KR101886235B1 - Apparatus and method for providing of body size specific dose and image quality based on ct image - Google Patents

Abstract

The present invention relates to a method for providing a body-size specific dose and an image quality index based on a CT image, and a method for providing a body-size-specific exposure dose and an image quality index based on a CT image includes the steps of: Calculating a body-size specific radiation dose considering the body size of the subject based on the identified body region, calculating an image quality index for the CT image based on the identified body region, A specific exposure dose, and the image quality index.

Description

TECHNICAL FIELD The present invention relates to an apparatus and method for providing a body-size-specific exposure dose and an image quality index based on a CT image,

The present invention relates to an apparatus and method for providing a body-size-specific exposure dose and an image quality index based on a CT image.

Computed tomography (CT) can capture a cross-section across a human body by photographing a subject entering a circular machine with an X-ray generator, and there is less overlap between structures than a simple X-ray Therefore, it has been widely used for the inspection of most organs and diseases because it has a merit of clearly observing structures and lesions.

The quality (resolution or precision) of CT images is a very important factor in the accurate diagnosis of lesions. Efforts are continuing to improve the quality of CT images with the development of CT systems in related fields. For example, there are multi-channel detector technology and high-speed high-resolution image reconstruction technology as CT image quality enhancement techniques. However, most of the conventional CT image quality enhancement techniques cause high dose radiation exposure, Concern is growing.

In this regard, international health and safety regulatory agencies are strengthening regulations to record and manage patient dose for every CT examination, but the burden of medical institutions is increasing. Thus, CT manufacturers provide radiation exposure figures as a part of the CT scan data as part of the inspection data, but this assumes that the patient's body is simply an acrylic object of a certain size and does not consider the body size of the patient, There is a problem that it is very low.

In order to overcome these problems, international organizations have published recommendations for CT scans to record and record the exposure dose taking into account the patient's body size.

For example, in the past, the patient-specific dose estimates (SSDE), which is a dose index tailored to the patient's body, were calculated, or the patient's body diameter using the attenuation index obtained from the CT scan A technique has been proposed that more accurately provides an exposure dose considering the patient's body size and X-ray attenuation degree.

However, such a conventional technique does not specifically disclose a method for obtaining the diameter of a patient's body. At present, there is a need to estimate the equivalent diameter of the patient by manually viewing the patient image for each image when calculating the SSDE.

On the other hand, the quality of the image can be considered as important part to be considered in the CT examination simultaneously with the radiation dose. If the amount of radiation exposure is too low to keep even the minimum quality required for diagnosis, the CT image can not be used for diagnosis, which can cause harm to both the patient and the medical institution.

Nevertheless, there is relatively little research on how to measure image quality on a quantitative basis in CT scans. Conventionally, as a method for measuring noise in an image, a region of interest (ROI) is drawn in a region where a measurer directly determines a CT value to be relatively uniform in the image, and a standard deviation or a signal-to- signal-to-noise ratio (SNR)). However, since the noise measurement method is manually performed by the measurer, there is a disadvantage in that it is time consuming and the reproducibility of the measured value is not sufficient.

Accordingly, there is a need for a technique capable of automatically calculating and providing the exposure dose and the image quality considering the body size in the CT image.

The background technology of the present application is disclosed in Korean Patent Laid-Open Publication No. 10-2014-0130784 (published on November 11, 2014).

The object of the present invention is to solve the above-mentioned problems of the conventional art, and it is an object of the present invention to provide a CT image-based body size calculation method capable of automatically calculating a body- And an apparatus and method for providing a specific exposure dose and an image quality index.

It is to be understood, however, that the technical scope of the embodiments of the present invention is not limited to the above-described technical problems, and other technical problems may exist.

According to an aspect of the present invention, there is provided a method for providing a body-size-specific exposure dose and an image quality index based on CT images, comprising the steps of: identifying a body region of a subject from an input CT image; Calculating a body-size specific radiation dose considering the body size of the subject based on the identified body region, calculating an image quality index for the CT image based on the identified body region, And displaying the image quality index.

The identifying step may include the steps of: designating a seed point in a central region of the CT image; expanding a region around the seed point in consideration of a range of pixel values of a body tissue; And identifying the body region by removing regions other than the body in the expanded region.

In addition, the step of designating the seed point may include designating a pixel at a center point of the CT image as the seed point, when the pixel at the center point does not satisfy the predetermined body tissue pixel value condition, A pixel that meets the predetermined body tissue pixel value condition within a predetermined distance can be designated as the seed point.

The step of calculating the body size specific radiation dose may further include the steps of: calculating a diameter of a water sample for the identified body area; calculating an irradiation dose conversion coefficient based on the calculated water sample diameter and a predetermined constant value according to the body part; And acquiring a CT dose index from externally provided data, wherein the body-size specific dose can be calculated by multiplying the exposure dose conversion coefficient by the CT dose index.

The calculating of the image quality index may further include calculating a structural component value for each of the pixels included in the identified bodily area, determining a pixel whose structural component value meets a predetermined criterion, Calculating a noise magnitude value based on a standard deviation of pixel values of pixels included in the flat region, and calculating a Hounsfield unit (HU) value of the pixels included in the flat region And calculating the contrast value based on a ratio of the contrast value to the noise size value.

