KR101810289B1 - Medical image reading apparatus and method for operating medical image reading apparatus - Google Patents
Medical image reading apparatus and method for operating medical image reading apparatus Download PDFInfo
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- KR101810289B1 KR101810289B1 KR1020150065902A KR20150065902A KR101810289B1 KR 101810289 B1 KR101810289 B1 KR 101810289B1 KR 1020150065902 A KR1020150065902 A KR 1020150065902A KR 20150065902 A KR20150065902 A KR 20150065902A KR 101810289 B1 KR101810289 B1 KR 101810289B1
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- 238000000034 method Methods 0.000 title claims description 37
- 230000003902 lesion Effects 0.000 claims abstract description 203
- 238000011017 operating method Methods 0.000 claims abstract 3
- 210000000056 organ Anatomy 0.000 claims description 29
- 201000010099 disease Diseases 0.000 claims description 18
- 208000037265 diseases, disorders, signs and symptoms Diseases 0.000 claims description 18
- 230000008859 change Effects 0.000 claims description 9
- 230000007704 transition Effects 0.000 claims description 5
- 238000000926 separation method Methods 0.000 claims description 4
- 210000004556 brain Anatomy 0.000 description 28
- 238000010586 diagram Methods 0.000 description 16
- 230000002159 abnormal effect Effects 0.000 description 11
- 208000003906 hydrocephalus Diseases 0.000 description 10
- 208000032843 Hemorrhage Diseases 0.000 description 8
- 230000000740 bleeding effect Effects 0.000 description 5
- 238000009826 distribution Methods 0.000 description 5
- 210000005153 frontal cortex Anatomy 0.000 description 5
- 230000007774 longterm Effects 0.000 description 4
- 230000006870 function Effects 0.000 description 3
- 230000036541 health Effects 0.000 description 3
- 230000007170 pathology Effects 0.000 description 3
- 210000004885 white matter Anatomy 0.000 description 2
- 206010016717 Fistula Diseases 0.000 description 1
- 230000005856 abnormality Effects 0.000 description 1
- 230000003247 decreasing effect Effects 0.000 description 1
- 238000003745 diagnosis Methods 0.000 description 1
- 238000002059 diagnostic imaging Methods 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 230000003890 fistula Effects 0.000 description 1
- 210000001652 frontal lobe Anatomy 0.000 description 1
- 210000004884 grey matter Anatomy 0.000 description 1
- 230000002008 hemorrhagic effect Effects 0.000 description 1
- 230000004807 localization Effects 0.000 description 1
- 230000035772 mutation Effects 0.000 description 1
- 238000002610 neuroimaging Methods 0.000 description 1
- 230000003287 optical effect Effects 0.000 description 1
- 230000001575 pathological effect Effects 0.000 description 1
- 230000001225 therapeutic effect Effects 0.000 description 1
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- A61B6/00—Apparatus or devices for radiation diagnosis; Apparatus or devices for radiation diagnosis combined with radiation therapy equipment
- A61B6/46—Arrangements for interfacing with the operator or the patient
- A61B6/467—Arrangements for interfacing with the operator or the patient characterised by special input means
- A61B6/469—Arrangements for interfacing with the operator or the patient characterised by special input means for selecting a region of interest [ROI]
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Abstract
A medical image reading apparatus and a medical image reading apparatus operating method are disclosed. A medical image reading apparatus according to an embodiment of the present invention includes a determination unit for analyzing an input medical image to determine whether a lesion is included, and a determination unit for determining whether a lesion is included in the medical image, And a control unit for outputting code data generated by encoding the position as a result of the input.
Description
The present invention relates to a lesion localization technique using a variable triangular model, and more particularly, to a medical image reading apparatus and a medical image reading apparatus for automatically identifying a location of a lesion from a medical image (e.g., CT image) And a device operation method.
Currently, in-hospital medical information systems have large-scale storage of readout data (for example, brain imaging readouts) for medical images of patients, but usually readout data is written in the form of narrative data that is not coded.
