지방 및 근육의 부피 비율 계산방법을 구현하는 화면의 예시도이다.7 is an exemplary view of a screen for implementing a method for calculating a volume ratio of bone, fat, and muscle according to another embodiment of the present invention.
상기 건강상태 분석 및 건강상태 정보 제공 방법은 바람직하게는 신체의 촬영 영상을 수신하는 단계, 상기 촬영 영상에서 특정 신체부위에 대한 영상을 추출하는 단계, 상기 추출된 영상에서 뼈, 지방 및 근육의 비율을 산출하는 단계 및The health state analysis and health state information providing method may include receiving a captured image of a body, extracting an image of a specific body part from the captured image, and a ratio of bone, fat, and muscle in the extracted image. Calculating and
비율에 따른 건강상태 정보가 저장된 진단 테이블로부터 상기 산출된 비율에 대한 건강상태 정보를 추출하여 표시하는 단계를 포함하는 것 일 수 있다.And extracting and displaying health state information on the calculated ratio from a diagnosis table in which health state information according to a ratio is stored.
아래에서는 첨부한 도면을 참조하여 본 발명이 속하는 기술분야에서 통상의 지식을 가진 자가 용이하게 실시할 수 있도록 본 발명의 실시예를 상세히 설명한다. 그러나 본 발명은 여러 가지 상이한 형태로 구현될 수 있으며 여기에서 설명하는 실시예에 한정되지 않는다. 그리고 도면에서 본 발명을 명확하게 설명하기 위해서 설명과 관계없는 부분은 생략하였으며, 명세서 전체를 통하여 유사한 부분에 대해서는 유사한 도면 부호를 붙였다.DETAILED DESCRIPTION Hereinafter, exemplary embodiments of the present invention will be described in detail with reference to the accompanying drawings so that those skilled in the art may easily implement the present invention. As those skilled in the art would realize, the described embodiments may be modified in various different ways, all without departing from the spirit or scope of the present invention. In the drawings, parts irrelevant to the description are omitted in order to clearly describe the present invention, and like reference numerals designate like parts throughout the specification.
도 1은 본 발명의 실시예에 따른 건강상태 분석 및 건강상태 정보 제공 방법을 도시하는 순서도이다. 도 1에 도시된 바와 같은 본원발명의 영상촬영 기반의 건강상태 분석 및 건강상태 정보 제공 방법은 크게 신체의 촬영 영상을 수신하는 단계(S100), 촬영 영상에서 특정 신체부위에 대한 영상을 추출하는 단계(S200), 추출된 영상에서 뼈, 지방 및 근육의 비율을 산출하는 단계(S300), 비율에 따른 건강상태 정보가 저장된 진단테이블로부터 산출된 비율에 대한 건강상태 정보를 추출하여 표시하는 단계(S400)를 포함한다.1 is a flow chart illustrating a health state analysis and health state information providing method according to an embodiment of the present invention. In the imaging method of the present invention based on the imaging state of the present invention as shown in FIG. 1 and the method for providing health state information, receiving a captured image of the body (S100), extracting an image for a specific body part from the captured image (S200), calculating the ratio of bone, fat and muscle in the extracted image (S300), extracting and displaying the health state information for the ratio calculated from the diagnosis table in which the health state information according to the ratio is stored (S400). ).
상기 촬영 영상을 수신하는 단계(S100)는 검사 대상자의 신체를 촬영한 영상을 수신하는 단계이다. 이때, 검사 대상자의 신체를 촬영한 영상은 CT(Computed Tomography), MRI(Magnetic Resonance Image) 또는 엑스선(X-ray)에 의해 촬영된 영상일 수 있다. 검사 대상자의 신체를 CT(Computed Tomography), MRI(Magnetic Resonance Image) 또는 엑스선(X-ray)로 촬영하는 경우, 신체 내부의 뼈, 지방 및 근육은 엑스선(X-ray)이 감쇠되는 정도(이하, 감쇠 값)에 따라 명도(이하, 조도 값)가 다르게 표시되어 뼈, 지방 및 근육이 분포된 영역을 용이하게 구분할 수 있다. 또한, 검사 대상자의 신체를 촬영한 영상은 검사 대상자의 신체를 일면에서 촬영한 영상 또는 검사 대상자의 신체를 삼면에서 촬영한 영상일 수 있다. 검사 대상자의 신체를 일면에서 촬영한 영상은 뼈, 지방 및 근육의 면적으로 비교적 단시간 내에 건강상태를 진단할 수 있지만 검사 대상자의 신체를 삼면에서 촬영하여 뼈, 지방 및 근육의 부피로 건강상태를 진단하는 방법보다는 진단의 정확도가 떨어질 수 있다.Receiving the captured image (S100) is a step of receiving an image of the body of the test subject. In this case, the image of the body of the test subject may be an image captured by CT (Computed Tomography), MRI (Magnetic Resonance Image) or X-ray (X-ray). When a patient's body is taken with computed tomography (MCT), magnetic resonance image (MRI), or x-rays (X-rays), bone, fat, and muscles inside the body are attenuated by X-rays (hereinafter referred to as , Brightness (hereinafter, referred to as illuminance value) is differently displayed according to the attenuation value, so that the areas where bone, fat, and muscle are distributed can be easily distinguished. The image of the body of the test subject may be an image of the body of the test subject, or an image of the body of the test subject. Although images of the subject's body taken from one side of the body can be diagnosed in a relatively short time with the area of bone, fat and muscle, the subject's body is taken from three sides to diagnose the state of health with the volume of bone, fat and muscle. The accuracy of the diagnosis may be less than that.