The step of calculating the structural component value may further include the step of calculating a weighting factor for the size component value of the first derivative and the size component value of the first eigenvalue of the structure tensor matrix for each of the pixels included in the identified body region , And calculate the structural component value using the calculated edge precision value.

The step of calculating the structural component value may further include calculating, for each of the pixels included in the identified bodily area, a direction of the pixel based on the sum of the angular entropy value of the first order differentiating component and the angular entropy value of the structure tensor matrix, And calculate the structural component value through a ratio of the edge precision value to an arbitrary value in the pixel direction.

The calculating of the noise magnitude value may include calculating a noise magnitude value using pixels corresponding to the soft tissue component extracted in consideration of the range of the hunting field unit value for each tissue component among the pixels included in the flat region, Can be calculated.

The step of calculating the noise magnitude value may further include extracting a pixel having a unit field value of -200 HU to 300 HU among the pixels included in the flat region as pixels corresponding to the soft tissue component, The value can be calculated.

The step of calculating the contrast value may include calculating a pixel value of a pixel in the background tissue area and a pixel value of a tissue area of interest in consideration of a range of the Hounsfield unit value for each tissue component, The contrast value may be calculated by using a difference between an average pixel value of pixels included in the background tissue region and an average pixel value of pixels included in the tissue region of interest.

Meanwhile, an apparatus for providing a body-size specific exposure dose and an image quality index based on a CT image according to an embodiment of the present invention includes a body region identification unit for identifying a body region of a subject from an input CT image, A calculation unit for calculating a body-size-specific exposure dose considering the body size of the subject, an image quality index for the CT image, and a display unit for displaying the calculated body-size-specific exposure dose and the image quality index .

The body region identification unit may designate a seed point in a central region of the CT image, expand the region around the seed point in consideration of the range of pixel values of the body tissue, The body region can be identified by removing regions other than the body in the region.

The body region identification unit may designate a pixel at the center point of the CT image as the seed point, and when the pixel at the center point does not satisfy the predetermined body tissue pixel value condition, A pixel satisfying the predetermined body tissue pixel value condition may be designated as the seed point.

The calculating unit calculates the diameter of the object to be examined with respect to the identified body area, calculates an exposure coefficient based on a predetermined constant value according to the calculated diameter of the object and the body part, The CT dose index is obtained, and the body-size-specific exposure dose can be calculated by multiplying the CTx dose factor by the CT dose index.

The calculating unit may calculate a structural component value for each of the pixels included in the identified bodily area, extract a pixel whose structural component value satisfies a preset reference as pixels of the flat area, Calculating a noise magnitude value based on a standard deviation of pixel values of pixels included in the flat area, calculating a contrast value based on a Hounsfield unit (HU) value of pixels included in the flat area, And the image quality index may be calculated through a ratio of the contrast value to the noise size value.

For each of the pixels included in the identified body region, the calculation unit calculates the edge degree value by considering the weight component value of the magnitude component value of the first order differential value and the magnitude component value of the first eigenvalue of the structure tensor matrix And calculate the structural component value using the calculated edge precision value.

The calculation unit may calculate an arbitrary value of the pixel direction based on the sum of the angular entropy value of the first order differentiated component and the angular entropy value of the structure tensor matrix for each of the pixels included in the identified body region And calculate the structural component value through a ratio of the edge degree value to an arbitrary value of the pixel direction.

The calculating unit may calculate a noise magnitude value using a pixel corresponding to the extracted soft tissue component in consideration of a range of hunting field unit values for each tissue component among the pixels included in the flat region.

The calculating unit may calculate a noise magnitude value by extracting a pixel having a unit field value of -200 HU to 300 HU among the pixels included in the flat region as pixels corresponding to the soft tissue component.

The calculating unit may divide the pixels corresponding to the soft tissue components included in the flat region into pixels of the background tissue region and pixels of the tissue region of interest in consideration of a range of hunting field unit values for each tissue component, The contrast value may be calculated using a difference between an average pixel value of pixels included in the background tissue region and an average pixel value of pixels included in the tissue region of interest.

The above-described task solution is merely exemplary and should not be construed as limiting the present disclosure. In addition to the exemplary embodiments described above, there may be additional embodiments in the drawings and the detailed description of the invention.

According to the above-described task solution of the present invention, it is possible to calculate and provide the body-size-specific exposure dose and the image quality index of the CT image automatically considering the body size of the subject in the CT image.

In addition, the present invention can automatically divide an internal body region of a patient from a CT image, and calculate an exposure conversion coefficient based on the diameter of water and the water equivalent diameter on the basis thereof.

In addition, the present invention can extract a structural component from a CT image, find a flat area in the body, and calculate and provide an image quality index of the CT image.

Further, the effects obtainable here are not limited to the effects mentioned above, and other effects not mentioned can be clearly understood by those skilled in the art from the following description will be.

