JP2010005263A - Image processing device, ultrasonic diagnosing apparatus, and image processing program - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To promptly obtain an objective differential result of a liver tumor. <P>SOLUTION: When the differential diagnosis is required through an input part 11, a tumor region setting part 16a reads all ultrasonic images of an object for differential diagnosis out of an ultrasonic image memory part 15a and sets a liver tumor region for each object's ultrasonic image for differential diagnosis, and a classification determination part 16b determines to which the liver tumor whose region is set classified is of a primary liver cancer, metastatic liver cancer, or angioma in reference to classification opacification patterns memorized in a classification opacification pattern memory part 15b. A grade determination part 16c determines a grade of the primary liver cancer in reference to grade opacification patterns memorized in a grade opacification pattern memory part 15c, when the result by the classification determination part 16b is determined that the object is the primary liver cancer. A display control part 16d controls so that the classified result by the classification determination part 16b and the determined grade result by the grade determination part 16c could be displayed on an output part 12. <P>COPYRIGHT: (C)2010,JPO&INPIT

Description

  The present invention relates to an image processing apparatus, an ultrasonic diagnostic apparatus, and an image processing program.

  Conventionally, “malignant neoplasm (cancer)”, “heart disease” and “cerebral vascular disease (stroke)” are listed as one of the three major causes of death in Japan. In particular, cancer has the largest number of deaths among the three major causes of death, accounting for 30% of total deaths.

  When cancer is classified based on the site of occurrence, cancer patients in Japan are lung cancer, stomach cancer, colon cancer, and liver cancer in descending order of the number of patients. However, the 5-year relative survival rate in patients with gastric cancer and colon cancer is relatively high at around 60%, whereas the 5-year relative survival rate in patients with lung cancer and liver cancer is as low as around 18%. It is known that the prognosis for treatment of lung cancer and liver cancer is poor.

  Now, liver tumors that are tumors occurring in the liver are roughly classified into three types: primary liver cancer, metastatic liver cancer, and hemangioma. Primary liver cancer is a hepatocyte-derived malignant tumor, and metastatic liver cancer is a secondary malignant tumor that has occurred when cancer cells that have developed in other organs have spread to the liver. Liver cancer is considered to be a liver tumor that leads to liver cancer. On the other hand, hemangioma (hepatic hemangioma) is a benign tumor in which a large number of small and large blood vessels are intertwined. In some cases, follow-up is necessary.

  In addition, primary liver cancer has different malignancy depending on the degree of differentiation of hepatocytes that have become tumors (the degree of maturation of hepatocytes). Specifically, the smaller the number of divisions of hepatocytes at the time of tumor formation (the less advanced the differentiation from hepatic stem cells to hepatocytes), the higher the malignancy.

  Therefore, when a liver tumor is discovered, whether the discovered liver tumor falls under “primary liver cancer, metastatic liver cancer, or hemangioma”, and if the discovered liver tumor is primary liver cancer, In order to improve the prognosis of treatment for liver cancer, it is necessary to quickly identify the level of malignancy (degree of differentiation) and to develop a treatment plan based on the characteristics of liver tumors. .

  Therefore, research is being conducted to differentiate liver tumors by ultrasonic diagnosis using a contrast medium. Specifically, hepatic tumors are identified by a contrast echo method in which an ultrasound image is taken using microbubbles (microbubbles) that can be administered intravenously as an ultrasound contrast agent.

  In contrast echocardiography, blood flow signals are enhanced by microbubbles introduced into blood vessels, so doctors can clearly observe blood flow dynamics by referring to ultrasound images using contrast agents. Is possible. Furthermore, microbubbles have the property of being taken up by Kupffer cells in the liver via blood vessels and specifically phagocytosed, but in liver tumors, the degree of uptake of microbubbles is reduced because Kupffer cells are reduced from normal tissues. As a result, echo reflection due to microbubbles is a low signal in liver tumors. Therefore, the doctor can clearly observe the form of the liver tumor by referring to the ultrasonic image using the contrast agent.

  Here, the structures in the liver that are stained by the ultrasound contrast agent are roughly classified into blood vessels, portal veins, and liver parenchyma. The flow until the liver parenchyma is sequentially stained will be briefly described.

