KR20170060701A - Estimation method of spine position from 3-dimensional human body image - Google Patents

Estimation method of spine position from 3-dimensional human body image Download PDF

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KR20170060701A
KR20170060701A KR1020150165169A KR20150165169A KR20170060701A KR 20170060701 A KR20170060701 A KR 20170060701A KR 1020150165169 A KR1020150165169 A KR 1020150165169A KR 20150165169 A KR20150165169 A KR 20150165169A KR 20170060701 A KR20170060701 A KR 20170060701A
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point
back surface
ridge
ridge point
vertebra
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KR101908767B1 (en
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조창석
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한신대학교 산학협력단
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    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B6/00—Apparatus for radiation diagnosis, e.g. combined with radiation therapy equipment
    • A61B6/50—Clinical applications
    • A61B6/505—Clinical applications involving diagnosis of bone
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/103—Detecting, measuring or recording devices for testing the shape, pattern, colour, size or movement of the body or parts thereof, for diagnostic purposes
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B6/00—Apparatus for radiation diagnosis, e.g. combined with radiation therapy equipment
    • A61B6/46—Apparatus for radiation diagnosis, e.g. combined with radiation therapy equipment with special arrangements for interfacing with the operator or the patient
    • A61B6/461—Displaying means of special interest
    • A61B6/466—Displaying means of special interest adapted to display 3D data
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B6/00—Apparatus for radiation diagnosis, e.g. combined with radiation therapy equipment
    • A61B6/52—Devices using data or image processing specially adapted for radiation diagnosis
    • A61B6/5211—Devices using data or image processing specially adapted for radiation diagnosis involving processing of medical diagnostic data
    • A61B6/5217—Devices using data or image processing specially adapted for radiation diagnosis involving processing of medical diagnostic data extracting a diagnostic or physiological parameter from medical diagnostic data

Abstract

A method for estimating a position of a vertebrae includes the steps of: (a) detecting a left ridge point and a right ridge point of the back surface from a human body image including a back surface; (b) searching for a point having the same height between the left ridge point and the right ridge point and the lower ridge point of the left ridge point and the right ridge point detected in the step (a); And (c) detecting a point having a lowest height between a point having a lower height of the left ridge point and the right ridge point and a point having the same height detected in the step (b).

Description

TECHNICAL FIELD [0001] The present invention relates to a method of estimating a position of a spine from a three-dimensional human body image,

The present invention relates to a method of estimating the position of a vertebra, and more particularly to a method of estimating a position of a vertebra from a human body image including a back surface such as a CT (Computer Tomography) image.

Korean Patent No. 1124144 (Spinal Deformation Measurement System, Feb. 28, 2012) discloses a system for measuring deformation of a vertebra using an x-ray image.

However, when using x-ray images to measure the spine, it is not only inconvenient because the radiation exposure caused by the x-rays increases, but also when radiographs are taken, it is necessary to arrange the radiologist and get permission to handle hazardous materials management.

The present invention provides a method for easily estimating the position of a vertebra from a human body image including a back surface such as a CT (Computer Tomography) image, which aims at solving the technical problems as described above It has its purpose.

A method of estimating a position of a vertebra of the present invention includes the steps of: (a) detecting a left ridge point and a right ridge point of the back surface from a human body image including a back surface; (b) searching for a point having the same height between the left ridge point and the right ridge point and the lower ridge point of the left ridge point and the right ridge point detected in the step (a); And (c) detecting a point having a lowest height between a point having a lower height of the left ridge point and the right ridge point and a point having the same height detected in the step (b).

According to another aspect of the present invention, there is provided a method for estimating a position of a vertebra, wherein when a point having the lowest height is represented by one point in the step (c), the point is estimated as a back surface point corresponding to an upper portion of the position of the vertebra , And when the point having the lowest height is represented as a section in the step (c), it is preferable to estimate the median value of the section as the surface point of the back corresponding to the upper portion of the vertebra.

Further, the method of estimating the position of the vertebra of the present invention further includes connecting a plurality of back surface points corresponding to the upper portion of the vertebra estimated from the plurality of human images including the back surface . Preferably, a point at a distance from the back surface point corresponding to the upper portion of the estimated vertebra position to the body direction is estimated as the projection position of the vertebra.