1 is a block diagram schematically showing a configuration of an apparatus 100 for providing a body-size specific exposure dose and an image quality based on a CT image according to an embodiment of the present invention.
FIG. 2 is a flowchart illustrating a process of identifying a body region of a subject in an apparatus 100 for providing body-size-specific exposure dose and image quality based on CT images according to an embodiment of the present invention.
FIG. 3 is a flowchart illustrating a process of calculating a body-size specific exposure in an apparatus 100 for providing a body-size-specific exposure dose and an image quality index based on a CT image according to an embodiment of the present invention.
4 is a flowchart illustrating a process of calculating an image quality index in an apparatus 100 for providing a body-size-specific exposure dose and an image quality based on a CT image according to an embodiment of the present invention.
FIG. 5 is a flowchart illustrating a method for providing a body-size specific dose and an image quality index based on a CT image according to an exemplary embodiment of the present invention.

Hereinafter, embodiments of the present invention will be described in detail with reference to the accompanying drawings so that those skilled in the art can easily carry out the present invention. It should be understood, however, that the present invention may be embodied in many different forms and should not be construed as limited to the embodiments set forth herein. In the drawings, the same reference numbers are used throughout the specification to refer to the same or like parts.

Throughout this specification, when an element is referred to as being "connected" to another element, it is intended to be understood that it is not only "directly connected" but also "electrically connected" or "indirectly connected" "Is included.

It will be appreciated that throughout the specification it will be understood that when a member is located on another member "top", "top", "under", "bottom" But also the case where there is another member between the two members as well as the case where they are in contact with each other.

Throughout this specification, when an element is referred to as "including " an element, it is understood that the element may include other elements as well, without departing from the other elements unless specifically stated otherwise.

1 is a block diagram schematically showing a configuration of an apparatus 100 for providing a body-size specific exposure dose and an image quality based on a CT image according to an embodiment of the present invention.

Referring to FIG. 1, an apparatus 100 for providing a body-size specific exposure dose and an image quality index based on a CT image according to an embodiment of the present invention includes a body region identification unit 110, a calculation unit 120, and a display unit 130 ).

The body region identification unit 110 can identify the body region of the subject from the input CT image. At this time, the device 100 for providing the body-size-specific exposure dose and picture quality index based on the CT image according to the embodiment of the present invention can receive the CT image from the CT system (not shown) connected through the network, Examples include a 3GPP (Long Term Evolution) network, a WIMAX (World Interoperability for Microwave Access) network, an Internet, a LAN (Local Area Network), a Wireless LAN (Wireless Local Area Network) , A WAN (Wide Area Network), a PAN (Personal Area Network), a Bluetooth network, a satellite broadcasting network, an analog broadcasting network, a DMB (Digital Multimedia Broadcasting) network, and the like.

The process of identifying the body region of the subject in the CT image through the body region identification unit 110 can be more easily understood with reference to FIG.

FIG. 2 is a flowchart illustrating a process of identifying a body region of a subject in an apparatus 100 for providing body-size-specific exposure dose and image quality based on CT images according to an embodiment of the present invention.

Referring to FIG. 2, the body region identification unit 110 may designate (21) at least one seed point in the central region of the input CT image.

At this time, the body region identification unit 110 can designate the pixel at the center point of the CT image as the seed point, and if the pixel at the center point does not satisfy the predetermined body tissue pixel value condition, A pixel that meets a predetermined body tissue pixel value condition within a distance can be designated as a seed point. In other words, the body region identification unit 110 specifies a pixel (pixel) at the center of the entire volume in the CT image as an initial seed value, where the pixel at the center point is a predetermined pixel value If the condition is not satisfied, a pixel satisfying the condition can be designated as an initial seed value by searching for neighboring pixels satisfying the signal range condition of the body region within a predetermined distance.

Then, the body region identification unit 110 may expand the region around the seed point (S22) in consideration of the range of the pixel value of the body tissue, and express it in a different manner within the range of the pixel value of the main body of the body Can grow around the seed point. At this time, in the process of the step S22 of expanding the region around the seed point, the extended region may include objects other than the body region such as clothing, a ringer line, a table of the CT apparatus, and the like. Therefore, after step S22, the body region identification unit 110 can identify the body region in the CT image (S23) by removing regions other than the body in the expanded region. At this time, in step S23, the body region identification unit 110 repeatedly applies a predetermined number of morphological operations such as erosion, dilation, and the like to the extended region, It is possible to remove an area including other objects. Through this process, the body region identification unit 110 can acquire the body region data in which only the body region of the subject is identified (or divided) from the CT image.

Then, the calculating unit 120 calculates the body-size-specific exposure dose and the image quality index for the CT image based on the body region identified through the body region identifying unit 110 and considers the body size of the subject, The apparatus 100 for providing a body-size-specific exposure dose and image quality based on a CT image according to an exemplary embodiment can prevent an influence on an area other than a body when calculating an exposure dose and an image quality index.

On the other hand, since there may be noise in the input CT image, in consideration of this, before the step S21 of designating the seed point, the body region identification unit 110 reads the input CT image to prevent the influence of noise A process of pre-processing with smoothing can be performed.

The calculation unit 120 can calculate the body-size specific dose and the image quality index for the CT image based on the body area identified by the body area identification unit 110, taking into account the body size of the subject. The process of calculating the body size specific exposure dose can be more easily understood from FIG. 3, and the process of calculating the picture quality index can be more easily understood from FIG.

