KR102377530B1 - The method and apparatus for generating three-dimensional(3d) image of the object - Google Patents

Abstract

According to an embodiment of the present invention, a method for generating a 3D image of an object includes: acquiring ultrasound data of the object; and generating a three-dimensional image of the object based on the obtained ultrasound data, wherein the generating of the three-dimensional image of the object includes a portion in which the characteristic information of the obtained ultrasound data is different from the 3D image of the object. A 3D image of the object may be generated so that the 3D image is expressed differently.

Description

Method and apparatus for generating a three-dimensional image of an object

The present invention relates to a method and apparatus for generating a 3D image of an object, and more particularly, to a method and apparatus for generating a 3D medical image of an object.

An ultrasound diagnosis apparatus transmits an ultrasound signal from a body surface of an object toward a predetermined part of the body, and obtains an image of a tomography or blood flow of a soft tissue by using information on the ultrasound signal reflected from a tissue in the body.

Such an ultrasound diagnosis apparatus has an advantage of being able to display information about an object in real time. In addition, the ultrasound diagnosis apparatus has the advantage of high stability because there is no exposure to X-rays, and other image diagnosis such as X-ray diagnostic apparatus, CT (Computerized Tomography) scanner, MRI (Magnetic Resonance Image) apparatus, nuclear medicine diagnostic apparatus, etc. It is widely used with devices.

According to an embodiment of the present invention, a method for generating a 3D image of an object includes: acquiring ultrasound data of the object; and generating a three-dimensional image of the object based on the obtained ultrasound data, wherein the generating of the three-dimensional image of the object includes a portion in which the characteristic information of the obtained ultrasound data is different from the 3D image of the object. A 3D image of the object may be generated so that the 3D image is expressed differently.

For example, the characteristic information may include at least one of image characteristic information, physical property information, and surface information about the object.

For example, the generating of the three-dimensional image of the object may include generating the three-dimensional image of the object through at least one of a specular reflection coefficient, a specular light index, and a color of the object.

For example, the generating of the 3D image of the object may include rendering the 3D image of the object according to the characteristic information.

For example, the method may further include displaying the generated 3D image of the object.

For example, generating the 3D image of the object may include generating an image having a reflected light effect on the object.

For example, the image having the reflected light effect may be generated by a plurality of light sources.

According to an embodiment of the present invention, an apparatus for generating a 3D image of an object includes: an ultrasound data acquisition unit configured to acquire ultrasound data of the object; and an image generator generating a three-dimensional image of the object based on the obtained ultrasound data, wherein the generating of the three-dimensional image of the object includes: a portion in which the characteristic information of the obtained ultrasound data is different is determined by the object. A 3D image of the object may be generated so that the 3D image is expressed differently.

For example, the characteristic information may include at least one of image characteristic information, physical property information, and surface information about the object.

For example, the image generator may generate a 3D image of the object through at least one of a specular reflection coefficient, a specular light index, and a color of the object.

For example, the image generator may generate a 3D image of the object by rendering a 3D image of the object according to the characteristic information.

For example, it may further include a display unit for displaying the generated 3D image.

For example, the image generator may generate an image having a reflected light effect on the object.

For example, the image having the reflected light effect may be generated by a plurality of light sources.

According to an embodiment of the present invention, a method for generating a 3D image of an object includes: acquiring medical image data of the object; and generating an image having a reflected light effect on the object based on the obtained medical image data.

For example, the method may further include displaying an image having the reflected light effect.

For example, generating the image having the reflected light effect on the object may include calculating a representative voxel to be displayed on a screen among voxels in a path of a gaze vector; calculating a surface normal vector; calculating a reflected light vector through the surface normal vector; generating a color of the object, a reflection coefficient for a light source, and a specular light index; and calculating the color of one point included in the image through at least one of the reflected light vector, the color of the object, the reflection coefficient for the light source, and the specular light index.

For example, generating the image having the reflected light effect on the object may include: extracting a depth map of the object and the screen; calculating a surface normal vector for the depth map; calculating a reflected light vector through the surface normal vector; generating a color of the object, a reflection coefficient for a light source, and a specular light index; and calculating the color of one point included in the image through at least one of the reflected light vector, the color of the object, the reflection coefficient for the light source, and the specular light index.

For example, the image having the specular light effect may be generated through a plurality of renderings including specular rendering.

For example, the image having the reflected light effect may be generated by a plurality of light sources.

For example, the medical image data may be image data of an object obtained using an ultrasound diagnosis apparatus, an X-ray diagnosis apparatus, a computerized tomography (CT) scanner, or a magnetic resonance image (MRI) apparatus.

According to an embodiment of the present invention, an apparatus for generating a 3D medical image of an object includes an ultrasound data acquisition unit configured to acquire medical image data of the object; and an image generator generating an image having a reflected light effect on the object based on the obtained medical image data.

For example, it may further include a display unit for displaying the image having the reflected light effect.

For example, the image generator may receive an input from the outside of the device or internally calculate the color of the object, the reflection coefficient for the light source, and the specular light index, and the color of the object, the reflection coefficient for the light source, and the It may be characterized in that the color of one point included in the image is calculated through at least one of the specular light indices.

For example, the image generator extracts a depth map for the object and the screen, calculates a reflected light vector, and calculates a color for one point included in the image through the reflected light vector. can be characterized.

For example, the image having the reflected light effect may be generated by a plurality of light sources.

For example, the image having the specular light effect may be generated through a plurality of renderings including specular rendering.

For example, the medical image data may be image data of an object obtained using an ultrasound diagnosis apparatus, an X-ray diagnosis apparatus, a computerized tomography (CT) scanner, or a magnetic resonance image (MRI) apparatus.