  First, since the injected contrast agent flows into the liver through the blood vessel, the blood vessel is stained (early vascular phase or arterial phase: about 40 seconds after the contrast agent injection). Then, since the contrast medium flows into the portal vein, the portal vein is shaded (late vascular phase or portal vein phase: a period centering about 90 seconds after the contrast agent injection). After that, the infused contrast agent is taken up by hepatocytes, the liver parenchyma is shaded, and the contrast agent in the blood vessel and portal vein is pushed away by the blood flow, so that the blood vessel and portal vein are not shaded ( Real phase: time around about 5 minutes after injection of contrast agent).

  In recent years, detailed analysis of the staining pattern along the time series from early vascular phase through late vascular phase to the parenchymal phase in liver tumors has been made. As a result, "primary liver cancer, metastatic liver cancer, hemangioma" It has been clarified that each liver tumor type has a specific tendency in the staining pattern along the time series (see, for example, Non-Patent Document 1). Furthermore, it has been clarified that in primary liver cancer, there is a specific tendency in the staining pattern along the time series according to the degree of differentiation (see, for example, Non-Patent Document 2).

  First, a staining pattern specific to the type of liver tumor will be described with reference to FIG. FIG. 11 is a diagram for explaining a staining pattern specific to the type of liver tumor. FIG. 11 schematically shows a surrounding staining pattern centering on the liver tumor, and the boundary between the liver tumor and the surrounding liver parenchyma is indicated by a solid line.

  As shown in FIG. 11, the staining pattern of primary liver cancer is the same as that of the liver tumor excluding the internal region in the parenchymal phase after the entire region of the liver tumor was gradually shaded from the early vascular phase to the late vascular phase. The liver parenchyma around the head and liver tumors tends to be stained.

  In addition, as shown in FIG. 11, the staining pattern of metastatic liver cancer is gradually stained after the region from the outside to the inside centering on the boundary of the liver tumor from the early vascular phase to the late vascular phase. However, the whole liver tumor is not shaded, and the liver parenchyma around the liver tumor tends to be shaded.

  In addition, as shown in FIG. 11, the staining pattern of the hemangioma is gradually shaded in the region other than the internal region of the liver tumor from the early vascular phase to the late vascular phase, and then excludes the internal region in the substantial phase. Part of the liver tumor and the liver parenchyma around the liver tumor tend to be stained.

  Next, a staining pattern specific to the degree of differentiation of primary liver cancer will be described with reference to FIG. FIG. 12 is a diagram for explaining a staining pattern specific to the degree of differentiation of primary liver cancer. FIG. 12 schematically shows the staining pattern in the liver tumor region when the liver tumor is primary liver cancer.

  In a liver tumor that is differentiated from primary liver cancer, in the case of a borderline lesion where the degree of differentiation of tumorized hepatocytes is high and malignant or benign, as shown in the A pattern of FIG. Early: no staining, late vascular phase: weak staining, substantial phase: weak staining.

  Further, in a liver tumor that is differentiated from primary liver cancer, when a well-differentiated hepatocyte becomes a malignant tumor, as shown in the B pattern of FIG. It tends to be a shadow.

  In addition, as the degree of differentiation of hepatocytes that have become tumors from the case of pattern B decreases (as the malignancy increases), a staining pattern as shown in the C, D, and E patterns in FIG. 12 is shown. That is, as shown in FIG. 12, in the C pattern, “early vascular phase: weak staining, late vascular phase: staining similar to the surrounding liver parenchyma, substantial phase: staining similar to the surrounding liver parenchyma. The D pattern having a lower degree of differentiation than the C pattern tends to be “early vascular phase: weak staining, late vascular phase: no staining, substantial phase: no staining”, and the D pattern. In the moderately differentiated E pattern with a lower degree of differentiation, there is a tendency to be “early vascular phase: strong staining, late vascular phase: weak staining, substantial phase: no staining”.

  That is, by comparing and interpreting the liver tumor staining pattern found by recent research results as shown in FIGS. 11 and 12 and the ultrasound image of the liver imaged by the ultrasound contrast agent, the doctor can , Liver tumors can be differentiated.