FIG. 3 is a flowchart illustrating a process of calculating a body-size specific exposure in an apparatus 100 for providing a body-size-specific exposure dose and an image quality index based on a CT image according to an embodiment of the present invention.

Through the process of FIG. 3, the apparatus 100 for providing the specific exposure dose and image quality index for each body size based on the CT image can calculate the exposure dose considering the body size of each patient.

Referring to FIG. 3, the calculation unit 120 may calculate the diameter of a body portion corresponding to the body region identified by the body region identification unit 110 (S31).

In step S31, the calculation unit 120 can calculate the water-equivalent diameter D _w based on the equation (1).

)을 곱한 후 이를 원주율(π)로 나누고, 제곱근을 구한 값에 2를 곱함으로써 물등가직경을 계산할 수 있다.Referring to Equation (1), the calculation unit 120 calculates the water fraction and the area of each pixel in the hounsfield unit (HU) of each pixel in the identified body region

), Divide it by the circle (π), and multiply the value obtained by the square root by 2 to calculate the diameter of the workpiece.

Next, the calculation unit 120 may calculate the exposure coefficient conversion coefficient based on the calculated water-equivalent diameter and a predetermined constant value according to body parts (e.g., head, torso, etc.) (S32).

)를 계산할 수 있다.Specifically, the calculating unit 120 calculates an exposure dose conversion coefficient

) Can be calculated.

Referring to Equation (2), the calculation unit 120 multiplies the value D of the material equivalent to the body of the subject calculated by Equation (1) by a predetermined constant value b, and calculates a natural constant-based exponential function And then multiplying the predetermined constant value a by the predetermined constant a.

Here, the constant value is set in advance so as to have a value of a = 4.378094 and b = 0.04331124 when the body part is a torso, and a = 1.874799 and b = 0.03871313 when the body part is a head .

Next, the calculating unit 120 obtains a volume CT dose index (i.e., a recommended dose value CTDI _vol , which is received by the patient at the time of CT imaging, CTDI _vol ) from data provided from an external (e.g., CT manufacturer) can do.

For example, the calculating unit 120 may acquire a volume CT dose index by applying optical character recognition (OCR) to a dose report image provided by a CT manufacturer.

In another example, the calculator 120 may be based on a medical protocol, such as Digital Imaging and Communications in Medicine (DICOM), an application layer network protocol for the transmission of medical images, waveforms, A volume CT dose index can be obtained by searching for the existence of a tag ID indicating CTDI _vol information among the DICOM headers provided by the CT manufacturer and extracting a numerical value corresponding to the tag ID.

The calculating unit 120 can calculate the body-size specific dose considering the body size of the subject by multiplying the previously calculated dose conversion coefficient by the previously obtained volume CT dose index.

Meanwhile, FIG. 4 is a flowchart illustrating a process of calculating an image quality index in an apparatus 100 for providing a body-size specific exposure dose and an image quality based on a CT image according to an embodiment of the present invention.

Through the process of FIG. 4, the apparatus 100 for providing the specific exposure dose and image quality index for each body size based on the CT image can calculate the image quality index for the CT image.

Referring to FIG. 4, the calculation unit 120 calculates a structural component value at each pixel in the identified body region, through calculation of structural component values for each of the pixels included in the body region identified in the body region identification unit 110 Can be extracted. A more detailed description follows.

To extract the structural components, the calculation unit 120 calculates an edge degree value for each of the pixels included in the identified body region, calculates an arbitrary value in the pixel direction for each of the pixels, And calculating a structural component value through a ratio to an arbitrary value in the pixel direction of the magnitude value.

The step of calculating the edge degree value is to obtain an edge feature accompanied by a structural component in the CT image. The calculation unit 120 calculates the edge feature value in the CT image, It can be calculated to reflect the characteristics of the signal slope at the boundary between the two tissue regions and the signal curvature characteristics due to the tubular structure such as blood vessels.

The calculating unit 120 calculates the magnitude component value of the first-order differential for each of the pixels included in the identified bodily area and the magnitude component value of the first eigenvalue of the structure tensor matrix for each of the pixels included in the identified bodily area The edge degree value can be calculated by considering the weight. In other words, the calculation unit 120 may consider the weights of the magnitude component values of the first-order differential of each pixel and the magnitude component values of the first-order eigenvalues of the structure tensor matrix as shown in Equation (3) By summing the values, the degree of edge can be calculated.

는 픽셀의 엣지정도를 나타내고,

는 1차 미분의 크기 성분 값을 나타내고,

는 구조텐서 행렬의 1차 고유값의 크기 성분 값을 나타내고, ω₁ 및 ω₂는 두 성분 각각에 대한 가중치를 나타낸다.At this time,

Represents the edge degree of the pixel,

Represents the magnitude component value of the first-order differential,

Represents the magnitude component value of the first eigenvalue of the structure tensor matrix, and? ₁ and? ₂ represent the weight for each of the two components.