1 shows an ultrasound image and a 3D rendered image of an object.
2 is a flowchart illustrating a method for generating a 3D image in which characteristic information of an object is reflected according to an embodiment of the present invention.
3 shows that image characteristic information is a spatial frequency according to an embodiment of the present invention.
4 shows that image characteristic information is image intensity according to an embodiment of the present invention.
5 shows that the image characteristic information is an image histogram according to an embodiment of the present invention.
6 illustrates that image characteristic information is a co-occurrence matrix according to an embodiment of the present invention.
7 illustrates that image characteristic information is a local binary pattern according to an embodiment of the present invention.
8 shows that image characteristic information is uniform according to an embodiment of the present invention.
9 is a flowchart illustrating a method of rendering and displaying a 3D image in which characteristic information of an object is reflected according to an embodiment of the present invention.
10 is a flowchart illustrating a method for generating an image in which characteristic information on a window region of an object is reflected according to an embodiment of the present invention.
11 is a flowchart illustrating a method of generating an image for a window region based on generated characteristic information according to an embodiment of the present invention.
12 is a flowchart illustrating a method of generating an image for a window region based on generated characteristic information according to another embodiment of the present invention.
13 is a block diagram illustrating an apparatus for generating a 3D image in which characteristic information of an object is reflected according to an embodiment of the present invention.
14 is a block diagram illustrating an apparatus for generating an image in which characteristic information on a window region of an object is reflected, according to an embodiment of the present invention.
15 is a block diagram illustrating an apparatus for generating an image in which characteristic information on a window region of an object is reflected, according to another embodiment of the present invention.
16 and 17 are diagrams for explaining a reflected light effect among characteristic information of an object according to an embodiment of the present invention.
18 is a diagram for explaining a method for obtaining the ultrasound image of FIGS. 16 and 17 .
19 is a diagram illustrating an image in which characteristic information on a window region of an object is reflected differently according to a specular light index according to an embodiment of the present invention.
20 is a diagram illustrating an image in which characteristic information on a window region of an object is reflected differently according to a specular light index according to an embodiment of the present invention.
FIG. 21 is a diagram illustrating changes in an image according to a specular light index and a specular reflection coefficient.
22 is a diagram illustrating an ultrasound image showing a reflected light effect when there are two light sources according to an embodiment of the present invention.
23 is a flowchart illustrating a 3D specular light effect rendering method according to an embodiment of the present invention.
24 is a diagram illustrating a method of calculating a reflected light vector through a normal vector.
25 is a flowchart illustrating a 3D specular light effect rendering method according to an embodiment of the present invention.
26 is a flowchart illustrating a 3D specular light effect rendering method according to an embodiment of the present invention.
27 to 29 are diagrams for explaining a method of calculating surface information of an object.

Terms used in this specification will be briefly described, and the present invention will be described in detail.

The terms used in the present invention have been selected as currently widely used general terms as possible while considering the functions in the present invention, which may vary depending on the intention or precedent of a person skilled in the art, the emergence of new technology, and the like. In addition, in a specific case, there is a term arbitrarily selected by the applicant, and in this case, the meaning will be described in detail in the description of the corresponding invention. Therefore, the term used in the present invention should be defined based on the meaning of the term and the overall content of the present invention, rather than the name of a simple term.

In the entire specification, when a part "includes" a certain element, this means that other elements may be further included, rather than excluding other elements, unless otherwise stated. In addition, terms such as "...unit" and "module" described in the specification mean a unit that processes at least one function or operation, which may be implemented as hardware or software, or a combination of hardware and software. .

Throughout the specification, the term “ultrasound image” refers to an image of an object obtained using ultrasound. The object may refer to a part of a body. For example, the object may include organs such as a liver, heart, uterus, brain, breast, abdomen, or a fetus.

Throughout the specification, the term “medical image” refers not only to an image of an object obtained using ultrasound, but also to an X-ray diagnostic device, a computerized tomography (CT) scanner, a magnetic resonance image (MRI) device, and a nuclear medicine diagnostic device. It may mean an image of an object.

Throughout the specification, a "user" may be a medical professional, such as a doctor, a nurse, a clinical pathologist, or a medical imaging specialist, but is not limited thereto.

Throughout the specification, “voxel” may mean a minimum unit of a 3D image image, but is not limited thereto.

Hereinafter, with reference to the accompanying drawings, the embodiments of the present invention will be described in detail so that those of ordinary skill in the art can easily implement them. However, the present invention may be embodied in several different forms and is not limited to the embodiments described herein. And in order to clearly explain the present invention in the drawings, parts irrelevant to the description are omitted, and similar reference numerals are attached to similar parts throughout the specification.

1 shows an ultrasound image and a 3D rendered image of an object.

The ultrasound 3D function has been used for fetal diagnosis until recently, but recently, it has been developed into a technology capable of producing effects such as imaging of the digestive tract through an endoscope without actually using an endoscope.

For example, if the ultrasound 3D function is used, the internal structure of the digestive system may be easily identified using ultrasound data of the digestive system including the stomach and the like and a 3D volume rendering technique.

However, since the 3D ultrasound function performs 3D volume rendering using only structural information displayed in the ultrasound image of the object, there is a problem in that characteristics (eg, texture) of the object cannot be accurately expressed.

For example, as shown in FIG. 1 , if there is a sediment 20 (eg, a bundle of noodles attached to the stomach, etc.) in the object (eg, the stomach of a patient), the sediment 20 is the ultrasound image 10 . It may appear darker or brighter than surrounding tissues. If a predetermined region 11 is selected from the ultrasound image 10 for precise observation of the sediment 20 and rendering is performed on the selected region, the sediment 20 in the object is displayed as if in the rendered image 30 . It may appear like a polyp (31).

According to this method, an error of rendering the sediment 20 like a polyp may occur because rendering is performed using only the structure information of the object while ignoring the properties of the tissue and sediment 20 of the object, and accordingly, the user may lead to erroneous clinical judgment.

In a two-dimensional (2D) ultrasound image of an object, the sediment 20 and the like may have different brightness and texture compared to the surrounding tissue, so according to an embodiment of the present invention, the sediment 20 and the like may have different characteristics. Thus, by performing 3D volume rendering, a 3D image in which characteristics of an object are reflected may be provided to the user.

When the apparatus or method for generating a 3D image according to an embodiment of the present invention generates a 3D image of an object through acquired ultrasound data, the 3D image of the object is different in a portion having different characteristic information of the acquired ultrasound data. A three-dimensional image of the object may be generated to be expressed in a realistic manner. For example, if the sediment 20 in FIG. 1 has characteristic information different from that of the surrounding tissue, the sediment 20 may be expressed differently from the surrounding tissue even in a 3D image.

In the 3D image generating apparatus or method according to an embodiment of the present invention, if the characteristic information of ultrasound data is different, the 3D image of the object may be different. Here, the characteristic information may include at least one of image characteristic information, physical property information, and surface information. The characteristic information will be described in detail below.

2 is a flowchart illustrating a method for generating a 3D image in which characteristic information of an object is reflected according to an embodiment of the present invention.

A method for generating a three-dimensional image in which characteristic information of an object is reflected according to an embodiment of the present invention includes: acquiring ultrasound data for the object (S10); generating characteristic information of the object from the acquired ultrasound data; (S20) and generating a 3D image of the object based on the generated characteristic information (S30).

The ultrasound data according to an embodiment of the present invention may include an ultrasound response signal received from an object irradiated with ultrasound. The ultrasonic response signal may include at least one of an analog signal and a digital signal.