The method of estimating the position of the vertebra according to the present invention further comprises the steps of: (d) in the step (b), calculating a position between the left ridge point and the right ridge point and between the left ridge point and the right ridge point, Or a distance between a point having a lower height of the left ridge point and the right ridge point and a point having the same height between the left ridge point and the right ridge point is If less than a predetermined distance, rotating the back surface; And (e) detecting a point having the smallest height between the left ridge point and the right ridge point.

The step (d) is characterized by rotating the back surface so that the left ridge point and the right ridge point have the same height.

According to another aspect of the present invention, there is provided a method of estimating a position of a vertebra, wherein when a point having the lowest height is represented by one point in the step (e), the point is estimated as a back surface point corresponding to an upper portion of the position of the vertebra And estimating a median of the interval as a surface point corresponding to an upper portion of the spinal column when the point having the lowest height is represented as a section in the step (e).

Preferably, each of the left ridge point and the right ridge point is one of a point where the change of the curvature in the pixel of the human image is inclined toward both sides. The method of estimating the position of the vertebrae according to the present invention is characterized in that when there are a plurality of points where the change of the curvature in both sides of the pixel of the human image is inclined toward the left or right from the center of the human image, Is selected as the left ridge point or the right ridge point.

According to the method of estimating the position of the spine from the three-dimensional human body image of the present invention, the position of the spine can be easily estimated from a human body image including a back surface such as a CT (Computer Tomography) image.

BRIEF DESCRIPTION OF THE DRAWINGS FIG. 1 is a flowchart of a method for estimating the position of a vertebra from a three-dimensional human body image of the present invention. FIG.
FIG. 2 is an explanatory diagram of a method of searching a spinal position using a virtual water droplet on a human body image including a back surface. FIG.
Fig. 3 is an example of detection of the left side ridge point and the right side ridge point of the back surface; Fig.
Fig. 4 is an example in which a left ridge point and a right ridge point of a valley are searched for a water depth determination; Fig.
Figure 5 is an example of implementing a water filled valley by allowing imaginary water to flow on various back surface information.
6 is an explanatory view showing the position of a surface, such as the presence of a vertebra;
7 is an exemplary view of rotating the back surface.
8 is a result of the spinal locus estimation based on the X-ray photograph of the back and the imaginary set of water of the present invention.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS Hereinafter, a method for estimating a position of a vertebra from a three-dimensional human body image according to an embodiment of the present invention will be described in detail with reference to the accompanying drawings.

It should be understood that the following embodiments of the present invention are only for embodying the present invention and do not limit or limit the scope of the present invention. It will be understood by those of ordinary skill in the art that various changes in form and details may be made therein without departing from the spirit and scope of the invention as defined by the appended claims.

The method of estimating the position of the vertebra from the three-dimensional human body image of the present invention can be implemented using a CT (Computer Tomography) sectional image including a plurality of back surface images captured and stored in advance. That is, a method of estimating the position of a spine from a three-dimensional human body image of the present invention includes storing a CT sectional image on a storage medium such as a memory or a hard disk, and storing a software program including the algorithm of the present invention, By means of a processor included in the system, to analyze the stored images.

First, FIG. 1 shows a flow chart of a method of estimating the position of a vertebra from a three-dimensional human body image of the present invention.

As can be seen from Fig. 1, the method of estimating the position of the vertebrae comprises the steps of (S10) detecting the left side ridge point and the right side ridge point of the back surface from the human body image including the back surface, As a result of the comparison of the heights of the left side ridge point and the right side ridge point (S20) and the comparison result of the step S20, the height of the left ridge point and the right side ridge point are the same between the lower ridge point and the left ridge point and the right ridge point And searching for a point (S30). Here, the point having the same height between the left side ridge point and the right side ridge point is a point having the same height as the left side ridge point and the right side ridge point, And reaches a point having the same height.