Next, the calculation unit 120 calculates the angular entropy value of the first-order differentiating component for each of the pixels included in the identified body region as shown in Equation (4) and the angular entropy value of the pixels included in the identified body region as shown in Equation Based on the sum of the angular entropy values of the structure tensor matrix for each, an arbitrary value of the pixel orientation (or pixel angle) for the pixels contained in the identified body region can be calculated.

는 1차 미분한 수평축 성분과 수직축 성분 간의 각도를 나타내고,

는 확률밀도 함수를 나타내고, ln은 자연 로그 함수를 나타낸다.In Equation (4), H _G represents the angular entropy of the value of the first derivative component,

Represents the angle between the first differentiated horizontal axis component and the vertical axis component,

Denotes a probability density function, and ln denotes a natural logarithmic function.

는 구조텐서 행렬에서 얻어지는 고유벡터의 각도를 나타낸다.In Equation (5), H _T represents the angular entropy of the structure tensor matrix,

Represents the angle of the eigenvector obtained from the structure tensor matrix.

In Equations (4) and (5), a region of interest (ROI) means a surrounding region of interest including the corresponding pixel. For example, the region of interest ROI is set to a circular region of 1 cm diameter centered on each pixel .

Also, in the equations (4) and (5), the angle of the first-order differential component and the angle of the structure tensor matrix are widely distributed in units of decimals, and the local entropy value may not reflect the structural characteristics of the image. In consideration of this, the calculating unit 120 may use the angle of the first order differential component quantized in units of 10 degrees and the angle of the structure tensor matrix when calculating the structural component value.

The calculation unit 120 may calculate the structural component value using each of the calculated edge degree values and the pixel direction randomness values. That is, the calculating unit 120 may calculate the structural component value using the edge accuracy value or may calculate the structural component value using the randomness value in the pixel direction. Further, the calculating unit 120 may calculate the structural component value at a ratio of the edge precision value and the randomness value in the pixel direction. More specifically, the calculating unit 120 may calculate the structural component value for the pixels included in the identified body region by dividing the edge precision value by the arbitrary value in the pixel direction.

Next, the calculation unit 120 can identify the flat region within the identified bodily region based on the calculated structural component values, wherein the calculated structural component values for each of the pixels included in the identified bodily region Are high values in the presence of boundary regions or tubular structures between tissue regions and low values in flat regions. However, since the absolute value of the absolute value of the structural component value can be largely varied depending on various factors such as the thickness of the slice, the tube voltage, the tube current, and more importantly, the reconstruction kernel uniquely provided for each CT manufacturer, It may be difficult to divide the structural region and the flat region within the body region identified through the body region identification unit 110 with a predetermined absolute reference. Accordingly, the calculating unit 120 can utilize the relative distribution of the structural component values when identifying flat regions within the identified body region using the structural component values.

The calculating unit 120 may extract a pixel whose structural component value satisfies a predetermined criterion as pixels of the flat region among pixels included in the identified body region. Specifically, the calculation unit 120 arranges the calculated structural component values for each of the pixels included in the identified body region in order of magnitude, and then calculates a pixel having a value less than a predetermined value as a pixel included in the flat region Can be selected.

Next, the calculation unit 120 may calculate the noise magnitude value by calculating the standard deviation of the pixel values of the pixels included in the flat region.

At this time, the calculation unit 120 may calculate the noise magnitude value using the pixels corresponding to the extracted soft tissue components in consideration of the range of the hunting field unit value of each tissue component among the pixels included in the flat region.

Specifically, the pixels included in the flat region may include tissue components such as bone tissue, calcium component, or implant implanted in the body, and an exceptionally high noise value may appear for such tissue components. Therefore, in order to exclude an exceptionally high noise value occurring in tissue components such as bone tissue, calcium component, prosthesis and the like among the pixels in the flat region in the calculation of the noise size value, A range of values can be used to extract only the pixels of the main soft tissue component, and the noise size value can be calculated using the pixels of the extracted main soft tissue component. For example, the calculation unit 120 can calculate a noise size value by extracting pixels of the pixels included in the flat region with a unit field value of -200 HU to 300 HU as a pixel corresponding to the main soft tissue component have.

Next, the calculation unit 120 can obtain the contrast between the background and the target tissue in the CT image based on the unit field value of the pixels included in the flat region. In the CT image, the contrast between the background tissue and the target tissue It is desirable to have a high contrast level because CT is the main factor that determines the image quality of CT images and is also used for CT examination. However, since various factors such as the section thickness, the tube voltage, the tube current, the amount of the contrast agent injected, and the organ function of the subject may influence the contrast degree, the CT image can be classified into specific The apparatus 100 for providing an exposure dose and picture quality index can monitor through the calculation unit 120 whether or not a proper contrast is calculated.

The calculating unit 120 may calculate the contrast value based on the ununiform unit value of the pixels included in the flat area. In addition, the calculation unit 120 divides the pixels corresponding to the soft tissue components included in the flat region into pixels of the background tissue region and pixels of the tissue region of interest, taking into account the range of the hunting field unit value for each tissue component , The contrast value can be calculated using the difference between the average pixel value of the pixels included in the background tissue area and the average pixel value of the pixels included in the tissue area of interest.