For example, the ultrasound data may include an ultrasound response signal obtained from an object that may be expressed in units of voxels. In other words, the ultrasound data may include amplitude and phase values of a response ultrasound in which ultrasound transmitted toward the object through the probe passes through the object and returns to the probe.

The attribute information of the object according to an embodiment of the present invention may include image characteristic information of the object, information on physical properties of the object, surface information of the object, and the like.

Image characteristic information includes ultrasound such as spatial frequency, image intensity, image histogram, co-occurrence matrix, local binary pattern, and homogeneity of an ultrasound image of an object. It may include at least one of the characteristic information of the image.

The uniformity of the object refers to a degree of change in the size and shape of at least one particle included in the object. For example, if the size or shape of at least one particle (or tissue) included in the object is varied, uniformity of the object is absent or very low. Also, if the size or shape of at least one particle (or tissue) included in the object is the same, it means that the object has very high uniformity.

Physical property information of an object includes strength, hardness, elasticity, plasticity, viscosity, density, ductile, brittleness, malleability, It may include information indicating a physical property of the object, such as rigidity and toughness.

The surface information of the object may include information for indicating the surface properties of the object that can be felt through a human tactile recognition organ, such as 'smooth', 'rough', 'rough', 'soft', and the like.

In addition, the surface information of the object includes information for indicating the visual or three-dimensional properties of the object that can be felt through the human visual organ, such as contrast between light and dark, 'separation or division between the entire background and a predetermined object' can do.

The attribute information of the object may be information on each pixel constituting an image, or information on each of one or more regions constituting an image. Also, the attribute information of the object may refer to information about a frame of an image.

The ultrasound image of the object may be at least one of a B-mode (brightness mode) image, a C-mode (color mode) image, and a D-mode (Doppler mode) image. Also, according to an embodiment of the present invention, the ultrasound image may be a 2D image or a 3D image of an object.

According to an embodiment of the present invention, the step of extracting characteristic information from the acquired ultrasound data ( S20 ) may include spatial frequency, image intensity, image histogram, co-occurrence matrix, and local frequency based on an ultrasound image generated according to an ultrasound response signal. obtaining one of a binary pattern and uniformity.

According to an embodiment of the present invention, the step of extracting characteristic information from the acquired ultrasound data (S20) may include analyzing the image characteristic information and determining characteristic information of the object based on the analysis result. .

Analysis and determination of image characteristic information will be described later with reference to FIGS. 3 to 8 .

3 shows that image characteristic information is a spatial frequency according to an embodiment of the present invention.

The spatial frequency is a concept for representing the rate at which pixel values change in the horizontal or vertical direction on a screen displaying an image. For example, when the pixel value changes slowly (or the pixel value hardly changes) or the correlation of objects included in the image is high, the spatial frequency is low. Conversely, when the change in the pixel value is extreme (or the change in the pixel value is discontinuous like an edge) or the correlation of objects included in the image is low, the spatial frequency is high.

An ultrasound image 40 or 50 of the object may be acquired as shown in FIG. 3 . Also, the ultrasound image 40 or 50 of the object may be an ultrasound image of a portion of the ultrasound image 10 of the object (eg, a portion corresponding to the predetermined selected region 11 ) as shown in FIG. 1 .

For example, the sizes of the tissues 41 , 42 , and 43 of the object may be different from each other. Here, the tissue may refer to particles of biological organs or particles of sediment constituting the object. The object may include the largest tissue 42 , the medium-sized tissue 43 , and the smallest tissue 41 . Also, the shapes of the tissues 41 , 42 , and 43 of the object may be different from each other.

Also, the brightness values of the tissues 41 , 42 , and 43 of the object may be different from each other. For example, the object may include a tissue 43 appearing brightest in the ultrasound image 40 or 50 , a tissue 42 exhibiting an intermediate brightness, and a tissue 41 appearing the darkest in the ultrasound image 40 or 50 . Since different ultrasound response signals may be generated according to the depth, density, elasticity, etc. of the tissue, different tissues may exhibit different brightness values. For example, the deepest tissue 41 may appear the darkest. In other words, as the depth of the tissue increases, the brightness value may appear gradually smaller.

The brightness values of the plurality of pixels included in the k-th line from the top of the first ultrasound image 40 may be expressed as amplitude values of the pixels as shown in FIG. 3 . For example, tissue 42 exhibiting moderate brightness may be represented as a pixel amplitude value of 0.5. Also, the darkest appearing tissue 41 can be expressed as a pixel amplitude value of -1.

In addition, the brightness values of the plurality of pixels included in the k-th line from the top of the second ultrasound image 50 corresponding to the first ultrasound image 40 may also be expressed as amplitude values of the pixels. The second ultrasound image 50 includes tissues 51 having the same size and the same brightness value. Accordingly, when the brightness value is expressed along the k-th line, it can be expressed to have a pixel amplitude value of 1 as shown in FIG. 3 .

The brightness values of pixels along the same k-th line show different aspects in the first ultrasound image 40 and the second ultrasound image 50 . In other words, in the first ultrasound image 40 , the pixel amplitude value (or the pixel brightness value) varies from -1 to 0.5, whereas in the second ultrasound image 50, the pixel amplitude value varies from 0 to 1. just do it

In the above-described example, since the pixel amplitude value of the first ultrasound image 40 has a large change, it may be determined that the spatial frequency is high. In other words, the correlation between the tissues 41 , 42 , and 43 included in the first ultrasound image 40 is low, and therefore it is assumed that the object of the first ultrasound image 40 has 'ragged' or 'rough' characteristics. can be decided.

Also, since the pixel amplitude value of the second ultrasound image 50 hardly changes compared to the first ultrasound image 40 , it may be determined that the spatial frequency is low. In other words, the correlation between objects (eg, tissues 51 ) included in the second ultrasound image is very high, and therefore it may be determined that the object of the second ultrasound image 50 has 'smooth' or 'soft' characteristics. there is.

As described above, the spatial frequency of the ultrasound image may be extracted as the characteristic information, and the characteristic information of the object may be determined (or acquired) based on the spatial frequency.

4 shows that image characteristic information is image intensity according to an embodiment of the present invention.

Image intensity according to an embodiment of the present invention may be expressed as a brightness value of a plurality of pixels of an ultrasound image of an object.

As shown in FIG. 4 , a plurality of tissues 41 to 43 having brightness values included in different ranges (eg, the first section 401 to the third section 403 ) appear in the first ultrasound image 40 . can Also, a tissue 51 having a brightness value in the same range (eg, the third section 403 ) may appear in the second ultrasound image 50 .