Differential diagnosis of hepatic neoplastic lesions using Levovist enhanced ultrasound. Rad Fan Vol. 2 No. 2: 62-65, 2004 Angiographic findings of hepatocellular carcinoma (HCC); Trial of differentiation degree diagnosis using Levovist. Rad Fan Vol. 2 No. 2: 66-68, 2004

  By the way, the above-described conventional technique has a problem that it is not possible to quickly obtain an objective liver tumor discrimination result.

  That is, in the above-described conventional technique, the doctor visually observes the ultrasonic images of the respective time phases displayed in parallel to determine the staining pattern in each time phase, and changes with the time series of the determined staining pattern Since the type of liver tumor is differentiated after grasping the combination, the discrimination results are not objective and the discrimination itself takes time.

  In addition, as shown in FIG. 12, when the liver tumor is primary liver cancer, there are various tendencies in the referenced staining pattern, and the objectivity of the discrimination result is also useful in visually identifying the malignancy of the primary liver cancer. The identification itself takes time.

  Therefore, the present invention was made to solve the above-described problems of the prior art, and an image processing apparatus, an ultrasonic diagnostic apparatus, and an ultrasonic diagnosis apparatus that can quickly obtain an objective liver tumor discrimination result, An object of the present invention is to provide an image processing program.

  In order to solve the above-described problems and achieve the object, the present invention according to claim 1 was photographed in time series based on the reflected wave of the ultrasonic wave transmitted to the subject administered with the contrast agent. An image processing apparatus that processes a plurality of ultrasound images, wherein the contrast pattern of the contrast agent along the time series of liver tumors in the ultrasound image is classified as a type of shadow pattern classified according to the type of liver tumor. Type pattern storage means for storing and liver tumors included in each of a plurality of discrimination target ultrasound images, which are a plurality of ultrasound images photographed in time series using the contrast agent in order to distinguish a liver tumor A liver tumor type that determines the type of liver tumor in which the region is set in the plurality of discrimination target ultrasonic images based on the type dyeing pattern stored by the type pattern storage unit after setting the region A constant section, the determination result by the liver tumor type determination means, characterized by comprising a display control means for controlling to display via a predetermined display unit.

  According to the fifth aspect of the present invention, there is provided an ultrasonic diagnosis for processing a plurality of ultrasonic images photographed in time series based on reflected ultrasonic waves transmitted to a subject administered with a contrast agent. A type pattern storage means for storing the contrast pattern of the contrast agent along the time series of liver tumors in an ultrasound image as a type of staining pattern classified for each type of liver tumor; and liver tumor A region of liver tumors included in each of a plurality of discrimination target ultrasound images that are a plurality of ultrasound images photographed in time series using the contrast agent, Liver tumor type determination means for determining the type of liver tumor in which a region is set in the discrimination target ultrasonic image based on the type shadow pattern stored by the type pattern storage means, and the liver tumor type determination means The determination result by, characterized by comprising a display control means for controlling to display via a predetermined display unit.

  According to a sixth aspect of the present invention, there is provided an image processing method for processing a plurality of ultrasonic images photographed in time series based on reflected ultrasonic waves transmitted to a subject administered with a contrast agent. Is a computer-executable image processing program, wherein the contrast agent staining pattern along the time series of liver tumors in an ultrasound image is stored as a predetermined staining pattern classified according to the type of liver tumor. Type pattern storage procedure stored in the part and the liver tumor in each of a plurality of discrimination target ultrasound images which are a plurality of ultrasound images taken in time series using the contrast agent in order to distinguish the liver tumor And determining the type of the liver tumor in which the region is set in the plurality of discrimination target ultrasonic images based on the type dyeing pattern stored in the predetermined storage unit A liver tumor type determination procedure that, the determination result by the liver tumor type determination procedure, characterized in that to execute a display control step of controlling to display via a predetermined display unit, to a computer.

  According to the first, fifth, or sixth aspect of the present invention, it is possible to quickly obtain an objective liver tumor discrimination result.

  Exemplary embodiments of an image processing apparatus, an ultrasonic diagnostic apparatus, and an image processing program according to the present invention will be described below in detail with reference to the accompanying drawings. In the following, an image processing apparatus that executes an image processing program according to the present invention will be described as an embodiment.