More specifically, the calculating unit 120 calculates the pixels belonging to the flat region based on the HUs value of the pixels belonging to the flat region according to the distribution range of the hun- A pixel belonging to the organization area and a pixel belonging to the interest organization area. For example, the distribution range of Hounsfield unit values for each tissue component is divided into -200HU to -50HU for fat tissue, -49HU to +40HU for soft tissue, Contrast enhancement tissue can be divided into the range of + 41HU to + 300HU.

In consideration of the distribution range of the Hounsfield unit value for each tissue component, the calculation unit 120 may divide the pixels belonging to the flat region into pixels of the background organization region and pixels of the interest tissue region. At this time, The average value of the pixels classified by each organization can be used as a representative value of each tissue component. Accordingly, the calculating unit 120 calculates the representative value of the background organization (that is, the average pixel value of the pixels included in the background tissue region) and the representative value of the interested tissue (i.e., The contrast value can be calculated through the difference value between the two values.

At this time, the calculating unit 120 may calculate the difference value between the background organization and the representative value of the target tissue based on the type information of the CT scan acquired from the CT image.

For example, in the case of a CT image for liver CT examination, the calculating unit 120 may use the soft tissue as a background tissue, and the liver and the enhancement tissue may be used as an interested tissue. (I.e., a representative value of soft tissues) of the pixels classified by the soft tissues among the pixels included in the flat region and an average pixel value of the pixels classified by the liver and the enhancement tissue (i.e., The representative value), the contrast value can be calculated.

As another example, in the case of a CT image for a CT examination of a nonspecific organs, the calculating unit 120 may use the fat tissue as a background tissue and the soft tissue as an interested tissue. Based on this, (120) can calculate the contrast value by the difference between the representative value of the soft tissue and the representative value of the fat tissue.

Next, the calculating unit 120 may calculate the image quality index for the input CT image using the noise size value and the contrast value calculated above.

Specifically, the calculating unit 120 may calculate the image quality index based on the ratio of the contrast value to the noise size value. In other words, the calculation unit 120 may calculate the ratio of the contrast value divided by the noise size value as the image quality index.

The display unit 130 displays the body-size-specific dose and the image quality index calculated through the calculator 120, thereby providing the user with the information.

The display unit 130 can easily determine whether the calculation of the body size-specific exposure dose, the image quality index calculation value, and the division of the body region derived from the corresponding value (i.e., the identification of the body region of the subject in the CT image) The outline of the body region identified on the CT image can be provided in a color different from the original pixel value. In addition, the display unit 130 arbitrarily selects a representative region of interest in the flat region and randomly selects an outline of the selected region of interest so that the user can easily confirm whether the flat region has been identified in the identified body region It can be provided with a color different from the original pixel value. Accordingly, the user can more easily perceive the portion (or position) corresponding to the body region and the flat region based on the calculated body size specific radiation dose and the calculated image quality index in the CT image.

Hereinafter, the operation flow of the present invention will be briefly described based on the details described above.

FIG. 5 is a flowchart illustrating a method for providing a body-size specific dose and an image quality index based on a CT image according to an exemplary embodiment of the present invention.

FIG. 5 shows a method of providing a body-size-specific exposure dose and an image quality index based on a CT image according to the body-size-specific exposure dose and image quality index providing apparatus 100 based on the CT image described above. Therefore, even if the contents are omitted in the following description, the contents of the CT image-based body size-specific exposure dose and picture quality index providing apparatus 100 can be similarly applied to FIG.

Referring to FIG. 5, in step S51, the identification unit 110 can identify the body region of the subject from the input CT image.

At this time, the identification unit 110 designates a seed point in the central region of the CT image, expands the region around the seed point in consideration of the range of pixel values of the body tissue, By removing the other area, the body area can be identified.

When designating the seed point, the identifying unit 110 designates the pixel at the center point of the CT image as the seed point, and when the pixel at the center point does not satisfy the predetermined body tissue pixel value condition, A pixel that meets a predetermined body tissue pixel value condition within a distance can be designated as a seed point.

Next, in step S52, the calculating unit 120 may calculate a body-size specific exposure dose considering the body size of the subject based on the body area identified in step S51.

At this time, in step S52, the calculating unit 120 calculates the diameter of the water body corresponding to the identified body region, calculates the radiation dose conversion coefficient on the basis of the calculated water-filled diameter and a predetermined constant value according to the body part, The body dose specific dose can be calculated by obtaining the CT dose index from the data obtained by multiplying the CT dose index by the exposure dose conversion coefficient and the CT dose index.

Next, in step S53, the calculating unit 120 may calculate the image quality index for the CT image based on the body area identified in step S51.

At this time, in step S53, the calculation unit 120 calculates a structural component value for each of the pixels included in the identified bodily area, and calculates a pixel whose structural component value satisfies a predetermined criterion, , Calculates a noise magnitude value based on the standard deviation of the pixel values of the pixels included in the flatness area, and calculates a contrast value based on the Hounsfield unit (HU) value of the pixels included in the flatness area And the picture quality index can be calculated through the ratio of the contrast value to the noise size value.