In other words, in the first ultrasound image 40 , the tissue 41 having a brightness value included in the first section (eg, dark section) 401 is included in the second section (eg, medium brightness section) 402 . Since it includes the tissue 42 having the brightness value obtained and the tissue 43 having the brightness value included in the third section (eg, the bright section) 403 , the tissues included in the first ultrasound image 40 ( 41 to 43) can be determined to be heterogeneous tissues. Also, even if the tissues 41 to 43 are the same type of tissue, since the brightness value sections of the tissues 41 to 43 are different, it may be determined that the depths of the tissues 41 to 43 are different, respectively.

Accordingly, the object of the first ultrasound image 40 may be determined to have a 'rough' or 'rough' characteristic.

On the other hand, since the second ultrasound image 50 includes the tissue 51 having the brightness value included in the third section (eg, the bright section) 403 , the second ultrasound image 50 is a single tissue ( 51) can be determined.

Therefore, the object of the second ultrasound image 50 may be determined to have a 'smooth' or 'soft' characteristic.

5 shows that the image characteristic information is an image histogram according to an embodiment of the present invention.

According to an embodiment of the present invention, an image histogram of an ultrasound image 40 or 50 of an object may be obtained as image characteristic information as shown in FIG. 5 .

An image histogram of the ultrasound image 40 or 50 indicates the number of pixels for a pixel value (eg, a brightness value, etc.) of the ultrasound image.

As shown in FIG. 5 , a plurality of tissues 41 to 43 having different brightness values may appear in the first ultrasound image 40 . The number of pixels according to the pixel values of the first ultrasound image 40 may be evenly distributed among pixel values 0 to 192 .

4 and 5 , the number of pixels having a brightness value included in the first section 401 is the first graph 501 , and the number of pixels having a brightness value included in the second section 402 is the second graph 501 . The number of pixels having a brightness value included in the second graph 503 and the third section 403 may be displayed on the image histogram as the third graph 505 .

Accordingly, the tissues 41 to 43 included in the first ultrasound image 40 may be determined to be heterogeneous tissues having various brightness values. Also, even if the tissues 41 to 43 are the same type of tissue, since the histogram distribution of the tissues 41 to 43 appears relatively wide, it may be determined that the depths of the tissues 41 to 43 are different, respectively.

Therefore, it may be determined that the object of the first ultrasound image 40 has a 'ragged' or 'rough' characteristic.

Also, tissues 51 having the same or similar brightness values may appear in the second ultrasound image 50 . 4 and 5 , on the image histogram of the second ultrasound image 50 , only the number of pixels having a brightness value included in the third section 403 may be displayed as the fourth graph 502 , so that the second The ultrasound image 50 may be determined to include single tissues 51 .

Therefore, the object of the second ultrasound image 50 may be determined to have a 'smooth' or 'soft' characteristic.

6 illustrates that image characteristic information is a co-occurrence matrix according to an embodiment of the present invention.

A co-occurrence matrix may be used to determine the repeatability of pixel values. For example, when there are many values corresponding to a predetermined pattern, it may be determined that the repeatability of the pattern is high.

For convenience of explanation, as shown in FIG. 6 , the brightest tissue 43 has a brightness value of 3, the medium-brightness tissue 42 has a brightness value of 2, and the darkest tissue 41 has a brightness value of 0. When expressed as , the first ultrasound image 40 may be simply expressed as a matrix 610 having a size of 4x4.

With respect to the matrix 610 indicating the pixel values of the first ultrasound image 40 , the co-occurrence matrix 630 may be obtained by using a pattern interpreted as a unit of a horizontal distance between pixels of 1 . However, the analysis of the pattern between the pixels is not necessarily limited to only the horizontal direction, and may be performed in a vertical direction, a diagonal direction, or the like.

For example, if there are pixel values 611 side by side in a horizontal pattern of (1, 0), the element of (1, 0) in the element 631 of the matrix corresponding to the pattern of (1, 0) is 3, which is the number of patterns, is displayed. The co-occurrence matrix 630 may be obtained by respectively indicating the number of patterns corresponding to each element of the matrix.

In addition, by expressing the brightness value of the tissue 51 included in the second ultrasound image 50 as 3, the second ultrasound image 50 may also be simply expressed as a matrix 620 having a size of 4x4. The co-occurrence matrix 640 for the second ultrasound image 50 may also be obtained in the same manner as the co-occurrence matrix 630 for the first ultrasound image 40 .

In the simultaneous occurrence matrix 640 for the second ultrasound image 50 , a value may appear intensively in a specific element 641 of the matrix 640 . In other words, since the pattern of (1,1) is repeated six times in the second ultrasound image 50, the element 641 of the matrix corresponding to the pattern of (1, 1) can be expressed as a value of 6. there is.

Comparing the co-occurrence matrix 630 for the first ultrasound image 40 and the co-occurrence matrix 640 for the second ultrasound image 50, values are concentrated on specific elements in the co-occurrence matrix 640 This is expressed as a relatively monotonous matrix because the repeatability of a predetermined pattern (eg, (1,1) or (3,3)) appears to be high in the second ultrasound image 50 .

Since the repeatability of the pattern of the second ultrasound image 50 is high, it may be determined that the object of the second ultrasound image 50 has a relatively 'smooth' or 'soft' characteristic compared to the object of the first ultrasound image 40 . can

7 shows that the image characteristic information extracted according to an embodiment of the present invention is a local binary pattern (LBP).

The local binary pattern is a technique for determining the similarity between pixels by expressing the difference between a pixel value of a current position and a neighboring pixel value in a binary form of 0 and 1. In other words, by obtaining an LBP histogram expressing the difference between neighboring pixels included within a predetermined radius for each pixel of the image as a binary value, and comparing a plurality of binary expression values obtained based on each pixel The similarity between pixels may be determined.

A high degree of similarity between pixels indicates that the pixels have the same feature. For example, pixels having a high similarity may have the same or similar brightness values. Therefore, it is possible to estimate the image pattern relatively accurately by using the local binary pattern technique.

As shown in FIG. 7 , a 3x3 matrix 710 centered on a predetermined element 711 is selected from the matrix 610 indicating pixel values of the first ultrasound image 40 , and the pixel of the element 711 is selected. A binary representation matrix 730 may be obtained by representing a value of 1 as 1 when a neighboring pixel has a higher or equal pixel value based on the value 1, and representing it as 0 when a pixel value is smaller than 1. By reading the values of each element in the clockwise direction from the element 711 in the binary representation matrix 730 , a binary value 750 '11101001' based on the pixel corresponding to the element 711 may be obtained. In this way, the binary value '11111111' may be obtained based on the element 712 .

In addition, a binary value 760 '00111110' may be obtained based on the matrix 720 centered on a predetermined element 721 in the matrix 620 indicating the pixel values of the second ultrasound image 50 . Also, a binary value '00111110' may be obtained based on the element 722 .