촬영 영상을 수신하는 단계(S100)가 완료되면, 촬영 영상에서 특정 신체부위에 대한 영상을 추출하는 단계(S200)를 진행한다. 상기 특정 신체부위에 대한 영상을 추출하는 단계(S200)는 촬영 영상에서 검사를 진행하고자하는 특정 신체부위에 대한 영상만을 추출하는 단계로, 이는 도 2에서 자세히 설명한다.When the step (S100) of receiving the captured image is completed, the process of extracting an image of a specific body part from the captured image (S200) is performed. Extracting an image of the specific body part (S200) is a step of extracting only an image of a specific body part to be examined from the captured image, which will be described in detail with reference to FIG. 2.
도 2는 본 발명의 실시예에 따른 건강상태 분석 및 건강상태 정보 제공 방법 중 특정 신체부위에 대한 영상 추출방법을 도시하는 순서도이다. 촬영 영상에서 특정 신체부위에 대한 영상을 추출하는 단계(S200)는 촬영 영상을 기저장된 특정 신체부위 영상의 특정 기준점에 일치시키는 단계(S201), 촬영 영상의 신체 외곽부가 특정 신체부위 영상의 신체 외곽부와 일치하도록 촬영 영상을 리사이징하는 단계(S202) 및 촬영 영상 중 특정 신체부위 영상과 중첩된 영역의 영상을 추출하는 단계(S203)를 포함한다. 2 is a flowchart illustrating a method of extracting an image of a specific body part of a health state analysis and health state information providing method according to an exemplary embodiment of the present invention. Extracting an image of a specific body part from the captured image (S200) may include matching the captured image with a specific reference point of a pre-stored specific body part image (S201). Resizing the captured image to match the unit (S202) and extracting an image of a region overlapped with a specific body region image from the captured image (S203).
상기 특정 기준점에 일치시키는 단계(S201)는 촬영 영상에 특정 신체부위 영상을 중첩하는 단계이다. 두 영상은 특정 기준점을 중심으로 중첩되기 때문에, 특정 신체부위 이외의 영역이 포함된 촬영 영상에서 특정 신체부위의 위치를 상기 특정 신체부위 영상이 중첩된 위치로 확인할 수 있다. 이때, 특정 기준점이 특정 지방 또는 특정 근육일 경우 검사 대상자의 건강상태에 따라 형성위치가 달라질 수 있기 때문에, 형성위치가 일정한 특정 뼈 또는 특정 장기인 것이 바람직하다.Matching the specific reference point (S201) is a step of superimposing a specific body part image on the captured image. Since the two images overlap with respect to a specific reference point, the position of a specific body part in the captured image including a region other than the specific body part may be identified as the position where the specific body part image is overlapped. In this case, when a specific reference point is a specific fat or a specific muscle, the formation position may vary depending on the health state of the test subject, and therefore, it is preferable that the formation position is a specific bone or a specific organ.
특정 신체부위 영상은 특정 신체부위의 최상단을 상한선으로 규정하고 최하단을 하한선으로 규정하여, 상한선과 하한선을 이은 직사각형 형태의 표준화 영상이다. 이때, 상한선과 하한선을 잇는 선은 신체부위를 가로질러 형성되지 않도록 신체의 외곽부 바깥쪽에 위치하는 것이 바람직하다. 예를 들어, 특정 신체부위가 대퇴부 상부인 경우, 대퇴골두의 최상단을 상한선으로 규정하고 소전자의 최하단을 하한선을 규정할 수 있다.The specific body region image is a standardized image of a rectangular form connecting an upper limit and a lower limit by defining an uppermost end of a specific body part as an upper limit and a lower end as a lower limit. At this time, it is preferable that the line connecting the upper limit and the lower limit is located outside the outer part of the body so that it is not formed across the body part. For example, if a particular body part is the upper thigh, the uppermost end of the femoral ball head may be defined as the upper limit and the lowermost end of the small electron may be defined.