Further, in step S53, the calculating unit 120 may calculate the edge degree value and the randomness value of the pixel direction for each of the pixels included in the identified body region, calculate the structural component value using the edge degree value The structural component value can be calculated using the randomness value in the pixel direction. The calculation unit 120 may also calculate the structural component value through a ratio to the arbitrary value of the pixel orientation of the edge accuracy value.

In calculating the structural component value, the calculation unit 120 calculates the weight component value of the first-order differential value and the magnitude component value of the first eigenvalue of the structure tensor matrix, for each of the pixels included in the identified body region , And for each of the pixels, calculate an arbitrary value in the pixel direction based on the sum of the angular entropy value of the first-order differentiated component and the angular entropy value of the structure tensor matrix.

In step S53, the calculation unit 120 calculates the noise size value using the pixels corresponding to the extracted soft tissue components in consideration of the range of the hunting field unit value for each tissue component among the pixels included in the flat region . At this time, the calculating unit 120 may calculate a noise magnitude value by extracting pixels having a unit field value of -200 HU to 300 HU among the pixels included in the flat region as pixels corresponding to the soft tissue component.

In step S53, the calculation unit 120 calculates a pixel corresponding to the soft tissue component included in the flat region as a pixel of the background tissue region and a pixel of the tissue region of interest, taking into account the range of the predetermined tissue component unit value The contrast value can be calculated using the difference between the average pixel value of the pixels included in the background organization area and the average pixel value of the pixels included in the tissue area of interest.

Next, in step S54, the display unit 130 may display the calculated body-size specific dose and the image quality index.

In the above description, steps S51 to S54 may be further divided into further steps or combined into fewer steps, according to embodiments of the present invention. Also, some of the steps may be omitted as necessary, and the order between the steps may be changed.

The CT image-based body-size-specific exposure dose and image quality index providing method according to one 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 recorded on the medium may be those specially designed and constructed for the present invention 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 present invention, and vice versa.

In addition, the CT image-based body-size-specific exposure dose and image quality index providing method may be implemented in the form of a computer program or an application executed by a computer stored in a recording medium.

It will be understood by those of ordinary skill in the art that the foregoing description of the embodiments is for illustrative purposes and that those skilled in the art can easily modify the invention without departing from the spirit or essential characteristics thereof. It is therefore to be understood that the above-described embodiments are illustrative in all aspects and not restrictive. For example, each component described as a single entity may be distributed and implemented, and components described as being distributed may also be implemented in a combined form.

The scope of the present invention is defined by the appended claims rather than the detailed description, and all changes or modifications derived from the meaning and scope of the claims and their equivalents should be interpreted as being included in the scope of the present invention.

100: Image-based body size specific exposure dose and image quality index
110: Body area identification part
120:
130:

Claims (21)