The binary values '11101001' and '11111111' obtained from the first ultrasound image 40 change rapidly, but the binary values '00111110' and '00111110' obtained from the second ultrasound image 50 change. there is no That is, compared to the first ultrasound image 40 , the change in pixel values between adjacent pixels in the second ultrasound image 50 is not large.

Since the second ultrasound image 50 has little change in pixel values between adjacent pixels, the object of the second ultrasound image 50 is relatively 'smooth' or 'soft' compared to the object of the first ultrasound image 40 . characteristics can be determined.

8 shows that image characteristic information is uniform according to an embodiment of the present invention.

The uniformity of the ultrasound image according to an embodiment of the present invention refers to the uniformity of the size or shape of the tissue 41 , 42 , 43 or 51 included in the ultrasound image 40 or 50 . For convenience of explanation, it is assumed that uniformity is expressed as a value of '10' when it is completely uniform, and uniformity is expressed as a value of '1' when it is not uniform.

The first ultrasound image 40 includes a plurality of tissues 41 to 43 having different sizes. Accordingly, it may be determined that the uniformity of the first ultrasound image 40 is low. For example, the uniformity of the first ultrasound image 40 may be expressed as a value of '1', and it may be determined that particles (or tissues) are uneven. In other words, the object of the first ultrasound image 40 may be determined to have a 'ragged' or 'rough' characteristic.

In contrast, the second ultrasound image 50 includes a plurality of tissues 51 having the same size. Therefore, it may be determined that the uniformity of the second ultrasound image 50 is relatively higher than that of the first ultrasound image. For example, the uniformity of the second ultrasound image 50 may be expressed as a value of '10', and it may be determined that particles (or tissues) are even. In other words, it may be determined that the object of the second ultrasound image 50 has a relatively 'smooth' or 'soft' characteristic compared to the object of the first ultrasound image 40 .

9 is a flowchart illustrating a method of rendering and displaying a 3D image in which characteristic information of an object is reflected, according to an embodiment of the present invention.

According to an embodiment of the present invention, generating a 3D image of an object based on the generated characteristic information (S30) may include rendering a 3D image of the object according to the characteristic information (S31). can

For example, a 3D image may be rendered using the characteristic information generated according to the method described above for the object. In other words, when 3D volume rendering of the object is performed, the structure of the object is obtained by using characteristic (eg, texture, etc.) information corresponding to each pixel obtained (or determined) through the analysis of the above-described image characteristic information. In addition, it is possible to obtain a 3D volume image in which characteristics such as the texture of the object are reflected.

In addition, the method according to an embodiment of the present invention may further include displaying a 3D image generated by reflecting the characteristic information (S40).

10 is a flowchart illustrating a method for generating an image in which characteristic information on a window region of an object is reflected, according to an embodiment of the present invention.

According to an embodiment of the present invention, a method for generating an image in which characteristic information on a window region of an object is reflected includes acquiring an ultrasound image of an object based on ultrasound data of the object (S100), the acquired ultrasound It includes the steps of setting the window area in the image (S200), generating characteristic information of the window area from ultrasound data (S300), and generating an image of the window area based on the generated characteristic information (S400). can do.

According to an embodiment of the present invention, the step of setting the window region in the acquired ultrasound image (S200) may include selecting a predetermined region in the ultrasound image based on an external input (S210).

In addition, the window area according to an embodiment of the present invention may be automatically set as much as a preset area of a predetermined size including a predetermined portion (or region) of the object even if a separate external input is not applied. For example, a window area preset to a predetermined size to include the upper end or lower curved surface of the patient's stomach may be automatically set.

The image characteristic information according to an embodiment of the present invention may include at least one of a spatial frequency, an image intensity, an image histogram, a co-occurrence matrix, a local binary pattern, and a uniformity of an ultrasound image of an object, and the characteristic information is The texture of the object may be included.

11 is a flowchart illustrating a method of generating an image for a window region based on generated characteristic information according to an embodiment of the present invention.

According to an embodiment of the present invention, the step of generating an image of the window region based on the generated characteristic information (S400) includes the step of rendering a 3D image of the window region according to the generated characteristic information (S410). may include

As described above, when 3D volume rendering of an object is performed, by using characteristic information corresponding to each pixel obtained (or determined) through analysis of characteristic information, not only the structure of the object but also the texture of the object A three-dimensional volume image with characteristics reflected may be obtained.

12 is a flowchart illustrating a method of generating an image for a window region based on generated characteristic information according to another embodiment of the present invention.

According to an embodiment of the present invention, the step (S400) of generating an image of the window area based on the generated characteristic information includes the steps of rendering (S420) so that a three-dimensional image of the window area is obtained and the rendered three-dimensional (3D) image. It may include adding the generated characteristic information to the image (S440).

After obtaining a 3D image by performing 3D volume rendering on the window region, the 3D image in which the characteristic information is reflected may be obtained by adding characteristic information to the rendered 3D image.

In other words, a first image is generated by performing 3D volume rendering on the window area, a second image is generated based on characteristic information generated by extraction and analysis from ultrasound data corresponding to the window area, and the first image is generated. By overlapping the second image and the second image, characteristic information may be added to the rendered 3D image (eg, the first image). In addition, a 3D image to which the characteristic information is reflected may be obtained by adding the characteristic information filtered through a predetermined image processing filter or the like to the rendered 3D image.

13 is a block diagram illustrating an apparatus for generating a 3D image in which characteristic information of an object is reflected according to an embodiment of the present invention.

An apparatus 1300 for generating a 3D image in which characteristic information of an object is reflected according to an embodiment of the present invention includes an ultrasound data acquisition unit 1310 that acquires ultrasound data of the object, and an ultrasound data acquisition unit 1310 of the object from the acquired ultrasound data. It may include a characteristic information generator 1350 that generates characteristic information and an image generator 1370 that generates a 3D image of an object based on the generated characteristic information.

Also, the apparatus 1300 according to an embodiment of the present invention may further include a display unit 1390 for displaying the generated 3D image.

The characteristic information according to an embodiment of the present invention may include image characteristic information of at least one of spatial frequency, image intensity, image histogram, co-occurrence matrix, local binary pattern, and uniformity of the ultrasound image of the object. .

The characteristic information according to an embodiment of the present invention may include at least one of image characteristic information, physical property information of an object, and expression information.

The image generation unit 1370 according to an embodiment of the present invention may render a 3D image of the object according to the characteristic information generated by the characteristic information generation unit 1350 .

14 is a block diagram illustrating an apparatus for generating an image in which characteristic information on a window region of an object is reflected, according to an embodiment of the present invention.