In order to actually utilize such read data, a reader (e.g., a doctor in charge) must perform a task of finding code data corresponding to the read data over a complicated step, so that a lot of time, manpower, and cost are required, There is a problem that it is merely stored, but the utilization of the read data is remarkably deteriorated.
In addition, conventionally, a function of displaying and indexing a medical image of a patient selected from a patient list, a function of determining the length of a lesion in a medical image, and a function of outputting a report by formatting the read data coded by a reader Etc. have been developed and commercialized.
However, since there is no commercially available program that can automatically detect an anatomical location from a medical image and code an anatomical location, time and cost are incurred when a reader directly encodes a medical image, and in particular, In the case of medical images, the lesion is usually twisted, so it may be difficult to accurately locate the lesion.
Accordingly, there is a desperate need for an apparatus and a technique capable of automatically detecting a lesion from a medical image of a patient organs and coded the anatomical position of the lesion.
The embodiment of the present invention identifies the position of the lesion from the medical image and automatically outputs the coded data generated through coding when the medical image of the patient's organs is input so that the reader does not perform a complicated coding operation , And to easily obtain the code data related to the anatomical position of the lesion.
In addition, the embodiment of the present invention aims to allow a healthcare person to easily grasp the existence of a lesion and its anatomical position within a patient's organ by using only the code data.
It is also an object of the present invention to more accurately identify and code an anatomical location of a lesion based on a variable triangular model even for a medical image that includes a lesion in comparison with a normal state, do.
In addition, embodiments of the present invention can also be applied to a medical imaging system, such as the size, volume, shape, brightness, number and progress of a lesion identified through symmetrical comparison or numerical comparison of a plurality of triangles overlaid on the medical image based on a variable triangular model And to automatically code the medical information of the patient.
In addition, the embodiment of the present invention generates code data in a form that is relatively compact as compared with the conventional read-form data format and can be interpreted by an information terminal such as a computer, The purpose of this study is to improve the utilization of the results of analysis of medical images of patients in PHR (Personal Health Record System), clinical decision system and Big Data System.
A medical image reading apparatus according to an embodiment of the present invention includes a determination unit for analyzing an input medical image to determine whether a lesion is included, and a determination unit for determining whether a lesion is included in the medical image, And a control unit for outputting code data generated by encoding the position as a result of the input.
According to another aspect of the present invention, there is provided a method of operating a medical image reading apparatus, the method comprising: analyzing an input medical image to determine whether a lesion is included; And outputting the code data generated by coding the position as a result of the input.
According to an embodiment of the present invention, when a medical image of a patient's organs is input, the position of the lesion is identified from the medical image and the coded data generated through coding is automatically output so that the reader can perform a complicated coding operation It is possible to easily obtain the code data on the anatomical position of the lesion without performing it.
Also, according to the embodiment of the present invention, it is possible to allow the healthcare person to easily grasp the existence of the lesion and its anatomical position within the patient's organs by using only the code data.
According to an embodiment of the present invention, an anatomical location of a lesion can be more accurately identified and coded on the basis of a variable triangular model even for a medical image including a lesion and a long-term twisted compared to a normal state.
Also, according to an embodiment of the present invention, the size, volume, shape, brightness, number, and size of a lesion identified through a symmetrical comparison or numerical comparison of a plurality of triangles overlaid on the medical image based on a variable triangular model The medical information such as the progress degree can be automatically coded.
Further, according to the embodiment of the present invention, by generating code data in a form that is relatively compact compared to the conventional read-only data type and can be interpreted by an information terminal such as a computer, It is possible to more easily transmit the result of analyzing the medical image of the patient to the medical device, the personal health record system (PHR), the clinical decision system, and the big data system, thereby increasing the utilization.
1 is a block diagram illustrating an internal configuration of a medical image reading apparatus according to an embodiment of the present invention.