상기 리사이징하는 단계(S202)는 두 영상을 특정 기준점으로 일치시킨 후 바로 중첩되는 영역의 영상을 추출할 경우, 신체가 큰 사람은 추출되는 부분이 작으며 신체가 작은 사람은 추출되는 부분이 클 수밖에 없기 때문에, 촬영 영상에 표시된 신체 외곽부가 특정 신체부위 영상에 표시된 신체 외곽부와 일치하도록 촬영 영상의 사이즈를 줄이거나 늘려 두 영상의 추출범위를 일치시키는 단계이다. In the step of resizing (S202), when the two images are matched with a specific reference point and the image of the overlapping area is extracted immediately, the large body is extracted from the small part and the small body is extracted from the large part. Since the body outline displayed on the captured image does not exist, the size of the captured image is reduced or increased to match the extraction range of the two images so that the body outline displayed on the specific body region image is matched.
상기 중첩된 영역의 영상을 추출하는 단계(S203)는 촬영 영상에서 특정 신체부위 영상만을 추출하는 단계이다. 도 2에는 도시되어 있지 않지만 본 발명의 실시예에 따라, 상기 영상을 추출하는 단계(S203) 이후에 추출된 영상에서 분석 대상영역을 지정하는 단계를 더 포함할 수 있다. 예를 들어, 추출된 영상에서 신체의 외곽선 및 뼈의 외곽선을 결정하고, 뼈를 둘러싸는 영역만을 분석 대상역역으로 지정할 수 있다.Extracting an image of the overlapped region (S203) is extracting only a specific body part image from the captured image. Although not shown in FIG. 2, according to an embodiment of the present invention, the method may further include designating an analysis target region in the extracted image after the extracting of the image (S203). For example, in the extracted image, the outline of the body and the outline of the bone may be determined, and only an area surrounding the bone may be designated as an analysis target region.
촬영 영상에서 특정 신체부위에 대한 영상을 추출하는 단계(S200)에 대해서 이를 구현하는 화면의 예시도인 도 5를 참조하여 설명하면, 도 5의 (a)는 특정 기준점(12)을 고관절로 설정되며, 고관절을 중심으로 촬영 영상(10)과 특정 신체부위 영상(11)을 중첩시키는 모습을 도시한다. 도 5의 (b)는 특정 신체부위 영상(11)의 신체 외곽부와 촬영 영상(10)의 신체외곽부가 일치하도록 촬영 영상(10)을 리사이징하고, 촬영 영상(10)으로부터 특정 신체부위 영상(11)과 중첩된 영역의 영상만을 추출한 모습을 도시한다. 이때, 추출된 영상에서 분석 대상영역(13)이 지정될 수 있으며, 분석 대상영역(13)이 뼈를 둘러싸는 영역으로 지정되어 있는 경우, 도 5의 (b)와 같이 뼈가 존재하지 않는 성기 영역을 제외하고 대퇴골 주변 영역만 분석 대상영역(13)으로 지정될 수 있다.The step (S200) of extracting an image of a specific body part from the captured image will be described with reference to FIG. 5, which is an exemplary view of a screen for implementing the same. FIG. 5A illustrates a specific reference point 12 as the hip joint. The superimposed image of the captured image 10 and the specific body part 11 around the hip joint are illustrated. 5B illustrates a resizing of the captured image 10 so that the body outline of the specific body image 11 and the body outline of the captured image 10 correspond to each other, and from the captured image 10, a specific body image ( 11 shows only the image of the overlapped region. In this case, the analysis target region 13 may be designated in the extracted image, and when the analysis target region 13 is designated as a region surrounding the bone, as shown in FIG. Except for the region, only the region around the femur may be designated as the analysis target region 13.
촬영 영상에서 특정 신체부위에 대한 영상을 추출하는 단계(S200)가 완료되면, 뼈, 근육 및 지방의 비율을 계산하는 단계(S300)를 진행한다. 상기 비율을 산출하는 단계(S300)는 검사 대상자의 신체 내의 뼈, 지방 및 근육이 차지하는 비율을 이용해 특정 신체부위의 건강상태를 파악하기 위한 단계로, 이는 도 3 및 도 4에서 자세히 설명한다.When the step (S200) of extracting an image of a specific body part from the captured image is completed, the step (S300) of calculating a ratio of bone, muscle, and fat is performed. The calculating of the ratio (S300) is a step for determining the health state of a specific body part by using the ratio of bone, fat and muscle in the body of the test subject, which will be described in detail with reference to FIGS.