In addition, the method of estimating the position of the vertebra of the present invention is characterized in that, in step S30, a point having the same height between the left ridge point and the right ridge point and the left ridge point and the right ridge point is not searched , A step S40 of rotating the back surface and a point having the lowest height between the point having the same height as that found at the step S30 and the point having the low height of the left side ridge point and the right side point are detected, And a step (S50) of detecting a point having the lowest height between the left and the right ridge points of the step.

Further, the step S40 is characterized in that the left and right ridgelines are rotated at the same height so as to have the same height.

However, in step S40, depending on the setting, the condition is set to 'when a point having the same height between the left ridge point and the right ridge point and the left ridge point and the right ridge point is not detected But the point between the left and the right ridge point and the point between the left ridge point and the right ridge point are found and the distance between the point having the same height as the lower ridge point is If less than a certain distance, it may be set to rotate the back surface. A case where a point having the same height of the ridge line is not searched, and a case where a distance between a point having the same height as a point having a low height and a point having the same height is less than a certain distance,

In addition, in the method of estimating the position of the vertebra of the present invention, when the point having the lowest height appears as one point in step S50, the point is estimated as the back surface point corresponding to the upper part of the position of the vertebra. In addition, when a point having the lowest height appears as a section, that is, a plurality of connected pixels, it is preferable to estimate the median value of the section as a surface point corresponding to the upper portion of the spinal column.

The method of estimating the position of the vertebra of the present invention includes the steps of connecting a plurality of back surface points corresponding to the upper portion of the vertebrae estimated from the plurality of human body images including the back surface, (S60). Finally, the method of estimating the position of the vertebra of the present invention estimates the position of the vertebrae as a position at a distance from the back surface point to the body direction corresponding to the upper portion of the estimated vertebra position.

The method for estimating the position of the vertebra of the present invention described above will be described in more detail below.

Basic background: Virtual droplet set method

2 is an explanatory diagram of a method of searching for a spinal position using a virtual water droplet on a human body image including a back surface.

Fig. 2 is a cross-sectional CT CT image of a prone person showing the position of the vertebra and the back surface, with the back surface facing upward. In order to estimate the position of the vertebrae, imaginary water is poured on the surface of the 3D measurement, and the inside of the vertebral column can be estimated as the position of the vertebra at a distance from the surface of the virtual water to the body. This method is based on the theory of orthopedics that the position of the vertebrae forms a valley on the back surface of everyone, and this assumption was confirmed in experiments on CT section images.

The upper part of Fig. 2 is a schematic representation of pouring imaginary water on the back. Of course, the water here is a numerical value of the mass '1' loaded per pixel, which moves along the gradient on the same principle as the water droplet. When imaginary water droplets fall on the back surface (in pixel units), the left and right side edges of the surface flow down to both sides along the slope, and the water drops falling to the center converge into the valley where the spine of the back surface is located. The collection of water droplets means that the value of mass '1' is accumulated.

S10  step

Fig. 3 shows an example of detection of the left side ridge point and the right side ridge point of the back surface.

As can be seen from Fig. 3, the left side ridge point and the right side ridge point of the back surface refer to the left side and right side hills forming valleys on the back surface, respectively. These points are very important to keep virtual water in the valley, and have information to calculate the twist angle of the body. The point of the ridge corresponds to the peak in terms of the signal and therefore has the characteristic of the peak seen in the signal. Using these properties, the curvature on each pixel is calculated, and the point where the change of the curvature shows both slopes becomes the left ridge point and the right ridge point. That is, each of the left ridge point and the right ridge point is one of the points where the change of the curvature in the pixel of the human image is inclined toward both sides. However, in order to detect the left side ridge point and the right side ridge point, it is preferable to search only the range within each constant value at the center of the corresponding image. An example of searching only within a predetermined value from the center of the corresponding image, that is, the back surface measurement data, is to set the search target area from the center pixel so that the number of horizontal pixels in the search subject area is 20% of the whole image. This is possible because the spine is in the center of the back. Two points that satisfy these conditions are found, and the left side point and the right side point from the center of the back surface measurement data are defined as the left side ridge point and the right side ridge point, respectively.

Equation (1) is a condition for searching the left and right ridge points.