2 is a diagram showing an example of creating a virtual figure (triangle) in the input medical image based on the variable triangular model.
FIG. 3 is a diagram illustrating an example of determining the presence or absence of a lesion through a triangular symmetric comparison based on a variable triangular model. FIG.
FIG. 4 is a diagram illustrating an example of determining the presence or absence of a lesion by comparing the distribution of pixels having a predetermined brightness.
FIG. 5 is a diagram showing an example of identifying a position of a lesion by confirming a separation distance from a feature point forming a triangle.
6 is a diagram showing an example of identifying a tissue in which a lesion has occurred in an organ.
7 is a diagram showing an example of code data generated by coding the position of a lesion.
Fig. 8 is a diagram showing an example of coding medical information about the degree of progress of a lesion identified according to a change in the size of a triangle.
9 is a flowchart illustrating a procedure of a method of operating a medical image reading apparatus according to an embodiment of the present invention.
Hereinafter, an apparatus and method for updating an application program according to an embodiment of the present invention will be described in detail with reference to the accompanying drawings. However, the present invention is not limited to or limited by the embodiments. Like reference symbols in the drawings denote like elements.
1 is a block diagram illustrating an internal configuration of a medical image reading apparatus according to an embodiment of the present invention.
Referring to FIG. 1, the medical
The
The
Here, a lesion can refer to a human tissue in which an abnormality occurs due to a change in pathological action. Generally, if a lesion occurs in a patient's organs, the lesion may cause the organs to twist to the left or right, and the degree of twisting may increase depending on the progress of the lesion.
Accordingly, the
Specifically, the
Here, a singular point (landmark) can be recognized even when a patient's organs (for example, brain) are twisted due to a lesion, or can be assigned to a main structure in a long term in a position where the presence or absence of a lesion can be confirmed. That is, the
For example, referring to FIG. 2 (a), the
2 (b), the
The
In addition, the
The
4, the
In addition, the
In addition, the
When the lesion is included in the medical image, the
For example, when the lesion is included in the medical image, the
For example, referring to FIG. 4, the
In another example, when the lesion is included in the medical image, the
5, when the triangle formed on the medical image is determined to be abnormal including the
In this manner, the
In addition, the
The
For example, the
For example, referring to FIG. 7 (i), the
7 (b), the
In another example, the
As another example, the
In this way, the
According to the embodiment, when the disease category is identified by the
Specifically, the
For example, referring to (ii) of FIG. 7, when the area having brightness of 30 to 50 disappears in the triangle 'a3' and instead, a structure such as a bright band appears, Can be confirmed. The
Also, according to the embodiment, the
For example, in the medical image judged that the lesion is included, the
For example, referring to FIG. 8, the
In the medical image judged to include the lesion, the
For example, referring to FIG. 8, when the
As described above, according to the embodiment of the present invention, when a medical image of a patient's organs is input, the position of the lesion is identified from the medical image and the coded data generated through coding is automatically output, It is possible to easily obtain the code data related to the anatomical position of the lesion without performing the coding operation.
Also, according to the embodiment of the present invention, it is possible to allow the healthcare person to easily grasp the existence of the lesion and its anatomical position within the patient's organs by using only the code data.
According to an embodiment of the present invention, an anatomical location of a lesion can be more accurately identified and coded on the basis of a variable triangular model even for a medical image including a lesion and a long-term twisted compared to a normal state.
Also, according to an embodiment of the present invention, the size, volume, shape, brightness, number, and size of a lesion identified through a symmetrical comparison or numerical comparison of a plurality of triangles overlaid on the medical image based on a variable triangular model The medical information such as the progress degree can be automatically coded.
Further, according to the embodiment of the present invention, by generating code data in a form that is relatively compact compared to the conventional read-only data type and can be interpreted by an information terminal such as a computer, It is possible to more easily transmit the result of analyzing the medical image of the patient to the medical device, the personal health record system (PHR), the clinical decision system, and the big data system, thereby increasing the utilization.