도 3은 본 발명의 실시예에 따른 건강상태 분석 및 건강상태 정보 제공 방법 중 뼈, 지방 및 근육의 비율을 계산 방법을 도시하는 순서도이다. 추출된 영상에서 뼈, 지방 및 근육의 비율을 산출하는 단계(S300)는 뼈면적을 산출하는 단계(S301), 지방면적을 산출하는 단계(S302), 근육면적을 산출하는 단계(S303) 및 전체 면적(뼈면적 + 지방면적 + 근육면적) 중 각 면적의 비율을 산출하는 단계(S304)를 포함한다.3 is a flowchart illustrating a method of calculating a ratio of bone, fat, and muscle in a health state analysis and health state information providing method according to an exemplary embodiment of the present invention. Calculating the ratio of bone, fat and muscle in the extracted image (S300) includes calculating a bone area (S301), calculating a fat area (S302), calculating a muscle area (S303), and overall Comprising a step (S304) of calculating the ratio of each area of the area (bone area + fat area + muscle area).
이때, 추출된 영상에서 뼈면적을 산출하는 단계(S301)는 뼈에 해당하는 감쇠 값인 200 내지 900 HU(Hounsfield Unit)에 해당하는 영역을 조도 값으로 찾아 구분하고 그 영역의 면적을 구하는 단계이다. 지방면적을 산출하는 단계(S302)는 지방에 해당하는 감쇠 값인 -30 내지 -190 HU(Hounsfield Unit)에 해당하는 영역을 조도 값으로 찾아 구분하고 그 영역의 면적을 구하는 단계이다. 근육면적을 산출하는 단계(S303)는 근육에 해당하는 감쇠 값인 30 내지 70 HU(Hounsfield Unit)에 해당하는 영역을 조도 값으로 찾아 구분하고 그 영역의 면적을 구하는 단계이다. At this time, the step of calculating the bone area in the extracted image (S301) is a step of finding and classifying a region corresponding to the attenuation value corresponding to the bone 200 to 900 HU (Hounsfield Unit) by the roughness value and obtaining the area of the region. The step of calculating the fat area (S302) is a step of finding and classifying an area corresponding to -30 to -190 Hounsfield Unit (HU), which is an attenuation value corresponding to fat, by the illuminance value, and obtaining an area of the area. Computing the muscle area (S303) is a step of finding and classifying an area corresponding to 30 to 70 HU (Hounsfield Unit), which is attenuation value corresponding to the muscle, by dividing the illuminance value and obtaining an area of the area.
전체 면적 중 각 면적의 비율을 산출하는 단계(S304)는 상기 S301 내지 S303 단계에서 계산된 뼈, 지방 및 근육 각각의 면적이 전체 면적(뼈면적 + 지방면적 + 근육면적)에서 차지하는 비율을 산출하는 단계이다.Calculating the ratio of each area of the total area (S304) is to calculate the ratio of the area of each of the bones, fats and muscles calculated in the step S301 to S303 in the total area (bone area + fat area + muscle area) Step.
추출된 영상에서 뼈, 지방 및 근육의 비율을 산출하는 단계(S300)에 대해서 이를 구현하는 화면의 예시도인 도 6을 참조하여 설명하면, 도 6은 추출된 영상에서 200 내지 900 HU(Hounsfield Unit)의 감쇠 값에 해당하는 뼈영역을 조도 값으로 찾아 폐곡선으로 표시하고, -30 내지 -190 HU(Hounsfield Unit)의 감쇠 값에 해당하는 지방영역을 조도 값으로 찾아 폐곡선으로 표시하며, 30 내지 70 HU(Hounsfield Unit)의 감쇠 값에 해당하는 근육영역 조도 값으로 찾아 폐곡선으로 표시한 모습을 도시한다. 상기와 같이 각 영역을 폐곡선으로 표시한 후, 영역이 차지하는 면적을 산출하고 전체 면적(뼈면적 + 지방면적 + 근육면적)을 기준으로 각 영역의 차지하는 비율을 구한다.The step (S300) of calculating the ratio of bone, fat, and muscle in the extracted image will be described with reference to FIG. 6, which is an exemplary view of a screen for implementing the same, and FIG. 6 shows 200 to 900 HUs in the extracted image. Find the bone area corresponding to the attenuation value of) as a roughness value and display it as a closed curve, and find the fat area corresponding to the attenuation value of -30 to -190 HU (Hounsfield Unit) as the intensity value and display it as a closed curve, 30 to 70 The figure shows the muscle area illuminance value corresponding to the attenuation value of the Hounsfield Unit (HU) and indicated by the closed curve. After displaying each area with a closed curve as described above, the area occupied by the area is calculated and the ratio of each area is calculated based on the total area (bone area + fat area + muscle area).