Figure pat00001

C (Pt): Curvature with respect to point P on the t position

δ: Adjustment value of curvature (according to clinical trial value)

Ψm, Ψ △: the like refers to the center (m), positions (△) away from the center on the surface (depending on the clinical trial)

∩: enemy set

In addition, when a large number of points are detected under the same conditions in the search process of the left and right ridgeline points, a point near the center of the back surface is defined as a left ridge point and a right ridge point respectively. That is, when there are many points where the change of the curvature on both sides of the human image pixel is inclined toward the left or right from the center of the human image, a point near the center of the human image is selected as the left side ridge point or the right side ridge point do. The surface position where the spine is present is defined as the deepest water depth between the two detected points.

Step S20, Step S30, and Step S50

When the imaginary water flows on the back, the water will be poured into the sloping valley, and it will flow down to both sides. When you find the deepest part of the valley, it becomes the part where the spine is present.

FIG. 4 is a diagram for explaining the left side ridge point and the right side ridge point of the valley for the water depth determination.

The left side ridge point A and the right side ridge point B in Fig. 4 have respective heights. The height of the two points A and B is compared, and the lower ridge point is the limit water height at which the water can be maximized. If the ridge ridges have the same height, the water will become the same height. In Fig. 4, the dotted line of arrow C represents the section of the valley, and the dotted line of D represents the limit water surface height at which water can run out. When the water flows down to the back surface, the water reaches the maximum limit water in the section, and the valley is filled with imaginary water. Equation (2) finds a point having the maximum depth.

Ψ A , Ψ B : Display of the back surface section of the left ridge point (A) and the right ridge point (B)

Pt: One point on t point within the ridge point section

D (Pt): Depth value of imaginary water on point

MAX: means maximum value

The point having the maximum depth of water means a point having the same height between the left ridge point and the right ridge point and the lower ridge point and the left ridge point and the right ridge point.

FIG. 5 is an exemplary view illustrating the implementation of water filled valleys by allowing imaginary water to flow on various back surface information.

The number of pixels is accumulated from the back surface to the maximum water depth in order to compare the water depth, and the position where the number of accumulated pixels becomes the maximum value becomes the maximum water depth.

6 is an explanatory view showing the position of the surface, such as the presence of a vertebra.

As can be seen from Fig. 6, the maximum depth at the back surface may appear as a section. The data presented as the interval estimate the median value of the interval as the surface point of the back corresponding to the position of the spine.

Step S40

If the surface of the back is severe and imaginary water does not settle on the valley of the back surface, the rotation angle is calculated using the ridge points on both sides of the back surface, and then the rotation is performed to fill the virtual water to obtain the spine position. Back. That is, in step S30, it is necessary to rotate the back surface when a point having the same height between the left ridge point and the right ridge point and between the left ridge point and the right ridge point is not found.

Figure 7 shows an example of rotating the back surface.

That is, FIG. 7 shows a method of applying a virtual water collection method by rotating a twisted surface. In Fig. 7, &thetas; is the surface rotation angle and is a vector passing through the left side ridge point and the right side ridge point of the back surface

Figure pat00003
And the vector passing through the highest ridge point
Figure pat00004
The internal formula of θ is computed. [Equation 3] is a calculation formula of the rotation angle [theta].

Figure pat00005

S60  step

The method of estimating the position of the vertebra of the present invention connects a place where the depth of the valley of the back surface is the deepest, and estimates the position of the vertebra below the predetermined height of the surface such as the deepest place. For example, assuming the position of the backbone 1cm below the back surface is the main purpose of vertebral position estimation, calculating the lateral inclinations of the vertebrae (left and right bending), song bending, and distortion (distortion) Can be achieved with the position setting of < RTI ID = 0.0 > 0. < / RTI >

FIG. 8 shows the result of spine position estimation by the X-ray photograph of the back and the imaginary set search method of the present invention.

As described above, according to the method of estimating the position of the spine from the three-dimensional human body image of the present invention, the position of the spine can be easily estimated from the human body image including the back surface such as CT (Computer Tomography) Able to know.