An apparatus 1300 for generating an image in which characteristic information on a window region of an object is reflected according to an embodiment of the present invention includes an ultrasound data acquisition unit 1310 that acquires ultrasound data on the object, and the acquired ultrasound data. An ultrasound image acquisition unit 1320 for acquiring an ultrasound image of an object based on an ultrasound image acquisition unit 1320, a window region setting unit 1360 for setting a window region from the acquired ultrasound image, and characteristic information for generating characteristic information on a window region from ultrasound data It may include a generator 1350 and an image generator 1370 that generates an image of the window region based on the generated characteristic information.

The window area setting unit 1360 according to an embodiment of the present invention may automatically set the window area by a preset area of a predetermined size including a predetermined part (or part) of the object. Such a preset area may be previously stored in a storage unit (not shown). For example, a window area preset to a predetermined size to include the upper end or lower curved surface of the patient's stomach may be automatically set.

The apparatus 1300 according to an embodiment of the present invention may further include an external input receiving unit 1340 .

The window area setting unit 1360 may select a predetermined area from the ultrasound image obtained through the ultrasound image obtaining unit 1320 based on the external input received through the external input receiving unit 1340 .

The image characteristic information according to an embodiment of the present invention includes at least one of a spatial frequency, an image intensity, an image histogram, a co-occurrence matrix, a local binary pattern, and a uniformity of an ultrasound image of an object, and the characteristic information includes: It may include at least one of texture and uniformity of the object.

The image generating unit 1370 according to an embodiment of the present invention includes an image rendering unit 1371 that renders a 3D image of the window area according to the characteristic information generated through the characteristic information generating unit 1350 to be obtained. may include

15 is a block diagram illustrating an apparatus for generating an image in which characteristic information on a window area of an object is reflected, according to another embodiment of the present invention.

The image generating unit 1370 according to an embodiment of the present invention may be configured to perform an image rendering unit 1371 that renders a 3D image for a window region to be obtained and a characteristic information generating unit 1350 on the rendered 3D image through the It may include a characteristic information adding unit 1372 for adding the generated characteristic information.

Also, the image generation unit 1370 according to an embodiment of the present invention may generate a characteristic information image in which characteristic information is expressed based on the characteristic information generated by the characteristic information generation unit 1350 .

In other words, a 3D image is obtained by performing 3D volume rendering on the window region, and then, a 3D image to which the characteristic information is reflected may be obtained by adding characteristic information to the rendered 3D image.

The characteristic information adding unit 1372 is a 3D image rendered by superimposing the first image generated by the image rendering unit 1371 and the second image (eg, characteristic information image) generated through the image generation unit 1370 . Characteristic information may be added to (eg, the first image). Also, the characteristic information adding unit 1372 may include a predetermined image processing filter or the like. In other words, a 3D image in which the characteristic information is reflected may be obtained by filtering the characteristic information through a predetermined image processing filter or the like and adding it to the rendered 3D image.

16 and 17 are diagrams for explaining a reflected light effect among characteristic information of an object according to an embodiment of the present invention.

16 and 17 , the image shown in FIG. 16(c) may be generated by synthesizing the image of FIG. 16(a) and the image of FIG. 16(b). The reflected light effect as shown in FIG. 16(b) may vary depending on the material properties of the object.

For example, the device 1300 of FIG. 13 may acquire a 3D image as shown in FIG. 16( a ), and may acquire characteristic information corresponding to the image of FIG. 16( b ). Also, for example, the apparatus 1300 of FIG. 13 may generate an image as shown in FIG. 16(c) by adding the image as shown in FIG. 16(b) to the 3D image as shown in FIG. 16(a). Accordingly, the apparatus 1300 of FIG. 13 may additionally render the reflected light effect, which is characteristic information corresponding to the image of FIG. 16(b), to the 3D image as shown in FIG. 16(a).

An image as shown in FIG. 17(c) may be generated by synthesizing the image of FIG. 17(a) and the image of FIG. 17(b). The reflected light effect as shown in FIG. 17(b) may vary depending on the material properties of the object.

For example, the device 1300 of FIG. 13 may acquire a 3D image as shown in FIG. 17(a) and may acquire characteristic information corresponding to the image of FIG. 17(b). Also, for example, the apparatus 1300 of FIG. 13 may generate an image as shown in FIG. 17(c) by adding the image as shown in FIG. 17(b) to the 3D image as shown in FIG. 17(a). Accordingly, the apparatus 1300 of FIG. 13 may additionally render the reflected light effect, which is characteristic information corresponding to the image of FIG. 17(b), to the 3D image as shown in FIG. 17(a).

18 is a diagram for explaining a method for obtaining the ultrasound image of FIGS. 16 and 17 .

Referring to FIG. 18 , the reflected light effect may be generated through a 3D rendering process. Specular rendering that generates a specular light effect may be implemented as ray tracing rendering. Ray tracing rendering is a rendering method that applies a global lighting model. In other words, ray tracing rendering assumes that rays are emitted from the camera and traces the path of light in all pixels on the screen to calculate lighting effects by reflection, refraction, absorption and self-luminescence occurring on light and surfaces. way. In ray tracing rendering, a local lighting model is used to calculate the lighting effect caused by reflection between a light source and an object. Calculate the lighting effect by Specular Reflection. Among them, the specular light effect expresses a lighting effect that is particularly highlighted by the light specularly reflected from the surface. These highlights change in intensity depending on the camera's position.

The reflected light effect can be calculated through the following [Equation 1].

[Equation 1]

Co: color of pixel

Cp : Specular light color

Ks: Specular reflection coefficient

Os : Object Color

R : Reflection light vector

S : View vector

n: Specular Reflection Exponent

The specular light color Cp may mean a color of light for giving a reflected light effect. The specular reflection coefficient Ks may mean a degree to which reflected light is reflected. The reflected light vector R may simultaneously indicate the direction and intensity of the reflected light. The gaze vector S may mean a unit vector with respect to the direction of the gaze.

If the direction of the reflected light vector (R) and the direction of the gaze vector (S) are matched in [Equation 1], it can be expressed as in [Equation 2].

That is, the reflected light effect can also be calculated through the following [Equation 2]. Assuming that the position and direction of the light source do not change, the position and direction of the light source can be regarded as the same as the camera position and direction.

[Equation 2]

Co: color of pixel

Cp : Specular light color

Ks: Specular reflection coefficient

Os : Object Color

Rz: The z-axis (View Plane origin) value of the reflection vector where light is reflected from the surface of the object.

N: specular light index

In addition, Cp (Specular light color), Ks (Specula reflection coefficient), and Os (Object Color) of [Equation 1] and [Equation 2] are spatial frequency and image intensity of the ultrasound data described with reference to FIGS. 3 to 8 . , image histogram, co-occurrence matrix, local binary pattern, and can be changed by characteristic information such as uniformity.