2 is a diagram showing an example of creating a virtual figure (triangle) in the input medical image based on the variable triangular model.
Referring to FIG. 2, the medical image reading apparatus judges whether a lesion is included in a medical image of a patient organs and, if so, identifies an anatomical location of the lesion within the organ, Based analysis.
2 (a), the medical image reading apparatus includes a central point 4 of the brain, an
Referring to FIG. 2B, the medical image reading apparatus creates 16 symmetrical triangles symmetrically connecting the respective singularities (0 through 10) over the medical image, and forms a brain shape Can be patterned.
In the medical image reading apparatus, symbols (a1 to a8, b1 to b8) can be assigned to each triangle. Particularly, in a triangle formed at a symmetrical position, symbols 'a1' and 'b1' .
FIG. 3 is a diagram illustrating an example of determining the presence or absence of a lesion through a triangular symmetric comparison based on a variable triangular model. FIG.
3, the medical image reading apparatus symmetrically compares at least one of the size, the width, the shape, and the angle formed by the two sides of the triangles formed at the positions symmetrical to each other in a bilaterally symmetrical manner, It can be judged that the lesion is included (abnormal).
That is, when the right triangle of the
FIG. 4 is a diagram illustrating an example of determining the presence or absence of a lesion by comparing the distribution of pixels having a predetermined brightness.
FIG. 4 shows a
The medical image reading apparatus compares the brightness in the
In addition, if a triangle shape is adopted as a standard in the world and used to search for lesions, a standard normal histogram may be prescribed throughout the world.
For example, a medical image reading device should be "no more than 10 pixels with a brightness value of 60 to 70 in the left triangle bra-74 of the brain." Or "the peak value of the brightness value of the same triangle shall be 100 ± 5". And the medical image deviating from these rules can be judged to be abnormal (including lesions). These rules can be set differently depending on age or gender, such as, for example, "the younger the age, the higher the peak value".
Also, the medical image reading device can be used to check the lesion, such as the width and height of the triangle, and the angle produced by the two sides.
FIG. 4 is an example for determining which part of the brain (white matter or gray matter) of the lesion has developed. In the histogram shown in FIG. 4 (i) On the other hand, in the histogram shown in FIG. 4 (ii), the number of pixels having the same brightness value is reduced to 150 or less and the brightness value of 200 or more is greatly increased. Accordingly, the medical image reading apparatus can determine that a lesion has occurred in a portion of the
FIG. 5 is a diagram showing an example of identifying a position of a lesion by confirming a separation distance from a feature point forming a triangle.
Referring to FIG. 5, when the medical image is determined to be abnormal including the
That is, the medical image reading apparatus can confirm the position of the area apart from each point by dividing the distances in the points a, b and c in the shape of a symmetrical triangle. The medical image reading device can use the points and sides to determine which position of the brain the lesion corresponds to.
In this manner, the
6 is a diagram showing an example of identifying a tissue in which a lesion has occurred in an organ.
6, when the
Here, the concentric circle may indicate the distance from the
In addition, the medical image reading apparatus can output the code data designated to a part of the overlapping line segment when the line segments forming the figure overlap on the region where the lesion is located. That is, when a
Further, the medical image reading apparatus can identify the position of the lesion by simultaneously using the distance from the feature point and the position of the lesion in the triangle. When the
7 is a diagram showing an example of code data generated by coding the position of a lesion.
Referring to (i) of FIG. 7, in the medical image reading apparatus, when the lesion is identified as being located at a position distant from the central point of the brain, that is, in the left frontal cortex, at the boundary line between the triangle a8 and the triangle a1 , And code data '26972005' corresponding to the left frontal cortex can be output.