도 4는 본 발명의 다른 실시예에 따른 건강상태 분석 및 건강상태 정보 제공 방법 중 뼈, 지방 및 근육의 비율을 산출하는 방법을 도시하는 순서도이다. 추출된 영상에서 뼈, 지방 및 근육의 비율을 산출하는 단계(S300)는 건강 상태를 파악하기 위해 뼈, 지방 및 근육의 부피 비율을 산출하는 단계로, 뼈부피를 산출하는 단계(S311), 지방부피를 산출하는 단계(S312), 근육부피를 산출하는 단계(S313) 및 전체 부피(뼈부피 + 지방부피 + 근육부피) 중 각 부피의 비율을 출산하는 단계(S314)를 포함한다. 이때, 뼈, 지방 및 근육의 부피 비율을 산출하기 위해서는 촬영 영상을 수신하는 단계(S100)에서 검사 대상자의 신체를 정면, 측면, 상면에서 촬영한 복수의 촬영 영상을 수신해야만 한다.4 is a flowchart illustrating a method of calculating a ratio of bone, fat, and muscle in a health state analysis and health state information providing method according to another exemplary embodiment of the present invention. Calculating the ratio of bone, fat and muscle in the extracted image (S300) is a step of calculating the volume ratio of bone, fat and muscle to determine the health state, calculating the bone volume (S311), fat Comprising a step of calculating the volume (S312), a step of calculating the muscle volume (S313) and the step of giving a ratio of each volume of the total volume (bone volume + fat volume + muscle volume) (S314). In this case, in order to calculate the volume ratio of bone, fat, and muscle, a plurality of captured images taken from the front, side, and top of the body of the test subject must be received in step S100 of receiving the captured image.
추출된 영상에서 뼈부피를 산출하는 단계는 각 촬영 영상에서 뼈에 해당하는 감쇠 값인 200 내지 900 HU(Hounsfield Unit)에 해당하는 영역을 조도 값으로 찾아 구분하고, 각 촬영 영상의 뼈영역을 합산하여 뼈의 부피를 산출하는 단계이다. The step of calculating the bone volume from the extracted image is to find and classify the area corresponding to the attenuation value 200 to 900 HU (Hounsfield Unit), which is the attenuation value corresponding to the bone, in each photographed image, and to sum the bone regions of each photographed image. Calculate the bone volume.
지방부피를 산출하는 단계(S312)는 각 촬영 영상에서 지방에 해당하는 감쇠 값인 -30 내지 -190 HU(Hounsfield Unit)에 해당하는 영역을 조도 값으로 찾아 구분하고, 각 촬영 영상의 지방영역을 합산하여 지방의 부피를 산출하는 단계이다. In calculating the fat volume (S312), the area corresponding to the attenuation value -30 to -190 HU (Hounsfield Unit) corresponding to the fat in each photographed image is found by dividing the illumination value, and the fat region of each photographed image is summed. It is a step of calculating the volume of fat.
근육부피를 산출하는 단계(S313)는 각 촬영 영상에서 근육에 해당하는 감쇠 값인 30 내지 70 HU(Hounsfield Unit)에 해당하는 영역을 조도 값으로 찾아 구분하고, 각 촬영 영상의 근육영역을 합산하여 근육의 부피를 산출하는 단계이다.In calculating the muscle volume (S313), the area corresponding to the attenuation value 30 to 70 HU (Hounsfield Unit) corresponding to the muscle in each photographed image is found by dividing the illuminance value, and the muscle area of each photographed image is added to the muscle. Calculating the volume of.
전체 부피 중 각 부피의 비율을 산출하는 단계(S314)는 상기 S311 내지 S313 단계에서 계산된 뼈, 지방 및 근육 각각의 부피가 전체 부피(뼈부피 + 지방부피 + 근육부피)에서 차지하는 비율을 계산하는 단계이다.Calculating the ratio of each volume of the total volume (S314) is to calculate the ratio of the volume of each of the bones, fats and muscles calculated in the steps S311 to S313 in the total volume (bone volume + fat volume + muscle volume) Step.
추출된 영상에서 뼈, 지방 및 근육의 비율을 산출하는 단계(S300)에 대해서 이를 구현하는 화면의 예시도인 도 7을 참조하여 설명하면, 먼저 뼈의 부피를 계산하기 위해서는 검사 대상자의 신체를 전면, 측면 및 상면에서 촬영한 영상을 수신해야 한다. 도 7의 (a)는 검사 대상자의 신체를 상면에서 촬영한 영상, (b)는 검사 대상자의 신체를 정면에서 촬영한 영상, (C)는 검사 대상자의 신체를 측면에서 촬영한 영상이다. Calculating the ratio of bone, fat and muscle in the extracted image (S300) will be described with reference to FIG. 7 which is an exemplary view of a screen for implementing the same. On the other hand, the images taken from the side and the top should be received. 7 (a) is an image of the body of the test subject taken from the upper surface, (b) is an image of the body of the test subject taken from the front, (C) is an image of the body of the test subject taken from the side.