In a device for providing a body-size-specific exposure dose and image quality index based on a CT image, a body region of a subject satisfying the predetermined body tissue pixel value condition is identified from an input CT image based on a predetermined body tissue pixel value condition step;
Calculating, in the providing apparatus, a body-size-specific exposure dose considering the body size of the subject based on the identified body region;
Calculating, in the providing device, an image quality index for the CT image based on the identified body area; And
In the providing apparatus, displaying the body-size-specific exposure dose and the picture quality index,
A method for providing body image size specific dose and image quality index based on CT image. The method according to claim 1,
Wherein the identifying comprises:
Designating a seed point in a central region of the CT image;
Expanding a region around the seed point in consideration of a range of pixel values of a body tissue; And
And identifying the body region by removing regions other than the body in the expanded region. A method for providing a body image size-specific exposure dose and an image quality index based on a CT image. 3. The method of claim 2,
Wherein the step of designating the seed point comprises:
Designating a pixel at a center point of the CT image as the seed point,
And assigns to the seed point a pixel that meets the predetermined body tissue pixel value condition within a predetermined distance from the center point if the pixel at the center point does not meet a predetermined body tissue pixel value condition, A method for providing body - size specific dose and image quality index based on CT image. The method according to claim 1,
The step of calculating the body-size-specific exposure dose includes:
Calculating a material equivalent diameter for the identified body region;
Calculating an exposure coefficient conversion coefficient based on a predetermined constant value according to the calculated water-filled-in diameter and the body part; And
Acquiring a CT dose index from externally provided data,
Wherein the body-size-specific exposure dose is calculated by multiplying the exposure dose conversion factor by the CT dose index, wherein the body-size-specific exposure dose is calculated. The method according to claim 1,
Wherein the step of calculating the image quality index comprises:
Computing a structural component value for each of the pixels included in the identified body region;
Extracting, as pixels of the flat region, pixels whose structural component values satisfy predetermined criteria among the pixels;
Calculating a noise magnitude value based on a standard deviation of pixel values of pixels included in the flat area; And
And calculating a contrast value based on a Hounsfield unit (HU) value of the pixels included in the flat area,
And calculating the image quality index based on a ratio of the contrast value to the noise magnitude value. 6. The method of claim 5,
Wherein calculating the structural component value comprises:
For each of the pixels included in the identified bodily area, calculating an edge precision value by taking the weights into the magnitude component values of the first order differential and the magnitude component values of the first eigenvalues of the structure tensor matrix, Wherein the structural component value is calculated using the degree value of the CT image. The method according to claim 6,
Wherein calculating the structural component value comprises:
Calculating an arbitrary value in the pixel direction based on the sum of the angular entropy value of the first derivative different component and the angular entropy value of the structure tensor matrix for each of the pixels included in the identified body region,
And calculating the structural component value through a ratio of the edge precision value to an arbitrary value in the pixel direction. 6. The method of claim 5,
The step of calculating the noise magnitude value comprises:
Wherein a noise size value is calculated using pixels corresponding to the extracted soft tissue components in consideration of a range of hunting field unit values of predetermined texture components among pixels included in the flat region, A method for providing a specific exposure dose and an image quality index. 9. The method of claim 8,
The step of calculating the noise magnitude value comprises:
And calculating a noise magnitude value by extracting, as pixels corresponding to the soft tissue component, pixels having a mean square unit value between -200 HU and 300 HU among the pixels included in the flat region, A method for providing size-specific exposure dose and image quality index. 6. The method of claim 5,
Wherein the step of calculating the contrast value comprises:
A pixel corresponding to a soft tissue component included in the flat region is divided into a pixel in a background tissue region and a pixel in a tissue region of interest in consideration of a range of a predetermined tissue component unit value,
Wherein the contrast value is calculated using a difference between an average pixel value of pixels included in the background tissue region and an average pixel value of pixels included in the region of interest tissue, And providing an image quality index. A body region identification unit for identifying a body region of the subject satisfying the predetermined body tissue pixel value condition from an input CT image based on a predetermined body tissue pixel value condition;
A calculation unit for calculating a body-size specific exposure dose considering the body size of the subject based on the identified body area and an image quality index for the CT image; And
A display unit for displaying the calculated body-size-specific exposure dose and the image quality index,
And a CT image-based body-size-specific exposure dose and image quality index. 12. The method of claim 11,
Wherein the body region identification unit comprises:
Designating a seed point in a central region of the CT image,
A region around the seed point is expanded in consideration of a range of pixel values of a body tissue,
And the body region is identified by removing a region other than the body in the expanded region, wherein the body region is identified based on the CT image. 13. The method of claim 12,
Wherein the body region identification unit comprises:
Designating a pixel at a center point of the CT image as the seed point,
And assigns to the seed point a pixel that meets the predetermined body tissue pixel value condition within a predetermined distance from the center point if the pixel at the center point does not meet a predetermined body tissue pixel value condition, Device for providing body size specific dose and image quality index based on CT image. 12. The method of claim 11,
The calculating unit calculates,
Calculating a water-equivalent diameter for the identified bodily area,
Calculating an exposure coefficient conversion coefficient on the basis of a predetermined constant value according to the calculated diameter and diameter of the body part,
Obtains a CT dose index from data provided from outside,
Wherein the body-size-specific exposure dose is calculated by multiplying the exposure dose conversion coefficient by the CT dose index, and wherein the body-size-specific exposure dose is calculated. 12. The method of claim 11,
The calculating unit calculates,
Calculating a structural component value for each of the pixels included in the identified body region,
Extracting, as pixels of the flat region, pixels whose structural component values satisfy predetermined criteria among the pixels,
Calculating a noise magnitude value based on a standard deviation of pixel values of pixels included in the flat region,
Calculating a contrast value based on a Hounsfield unit (HU) value of pixels included in the flat area,
Wherein the image quality index is calculated based on a ratio of the contrast value to the noise size value. 16. The method of claim 15,
The calculating unit calculates,
For each of the pixels included in the identified bodily area, calculating an edge precision value by taking the weights into the magnitude component values of the first order differential and the magnitude component values of the first eigenvalues of the structure tensor matrix, And the structural component value is calculated using the degree value of the CT image. 17. The method of claim 16,
The calculating unit calculates,
Calculating an arbitrary value in the pixel direction based on the sum of the angular entropy value of the first derivative different component and the angular entropy value of the structure tensor matrix for each of the pixels included in the identified body region,
And calculates the structural component value through a ratio of the edge precision value to an arbitrary value in the pixel direction. 16. The method of claim 15,
The calculating unit calculates,
Wherein a noise size value is calculated using pixels corresponding to the extracted soft tissue components in consideration of a range of hunting field unit values of predetermined texture components among pixels included in the flat region, Specific dose and image quality index. 19. The method of claim 18,
The calculating unit calculates,
And calculating a noise magnitude value by extracting, as pixels corresponding to the soft tissue component, pixels having a mean square unit value between -200 HU and 300 HU among the pixels included in the flat region, Size specific dose and device for providing image quality index. 16. The method of claim 15,
The calculating unit calculates,
A pixel corresponding to a soft tissue component included in the flat region is divided into a pixel in a background tissue region and a pixel in a tissue region of interest in consideration of a range of a predetermined tissue component unit value,
Wherein the contrast value is calculated using a difference between an average pixel value of pixels included in the background tissue region and an average pixel value of pixels included in the region of interest tissue, And an image quality index providing device. A computer-readable recording medium storing a program for executing the method of any one of claims 1 to 10 in a computer.

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