7 (ii), the medical image reading apparatus discriminates that the lesion is located in the region where the brightness appears to be 30 to 50 in the triangle 'a3' having brightness of 0 to 255, that is, in the side fissure , It is possible to output the code data '55228006' corresponding to the side fissure. At this time, when the area having the brightness of 30 to 50 disappears in the triangle 'a3' and instead, a structure like a bright band appears, the medical image reading device confirms that the hemorrhage occurs in the side fissure, Quot; 21454007 ", which is designated for the " 1 "
Fig. 8 is a diagram showing an example of coding medical information about the degree of progress of a lesion identified according to a change in the size of a triangle.
8 shows the triangular distribution in the
In the
A triangle a4 and a triangle b4 in the
The medical image reading device can utilize the numerical objective index for the progress of the hydrocephalus according to the size change of the lesion such as increasing or decreasing hydrocephalus. In addition, the medical image reading apparatus may define the ratio of the value of each line segment constituting the triangle a1, or may use the angle of the angle between the minutiae points 0, 1, 5 as an index of hydrocephalus. For example, in the medical image reading apparatus, by using the fact that the angle connecting the characteristic points '0', '1', and '5' in the
Hereinafter, the operation flow of the medical
9 is a flowchart illustrating a procedure of a method of operating a medical image reading apparatus according to an embodiment of the present invention.
The method of operating the medical image reading apparatus according to the present embodiment can be performed by the medical
Referring to FIG. 9, in
The medical
For example, referring to FIG. 2, the medical
3, the medical
In
For example, when the lesion is included in the medical image, the medical
For example, referring to FIG. 4, the medical
5, when the medical
As described above, the medical
In
For example, if the medical
In addition, when the medical
At this time, when the area having the brightness of 30 to 50 disappears in the triangle 'a3' and instead, a structure such as a bright band appears, the medical
That is, the medical
Also, the medical
Further, when the lesion is spread over a plurality of triangles, the medical
Further, according to the embodiment, the medical
For example, referring to FIG. 8, the medical
In the medical
As described above, according to the embodiment of the present invention, when a medical image of a patient's organs is input, the position of the lesion is identified from the medical image and the coded data generated through coding is automatically output, It is possible to easily obtain the code data related to the anatomical position of the lesion without performing the coding operation.
Also, according to the embodiment of the present invention, it is possible to allow the healthcare person to easily grasp the existence of the lesion and its anatomical position within the patient's organs by using only the code data.
The method according to an embodiment of the present invention may be implemented in the form of a program command that can be executed through various computer means and recorded in a computer-readable medium. The computer-readable medium may include program instructions, data files, data structures, and the like, alone or in combination. The program instructions to be recorded on the medium may be those specially designed and configured for the embodiments or may be available to those skilled in the art of computer software. Examples of computer-readable media include magnetic media such as hard disks, floppy disks, and magnetic tape; optical media such as CD-ROMs and DVDs; magnetic media such as floppy disks; Magneto-optical media, and hardware devices specifically configured to store and execute program instructions such as ROM, RAM, flash memory, and the like. Examples of program instructions include machine language code such as those produced by a compiler, as well as high-level language code that can be executed by a computer using an interpreter or the like. The hardware devices described above may be configured to operate as one or more software modules to perform the operations of the embodiments, and vice versa.
While the present invention has been particularly shown and described with reference to exemplary embodiments thereof, it is to be understood that the invention is not limited to the disclosed exemplary embodiments. For example, it is to be understood that the techniques described may be performed in a different order than the described methods, and / or that components of the described systems, structures, devices, circuits, Lt; / RTI > or equivalents, even if it is replaced or replaced.
Therefore, other implementations, other embodiments, and equivalents to the claims are also within the scope of the following claims.
100: Medical image reading device
110:
120: Identification unit
130:
Claims (18)
An identification unit for identifying a position of the lesion when the lesion is included in the medical image; And
Outputting code data generated by coding the position as a result of the medical image and outputting first code data related to a figure including a region represented by the lesion among the figures generated in the medical image And generating second code data relating to the lesion when the region is replaced with a structure and outputting the second code data together with the first code data,
Lt; / RTI >
Wherein,
Code data relating to the degree of progress of the lesion identified according to the size change of the region is included in the second code data and is output
Medical image reading device.