Claims (13)

(a) detecting a left ridge point and a right ridge point of the back surface from a human body image including a back surface; And
(b) searching for a point having the same height between the left ridge point and the right ridge point and the lower ridge point of the left ridge point and the right ridge point detected in the step (a) A method of estimating the position of a vertebra. The method according to claim 1,
A method of estimating a position of the vertebra,
(c) detecting a point having the lowest height between a point having a lower height of the left ridge point and the right ridge point and a point having the same height retrieved in the step (b) To estimate the position of the vertebra. 3. The method of claim 2,
If the point having the lowest height is represented by one point in the step (c), the corresponding point is estimated as the back surface point corresponding to the upper part of the position of the vertebra,
Wherein, in the step (c), when a point having the lowest height appears as a section, the median value of the section is estimated as a back surface point corresponding to the upper portion of the vertebra. The method of claim 3,
And connecting a plurality of back surface points corresponding to an upper portion of the vertebral position estimated from the plurality of human images including the back surface. ≪ Desc / Clms Page number 13 > The method of claim 3,
And estimating a position of the vertebrae at a position spaced a certain distance from the back surface point corresponding to the upper portion of the estimated vertebra position to the body direction. The method according to claim 1,
A method of estimating a position of the vertebra,
(d) if, in the step (b), a point having the same height between the left ridge point and the right ridge point and the left ridge point and the right ridge point are not searched, Rotating the back surface if the distance between the lower ridge point of the left ridge point and the right ridge point and the point having the same height between the left ridge point and the right ridge point is less than a predetermined distance; ≪ / RTI > further comprising determining a position of the vertebrae. The method according to claim 6,
The step (d)
Wherein the back ridge point and the right ridge point are rotated at the same height so as to be at the same height. 8. The method of claim 7,
The method of estimating the position of the vertebrae may further comprise, after the step (d)
(e) detecting a point having the smallest height between the left ridge point and the right ridge point. 9. The method of claim 8,
In the step (e), when the point having the lowest height appears as one point, the corresponding point is estimated as the back surface point corresponding to the upper part of the position of the vertebra,
Wherein, in the step (e), when a point having the lowest height appears as a section, the median value of the section is estimated as a back surface point corresponding to an upper portion of the spinal column. 10. The method of claim 9,
And connecting a plurality of back surface points corresponding to an upper portion of the vertebral position estimated from the plurality of human images including the back surface. ≪ Desc / Clms Page number 13 > 10. The method of claim 9,
And estimating a position of the vertebrae at a position spaced a certain distance from the back surface point corresponding to the upper portion of the estimated vertebra position to the body direction. The method according to claim 1,
Wherein each of the left ridge point and the right ridge point is one of a point where the change of the curvature in the pixel of the human image shows a slope on both sides. 13. The method of claim 12,
When a plurality of points where the change of the curvature in the pixels of the human image are both inclined are present on the left side or the right side of the center of the human body image, a point near the center of the human body image is referred to as the left side ridge point or the right side ridge And a point is selected as the position of the vertebra.
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Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20060110017A1 (en) * 2004-11-25 2006-05-25 Chung Yuan Christian University Method for spinal disease diagnosis based on image analysis of unaligned transversal slices
JP2011160824A (en) * 2010-02-04 2011-08-25 Future Univ-Hakodate Spinal curvature determination support apparatus
US8423124B2 (en) * 2007-05-18 2013-04-16 Siemens Aktiengesellschaft Method and system for spine visualization in 3D medical images
KR101331043B1 (en) * 2012-03-08 2013-11-22 관동대학교산학협력단 System for diagnosing scoliosis and method for diagnosing scoliosis

Patent Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20060110017A1 (en) * 2004-11-25 2006-05-25 Chung Yuan Christian University Method for spinal disease diagnosis based on image analysis of unaligned transversal slices
US8423124B2 (en) * 2007-05-18 2013-04-16 Siemens Aktiengesellschaft Method and system for spine visualization in 3D medical images
JP2011160824A (en) * 2010-02-04 2011-08-25 Future Univ-Hakodate Spinal curvature determination support apparatus
KR101331043B1 (en) * 2012-03-08 2013-11-22 관동대학교산학협력단 System for diagnosing scoliosis and method for diagnosing scoliosis

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