In addition, Cp (Specular light color), Ks (Specula reflection coefficient), Os (Object Color) of [Equation 1] and [Equation 2] are the average, variance, It can be changed according to characteristic information such as standard distribution, skewness, and kurtosis.

In addition, Cp (Specular light color), Ks (Specula reflection coefficient), and Os (Object Color) of [Equation 1] and [Equation 2] may be statistical values for a distance between voxels of an object.

19 is a diagram illustrating an image in which characteristic information on a window region of an object is reflected differently according to a specular light index according to an embodiment of the present invention.

Referring to FIG. 19, FIG. 19(a) is an ultrasound image of an object for a case in which the specular light index is 10 in [Equation 2], and FIG. 19(b) is a specular light index of 40 in [Equation 2] This is an ultrasound image of the object for the case of . Compared to the ultrasound image of FIG. 19(b) , the ultrasound image of FIG. 19( a ) has a small specular light index, and thus a highlight portion is widely distributed in the ultrasound image.

20 is a diagram illustrating an image in which characteristic information on a window region of an object is reflected differently according to a specular light index according to an embodiment of the present invention.

Referring to FIG. 20, FIG. 20(a) is an ultrasound image of an object when the specular reflection coefficient is 0.19 in [Equation 2], and FIG. 20(b) is a specular reflection coefficient of 0.5 in [Equation 2] This is an ultrasound image of the object for the case of . Compared to the ultrasound image of FIG. 20(b) , the ultrasound image of FIG. 20( a ) has a small specular reflection coefficient, and thus a highlight portion in the ultrasound image is relatively weak.

FIG. 21 is a diagram illustrating changes in an image according to a specular light index and a specular reflection coefficient.

Referring to FIG. 21 , it can be seen that the size of the reflected light increases as the specular reflection coefficient increases, and the size of the reflected portion is narrowly distributed as the specular light index increases.

22 is a diagram illustrating an ultrasound image showing a reflected light effect when there are two light sources according to an embodiment of the present invention.

Referring to FIG. 22 , FIG. 22( a ) is an ultrasound image when only one white light source is assumed. 22B is an ultrasound image when a white light source and a red light source are assumed together. In contrast to the ultrasound image of FIG. 22( a ), in the ultrasound image of FIG. 22( b ), it can be seen that the highlight is red.

When there are two light sources, the color of a pixel can be calculated as in [Equation 3].

[Equation 3]

In general, since the color of the object is the same, it can be calculated as in [Equation 4].

[Equation 4]

Co: color of pixel

Cp1 ~ Cpj : Specular light color of each light source

Ks1 ~ Ksj : specular reflection coefficient for each light source

Os1 ~ Osj : Object Color

Rz1 ~ Rzj : The z-axis value of the reflection vector that light is reflected from the surface of the object for each light source

n1 ~ nj : specular light index for each light source

In addition, [Equation 3] may be applied according to various embodiments. For example, in [Equation 3], when the color of the object and the reflection coefficient for the light source are the same, Ks1 to Ksj may have the same value.

23 is a flowchart illustrating a 3D specular light effect rendering method according to an embodiment of the present invention.

The image generator 1370 of FIG. 13 may generate an image by the method of FIG. 23 . Referring to FIG. 23 , the image generator 1370 may obtain a representative voxel V to be displayed on the screen among voxels in the path of the gaze vector projected from one point P on the screen ( S2100 ). The image generator 1370 may calculate a surface normal vector for the voxel V, and may calculate a reflected light vector through the normal vector (S2200).

The image generator 1370 may receive the specular light color Cp, the specular reflection coefficient Ks, and the color Os of the object as input from the user or internally calculate the specular light color (S2300). For example, the image generator 1370 uses the specular light color ( Cp), the specular reflection coefficient (Ks), and the color (Os) of the object may be calculated.

The image generator 1370 uses a specular light color (Cp), a specular reflection coefficient (Ks), an object color (Os), and a reflected light vector through [Equation 1] at a point P on the screen. The color (Co) of can be calculated.

The image rendering unit 1371 of FIG. 14 and the image rendering unit 1371 of FIG. 15 may generate an image by the method of FIG. 23 .

24 is a diagram illustrating a method of calculating a reflected light vector through a normal vector.

Referring to FIG. 24 , the image generator 1370 may calculate the reflected light vector V _reflect by Equation 5.

[Equation 5]

The image generator 1370 may calculate the reflected light vector V _reflect through the normal vector V _normal and the light source vector V _light through [Equation 5].

25 is a flowchart illustrating a 3D specular light effect rendering method according to an embodiment of the present invention.

The image generator 1370 of FIG. 13 may generate an image by the method of FIG. 25 . Referring to FIG. 25 , the image generator 1370 extracts a depth map for an object and a screen ( S3100 ). The image generator 1370 may calculate a surface normal vector and a reflection vector with respect to the depth map ( S3200 ). The image generator 1370 may receive the specular light color Cp, the specular reflection coefficient Ks, and the color Os of the object externally or calculate it internally (S3300). The image generator 1370 uses the specular light color (Cp), the specular reflection coefficient (Ks), the color (Os) of the object, and the reflected light vector through [Equation 2] at a point P on the screen. The color (Co) of can be calculated.

26 is a flowchart illustrating a 3D specular light effect rendering method according to an embodiment of the present invention.

The image generator 1370 of FIG. 13 may generate an image by the method of FIG. 26 . Referring to FIG. 26 , the image generator 1370 extracts a depth map for an object and a screen ( S4100 ). The image generator 1370 may calculate a surface normal vector and a reflection vector with respect to the depth map (S4200). The image generator 1370 may receive the specular light color Cp, the specular reflection coefficient Ks, and the color Os of the object externally or calculate it internally (S4300). The image generator 1370 uses the specular light color (Cp), the specular reflection coefficient (Ks), the color of the object (Os), and the reflected light vector through [Equation 3] or [Equation 4] to a point on the screen The color (Co) of the pixel in (P) can be calculated.

Meanwhile, the reflection light effect rendering method illustrated in FIGS. 24 to 26 may be a part of step S500 of FIG. 10 . The specular effect rendering method of FIGS. 24 to 26 may be implemented by the image generating unit 1370 of FIG. 13 , the image rendering unit 1371 of FIG. 14 , and the image rendering unit 1371 of FIG. 15 .

Also, the reflected light rendering method illustrated in FIGS. 24 to 26 may be implemented together with gray scale rendering and diffused light rendering. In addition, the specular light rendering method shown in FIGS. 24 to 26 is implemented independently of gray scale rendering and diffused light rendering, and may implement a completed image by combining the respective rendering images.