도 7과 같이 4개의 요추(14, 15, 16, 17)에 대해서 검사를 진행하고자 하는 경우 정면과 측면에서 촬영한 영상은 한 번의 촬영으로 4개의 요추(14, 15, 16, 17)가 포함될 수 있지만 상면에서 촬영한 영상의 경우에는 제1요추(14)에 의해 제2요추(15) 내지 제4요추(17)가 가려져 하나의 영상에 하나의 요추만 포함될 수 있기 때문에, 각 요추마다 따로 촬영된 영상을 얻어야 한다. 도 7은 정면, 측면 및 상면에서 검사 대상자의 신체를 촬영하고 제1요추(14) 내지 제4 요추(17)에 대해 추출된 영상과, 모든 추출 영상에서 뼈에 해당하는 감쇠 값인 200 내지 900 HU(Hounsfield Unit)의 해당하는 뼈영역을 조도 값으로 찾아 폐곡선으로 표시한 모습을 도시한다. 상기와 같이 모든 추출영상에서 각 영역을 폐곡선으로 표시한 후, 표시된 영역을 합산하여 뼈의 부피를 산출한다. 이후, 근육 및 지방에 대해서도 그에 해당하는 조도값으로 찾아 폐곡선으로 표시하고 표시된 영역을 합산하여 각각의 부피를 산출하며, 전체 부피(뼈부피 + 지방부피 + 근육부피)를 기준으로 각 영역이 차지하는 비율을 구한다.As shown in FIG. 7, when the examination is to be performed on the four lumbar vertebrae 14, 15, 16, and 17, the images taken from the front and side surfaces include four lumbar vertebrae 14, 15, 16, and 17 in one shot. However, in the case of an image taken from the upper surface, since the second lumbar spine 15 to the fourth lumbar spine 17 are covered by the first lumbar spine 14, only one lumbar spine may be included in one image, so that each lumbar spine is separately. You need to get a video. 7 is an image of the subject's body taken from the front, side, and top surface and extracted from the first lumbar spine 14 to the fourth lumbar spine 17, and attenuation values corresponding to bones in all extracted images are 200 to 900 HU. The figure shows the bone area of the Hounsfield Unit with the roughness value and displayed as a closed curve. As described above, each area is displayed as a closed curve in all the extracted images, and then the displayed areas are summed to calculate the bone volume. Afterwards, the muscles and fats are searched for corresponding illuminance values and displayed as closed curves, and the displayed areas are summed to calculate the respective volume, and the proportion of each area based on the total volume (bone volume + fat volume + muscle volume). Obtain
뼈, 근육 및 지방의 비율을 계산하는 단계(S300)가 완료되면, 비율에 따른 건강상태 정보가 저장된 진단테이블로부터 산출된 비율에 대한 건강상태 정보를 추출하여 표시하는 단계(S400)를 진행한다. 상기 건강상태 정보를 추출하여 표시하는 단계(S400)는 상기 비율을 계산하는 단계(S300)에서 산출되 뼈, 지방 및 근육의 비율을 가지고 건강상태를 판단하는 단계로, 뼈, 지방 및 근육의 비율에 따른 건강상태 정보가 저장된 진단테이블에서 산출된 비율에 따른 건강상태 정보만을 추출하여 표시한다. 본 발명의 실시예에 따라 건강상태 정보는 점수화해서 검사 대상자에게 제공될 수 있다. When the step (S300) of calculating the ratio of bone, muscle, and fat is completed, step (S400) of extracting and displaying health state information on the ratio calculated from the diagnosis table in which health state information according to the ratio is stored is performed. Extracting and displaying the health state information (S400) is a step of determining a health state with a ratio of bones, fats and muscles calculated in the step (S300), and the ratio of bones, fats and muscles. Extracts and displays only the health status information according to the ratio calculated from the diagnosis table in which the health status information is stored. According to the exemplary embodiment of the present invention, the health state information may be provided to the test subject by scoring.
본 발명의 건강상태 분석 및 건강상태 정보 제공 방법을 이용하면, 실제로 체내에 분포되어 있는 뼈, 지방 및 근육의 차지하는 비율로 건강상태를 진단할 수 있어, 종래의 기술보다 진단의 정확도가 향상된다.By using the health state analysis and the health state information providing method of the present invention, it is possible to diagnose the state of health at the proportion of bones, fats, and muscles that are actually distributed in the body, thereby improving the accuracy of diagnosis compared to the prior art.