When the disease category is identified from the location by the identification unit,
Wherein,
The disease category is coded and included in the code data and output
Medical image reading device.
Wherein,
Assigning a singularity point in the medical image,
A virtual figure connecting the singular points is created by a specified number,
The presence or absence of the lesion is judged through symmetrical comparison or numerical comparison between the figures
Medical image reading device.
Wherein,
Any one of a center point of the organ associated with the medical image, an outer point on the contour constituting the organ, and a transition point where the shade is switched over to a predetermined value is assigned to the singular point
Medical image reading device.
When a lesion is included in the medical image,
Wherein,
The distance between the feature points constituting each figure is checked and the position of the lesion is identified
Medical image reading device.
When a lesion is included in the medical image,
Wherein,
It is determined whether or not the number of pixels having the predetermined brightness in each figure exceeds a certain range, and the position of the lesion is identified
Medical image reading device.
Wherein,
Identifying at least one medical information of size, volume, shape, brightness, number and progression for the lesion based on a variable triangular model,
Wherein,
The identified medical information is coded and included in the code data and output
Medical image reading device.
In a medical image judged to contain a lesion, if the size change of the triangle is below a certain level,
The identification unit identifies the progression of the lesion as 'initial'
The control unit codes the medical information that diagnoses the progress as 'early'
Medical image reading device.
In the medical image judged to include the lesion, if the triangle is confirmed to be extinct,
The identification unit re-identifies the progression of the lesion as 'severe'
Wherein the control unit updates the degree of progress of the medical information to 'severe'
Medical image reading device.
Wherein,
Code data generated by combining the feature points of the first figure determined to include the lesion and the ratio of the distance from each feature point to the lesion among the figures created in the medical image, When the line segment overlaps on the lesion, code data designated as a part of the overlapping line segment is output as the result
Medical image reading device.
Identifying a lesion in the medical image if the lesion is included in the medical image; And
And outputting code data generated by coding the position as a result of the input
Lt; / RTI >
Wherein the outputting step comprises:
Outputting first code data on a figure including a region that is associated with the lesion among the figures created in the medical image, and generating second code data on the lesion when the region is replaced with a structure And outputting the first code data together with the first code data; And
And outputting code data relating to the degree of progress of the lesion identified according to the size change of the region in the second code data and outputting
The method comprising the steps of:
If a disease category is identified from the location,
The medical image reading apparatus operating method includes:
Categorizing the disease category into the code data and outputting
Further comprising the steps of:
Wherein the determining step comprises:
Assigning a singularity in the medical image;
Creating a virtual figure connecting the singular points by a specified number; And
Determining whether the lesion is present through symmetric comparison or numerical comparison between the figures;
The method comprising the steps of:
Wherein the step of allocating the singular point comprises:
Assigning any one of a center point of the organs associated with the medical image, an outlier point on the outline of the organs, and a transition point where the shade is switched over to a predetermined value, to the singular point
The method comprising the steps of:
When a lesion is included in the medical image,
Wherein the identifying comprises:
Identifying a position of the lesion by checking a separation distance from a feature point constituting each figure,
The method comprising the steps of:
When a lesion is included in the medical image,
Wherein the identifying comprises:
Identifying the position of the lesion by checking whether the number of pixels having the predetermined brightness in each figure exceeds a certain range,
The method comprising the steps of:
If at least one of the size, volume, shape, brightness, number, and degree of progress of the lesion is identified based on the variable triangular model,
The medical image reading apparatus operating method includes:
Categorizing the identified medical care information into the code data and outputting
Further comprising the steps of:
In a medical image judged to include a lesion, if the size change of the triangle is below a predetermined level and the progression of the lesion is identified as 'initial'
The step of outputting the code data includes:
The step of coding the medical information diagnosing the progress level as " initial "
The method comprising the steps of:
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