27 to 29 are diagrams for explaining a method of calculating surface information of an object.

Referring to FIG. 27 , when the surface of an object is expressed as a geometric model, it can be expressed in various ways, such as wave lines A to H. Each of the wavelines A to H has a baseline. The reference line is a line that serves as a reference for a wave expressed as a wave line. The reference line may be calculated through a smoothing technique and a line fitting technique using a wave line.

The higher the frequency of intersection of the wave line and the reference line, the rougher the surface. The lower the frequency of intersection of the wave line and the reference line, the smoother the surface. Accordingly, from the wavelines A to H, the closer the waveline to the A waveline is, the smoother the surface of the object can be, and the closer the waveline to the H waveline is, the more the rough surface of the object can be expressed.

Referring to FIG. 28 , surface information of an object may be calculated from a 2D image (or a cross section of 3D ultrasound volume data) through the concept of the wave line and the reference line of FIG. 27 . Meanwhile, in calculating the surface information of the object in the two-dimensional image, the wave line and reference line of FIG. 27 are not used, but various types of wave line and reference line may be used. For example, the baseline may be curved, as shown in FIG. 28 .

Referring to FIG. 29 , the wave plane and the reference plane may be defined by extending the wave line and the reference line of FIG. 27 to a 3D ultrasound volume. When the 2D image of FIG. 28 is expanded to 3D, the 3D image of FIG. 29 may be acquired. The method of calculating the surface information of the object according to an embodiment of the present invention may calculate the wave plane and the reference plane of the 3D image through the wave line and the reference line of the 2D image.

Regarding the apparatus according to an embodiment of the present invention, contents related to the above-described method may be applied. Accordingly, in relation to the apparatus, descriptions of the same contents as those of the above-described method are omitted.

Meanwhile, the above-described embodiments of the present invention can be written as a program that can be executed on a computer, and can be implemented in a general-purpose digital computer that operates such a program using a computer-readable recording medium.

The computer-readable recording medium includes a magnetic storage medium (eg, ROM, floppy disk, hard disk, etc.), an optically readable medium (eg, CD-ROM, DVD, etc.) and a carrier wave (eg, through the Internet). storage media such as transmission).

So far, the present invention has been looked at with respect to preferred embodiments thereof. Those of ordinary skill in the art to which the present invention pertains will understand that the present invention can be implemented in a modified form without departing from the essential characteristics of the present invention. Therefore, the disclosed embodiments are to be considered in an illustrative rather than a restrictive sense. The scope of the present invention is indicated in the claims rather than the foregoing description, and all differences within the scope equivalent thereto should be construed as being included in the present invention.

Claims (28)

A method for generating a three-dimensional image of an object, the method comprising:
acquiring ultrasound data for the object; and
generating a three-dimensional image of the object through the acquired ultrasound data;
The acquired ultrasound data has characteristic information including first characteristic information and second characteristic information,
The step of generating a three-dimensional image of the object comprises:
generating a first image of at least a portion of the acquired ultrasound data having the first characteristic information by using 3D volume rendering;
generating, as an image of at least a portion of the acquired ultrasound data, a second image having a reflected light effect according to the second characteristic information different from the first characteristic information; and
synthesizing the first image and the second image; A method comprising a. The method of claim 1, wherein the characteristic information includes at least one of image characteristic information, physical property information, and surface information about the object. The method of claim 1 , wherein the generating of the three-dimensional image of the object comprises generating the three-dimensional image of the object through at least one of a specular reflection coefficient, a specular light index, and a color of the object. The method of claim 1, wherein the generating of the 3D image of the object comprises rendering the 3D image of the object according to the characteristic information. The method of claim 1, further comprising displaying the generated 3D image of the object. delete The method of claim 1 , wherein the image having the reflected light effect is generated by a plurality of light sources. An apparatus for generating a three-dimensional image of an object, comprising:
an ultrasound data acquisition unit configured to acquire ultrasound data for the object; and
and an image generator for generating a three-dimensional image of the object through the acquired ultrasound data,
The acquired ultrasound data has characteristic information including first characteristic information and second characteristic information,
The image generator may generate a first image of at least a portion of the obtained ultrasound data having the first characteristic information by using 3D volume rendering, and an image of at least a portion of the obtained ultrasound data as a second image having a reflected light effect according to the second characteristic information different from the first characteristic information, and synthesizing the first image and the second image. . The apparatus of claim 8 , wherein the characteristic information includes at least one of image characteristic information, physical property information, and surface information about the object. The apparatus of claim 8 , wherein the image generator generates a 3D image of the object using at least one of a specular reflection coefficient, a specular light index, and a color of the object. The apparatus of claim 8 , wherein the image generator generates a 3D image of the object by rendering the 3D image of the object according to the characteristic information. The apparatus of claim 8, further comprising a display unit configured to display the generated 3D image. delete The apparatus of claim 8 , wherein the image having the reflected light effect is generated by a plurality of light sources. delete delete The method of claim 1, wherein the generating of the second image comprises:
calculating a representative voxel to be displayed on a screen among voxels in a path of a gaze vector;
calculating a surface normal vector;
calculating a reflected light vector through the surface normal vector;
generating a color of the object, a reflection coefficient for a light source, and a specular light index;
and calculating a color for one point included in the image through at least one of the reflected light vector, the color of the object, the reflection coefficient for the light source, and the specular light index. The method of claim 1, wherein the generating of the second image comprises:
extracting a depth map for an object and a screen;
calculating a surface normal vector for the depth map;
calculating a reflected light vector through the surface normal vector;
generating a color of the object, a reflection coefficient for a light source, and a specular light index;
and calculating a color for one point included in the image through at least one of the reflected light vector, the color of the object, the reflection coefficient for the light source, and the specular light index. The method of claim 1 , wherein the second image having the specular light effect is generated through a plurality of renderings including specular rendering. The method of claim 1 , wherein the second image having the reflected light effect is generated by a plurality of light sources. delete delete The apparatus of claim 8, further comprising a display unit configured to display the second image having the reflected light effect. The method of claim 8, wherein the image generator,
The color of the object, the reflection coefficient for the light source, and the specular light index are received from the outside of the device or calculated internally, and the color of the object, the reflection coefficient for the light source, and the specular light index are used through at least one of the An apparatus for calculating a color for a single point included in an image. The method of claim 8, wherein the image generator,
and extracting a depth map for the object and the screen, calculating a reflected light vector, and calculating a color for one point included in the image through the reflected light vector. delete The apparatus of claim 8 , wherein the second image having the specular light effect is generated through a plurality of renderings including specular rendering. delete

Images