한편, 본 명세서와 도면에 개시된 본 발명의 실시예들은 본 발명의 기술 내용을 쉽게 설명하고 본 발명의 이해를 돕기 위해 특정 예를 제시한 것일 뿐이며, 본 발명의 범위를 한정하고자 하는 것은 아니다. 여기에 개시된 실시예들 이외에도 본 발명의 기술적 사상에 바탕을 둔 다른 변형예들이 실시 가능하다는 것은 본 발명이 속하는 기술 분야에서 통상의 지식을 가진 자에게 자명한 것이다.On the other hand, the embodiments of the present invention disclosed in the specification and drawings are merely presented specific examples to easily explain the technical contents of the present invention and help the understanding of the present invention, and are not intended to limit the scope of the present invention. It will be apparent to those skilled in the art that other modifications based on the technical idea of the present invention can be carried out in addition to the embodiments disclosed herein.

Claims (10)

  1. 신체의 촬영 영상을 수신하는 단계;Receiving a captured image of the body;
    상기 촬영 영상에서 특정 신체부위에 대한 영상을 추출하는 단계;Extracting an image of a specific body part from the captured image;
    상기 추출된 영상에서 뼈, 지방 및 근육의 비율을 산출하는 단계; 및Calculating a ratio of bone, fat and muscle in the extracted image; And
    비율에 따른 건강상태 정보가 저장된 진단 테이블로부터 상기 산출된 비율에 대한 건강상태 정보를 추출하여 표시하는 단계;를 포함하는 것을 특징으로 하는 영상촬영 기반의 건강상태 분석 및 건강상태 정보 제공 방법.And extracting and displaying health state information on the calculated ratio from a diagnosis table in which health state information according to a ratio is stored.
  2. 제1항에 있어서,The method of claim 1,
    상기 촬영 영상을 수신하는 단계;는 Receiving the captured image;
    CT(Computed Tomography), MRI(Magnetic Resonance Image) 또는 엑스선(X-Ray)으로부터 촬영된 촬영 영상을 수신하는 단계인 것을 특징으로 하는 영상촬영 기반의 건강상태 분석 및 건강상태 정보 제공 방법.Imaging-based health status analysis and health information providing method comprising the step of receiving a photographed image taken from a CT (Computed Tomography), MRI (Magnetic Resonance Image) or X-ray (X-Ray).
  3. 제1항에 있어서,The method of claim 1,
    상기 영상을 추출하는 단계;는Extracting the image;
    상기 촬영 영상을 기저장된 특정 신체부위 영상의 특정 기준점에 일치시키는 단계;Matching the captured image to a specific reference point of a previously stored specific body part image;
    상기 촬영 영상에 표시된 신체 외곽부가 상기 특정 신체부위 영상에 표시된 신체 외곽부와 일치하도록 촬영 영상을 리사이징(resizing) 하는 단계; 및 Resizing the captured image such that the body outline displayed on the captured image matches the body outline displayed on the specific body image; And
    상기 촬영 영상 중 상기 특정 신체부위 영상과 중첩된 영역의 영상을 추출하는 단계;를 포함하는 것을 특징으로 하는 영상촬영 기반의 건강상태 분석 및 건강상태 정보 제공 방법.And extracting an image of a region overlapping with the specific body part image of the photographed image.
  4. 제3항에 있어서,The method of claim 3,
    상기 기저장된 특정 신체부위 영상은The pre-stored specific body part image
    특정 신체부위의 최상단을 상한선으로 규정하고 최하단을 하한선으로 규정하며, 상기 상한선과 상기 하한선을 이은 직사각형 형태의 표준화 영상인 것을 특징으로 하는 영상촬영 기반의 건강상태 분석 및 건강상태 정보 제공 방법.Imaging-based health state analysis and health state information providing method, characterized in that the uppermost end of a specific body part is defined as the upper limit and the lowermost end is the lower limit, and the upper limit and the lower limit are standardized images.
  5. 제1항에 있어서,The method of claim 1,
    상기 영상을 추출하는 단계; 이후,Extracting the image; after,
    추출된 영상에서 분석대상 영역을 지정하는 단계;를 더 포함하는 것을 특징으로 하는 영상촬영 기반의 건강상태 분석 및 건강상태 정보 제공 방법.Specifying an analysis target region in the extracted image; imaging method based health status analysis and health status information providing method further comprising a.
  6. 제1항에 있어서,The method of claim 1,
    상기 촬영 영상을 수신하는 단계;는 Receiving the captured image;
    사용자의 신체를 정면에서 촬영한 영상을 수신하는 단계;인 것을 특징으로 하는 영상촬영 기반의 건강상태 분석 및 건강상태 정보 제공 방법.Receiving an image of the user's body taken from the front; Image-based health status analysis and health status information providing method comprising the.
  7. 제6항에 있어서,The method of claim 6,
    상기 추출된 영상에서 뼈, 지방 및 근육의 비율을 산출하는 단계;는Calculating a ratio of bone, fat and muscle in the extracted image;
    뼈, 지방 및 근육에 해당하는 감쇠 값으로 각 영역을 검출하여 면적을 계산하는 단계; 및 Calculating an area by detecting each area with an attenuation value corresponding to bone, fat, and muscle; And
    각 면적의 비율을 산출하는 단계;를 포함하는 것을 특징으로 하는 영상촬영 기반의 건강상태 분석 및 건강상태 정보 제공 방법.Comprising a step of calculating the ratio of each area; imaging method based health status analysis and health status information providing method comprising a.
  8. 제1항에 있어서,The method of claim 1,
    상기 촬영 영상을 수신하는 단계;는Receiving the captured image;
    사용자의 신체를 정면, 측면, 상면에서 촬영한 영상을 수신하는 단계;인 것을 특징으로 하는 영상촬영 기반의 건강상태 분석 및 건강상태 정보 제공 방법.Receiving an image taken from the front, side, top of the user's body; Image-based health status analysis and health status information providing method comprising the.
  9. 제8항에 있어서,The method of claim 8,
    상기 추출된 영상에서 뼈, 지방 및 근육의 비율을 산출하는 단계;는Calculating a ratio of bone, fat and muscle in the extracted image;
    뼈, 지방 및 근육에 해당하는 감쇠 값으로 각 영역을 검출하여 부피를 계산하는 단계; 및Calculating the volume by detecting each region with an attenuation value corresponding to bone, fat and muscle; And
    각 부피의 비율을 산출하는 단계;를 포함하는 것을 특징으로 하는 영상촬영 기반의 건강상태 분석 및 건강상태 정보 제공 방법.Comprising a step of calculating the ratio of each volume; imaging method based on health analysis and health state information providing method comprising a.
  10. 제1항에 있어서,The method of claim 1,
    상기 건강상태 정보를 추출하여 표시하는 단계;는Extracting and displaying the health state information;
    건강상태 정보를 점수로 환산하여 표시하는 단계;인 것을 특징으로 하는 영상촬영 기반의 건강상태 분석 및 건강상태 정보 제공 방법.And converting the health status information into scores and displaying the converted health status information.
PCT/KR2017/006478 2016-06-21 2017-06-20 Method for analyzing health condition on basis of image photographing and providing health condition information WO2017222283A1 (en)

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Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN109512449A (en) * 2018-09-26 2019-03-26 沈阳东软医疗***有限公司 Physiological parameter output method and device
US11182920B2 (en) * 2018-04-26 2021-11-23 Jerry NAM Automated determination of muscle mass from images

Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
KR20030018792A (en) * 2001-08-31 2003-03-06 버츄얼아이테크 주식회사 A medical image processing system and the method thereof
KR20030081340A (en) * 2000-11-29 2003-10-17 가부시키가이샤 아트헤븐나인 Method and device for measuring body compositions
JP2008142532A (en) * 2007-11-14 2008-06-26 Hitachi Medical Corp Medical image diagnosis support system
KR20140144645A (en) * 2013-06-11 2014-12-19 삼성전자주식회사 The method and apparatus otaining a image related to region of interest of a target object
JP2015142619A (en) * 2014-01-31 2015-08-06 セイコーエプソン株式会社 Processing system, ultrasonic measurement apparatus, program and ultrasonic measurement method

Patent Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
KR20030081340A (en) * 2000-11-29 2003-10-17 가부시키가이샤 아트헤븐나인 Method and device for measuring body compositions
KR20030018792A (en) * 2001-08-31 2003-03-06 버츄얼아이테크 주식회사 A medical image processing system and the method thereof
JP2008142532A (en) * 2007-11-14 2008-06-26 Hitachi Medical Corp Medical image diagnosis support system
KR20140144645A (en) * 2013-06-11 2014-12-19 삼성전자주식회사 The method and apparatus otaining a image related to region of interest of a target object
JP2015142619A (en) * 2014-01-31 2015-08-06 セイコーエプソン株式会社 Processing system, ultrasonic measurement apparatus, program and ultrasonic measurement method

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US11182920B2 (en) * 2018-04-26 2021-11-23 Jerry NAM Automated determination of muscle mass from images
CN109512449A (en) * 2018-09-26 2019-03-26 沈阳东软医疗***有限公司 Physiological parameter output method and device

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