  First, the configuration of the image processing apparatus in this embodiment will be described. FIG. 1 is a diagram for explaining the configuration of the image processing apparatus according to the present embodiment. As shown in FIG. 1, the image processing apparatus 10 in this embodiment includes an input unit 11, an output unit 12, a communication unit 13, an input / output control I / F unit 14, a storage unit 15, and a processing unit 16. And is further connected to the ultrasonic diagnostic apparatus 20.

  The ultrasonic diagnostic apparatus 20 includes an ultrasonic probe containing an ultrasonic transducer in which a plurality of transducer cells are integrated. The ultrasonic probe transmits the ultrasonic wave generated from the ultrasonic transducer into the subject, and receives the reflected wave from the internal tissue of the subject in each transducer cell of the ultrasonic transducer. The ultrasonic diagnostic apparatus 20 captures an ultrasonic image based on the reflected wave of the ultrasonic wave received by the ultrasonic probe.

  Here, the ultrasonic diagnostic apparatus 20 is an apparatus capable of executing a contrast echo method for capturing an ultrasonic image using microbubbles (microbubbles) that can be administered intravenously as an ultrasonic contrast agent.

  The image processing apparatus 10 according to the present embodiment outlines processing a plurality of ultrasonic images along the time series captured by the ultrasonic diagnostic apparatus 20 for the liver of the subject to which the ultrasonic contrast agent is administered. The main feature is that it is possible to quickly obtain an objective liver tumor discrimination result.

  This main feature will be described with reference to FIGS. 2 to 9 together with FIG. FIG. 2 is a diagram for explaining the type staining pattern storage unit, FIG. 3 is a diagram for explaining the differentiation degree staining pattern storage unit, and FIG. 4 is a diagram explaining the tumor region setting unit. 5 is a flowchart for explaining the processing of the type determining unit, FIG. 6 is a diagram for explaining the type determining unit, and FIG. 7 is a modified example of the type determining unit. FIG. 8 is a diagram for explaining the differentiation degree determination unit, and FIG. 9 is a diagram for explaining the display control unit.

  In the following, while an ultrasound image is taken in time series by the ultrasound diagnostic apparatus 20, that is, after injecting an ultrasound contrast agent, the blood vessel is dyed early (arterial phase). Ultrasound probe during the late phase of the vascular phase (portal vein phase) where the portal vein is stained, and during the time when the liver parenchyma is stained and the blood vessels and portal vein are not stained (about 5 minutes) A case where the position of the liver of the subject in the ultrasonic image is fixed will be described. However, the present invention is applicable even when the position of the ultrasound probe is shifted and the position of the liver of the subject in the ultrasound image is not constant.

  The input unit 11 inputs various types of information and includes a mouse, a keyboard, and the like, and particularly as closely related to the present invention, an operator of the image processing apparatus 10 (for example, an ultrasonic image taken by the ultrasonic diagnostic apparatus 20) A differential request from a doctor who interprets a sound image and interprets a liver tumor is received and input.

  The output unit 12 outputs various types of information and includes a monitor, a speaker, and the like. Particularly, as closely related to the present invention, the processing results obtained by the type determination unit 16b and the differentiation degree determination unit 16c described later are displayed as described later. Based on the control by the control unit 16d, it is displayed on the monitor.

  The communication unit 13 communicates with other devices, and particularly as closely related to the present invention, receives and receives "a plurality of time-series ultrasonic images" from the ultrasonic diagnostic device 20. “Multiple ultrasonic images in time series” are transferred to the ultrasonic image storage unit 15a described later via the input / output control I / F unit 14.

  The input / output control I / F unit 14 controls data transfer between the input unit 11, the output unit 12, the communication unit 13, the storage unit 15, and the processing unit 16.

  The storage unit 15 stores data used for processing by the processing unit 16 and a processing result by the processing unit 16, and particularly as closely related to the present invention, as shown in FIG. 15a, a type staining pattern storage unit 15b, a differentiation degree staining pattern storage unit 15c, and a determination result storage unit 15d. Here, the type dyeing pattern storage unit 15b corresponds to “type pattern storage unit” recited in the claims, and the differentiation degree dyeing pattern storage unit 15c similarly corresponds to “differentiation degree pattern storage unit”. .

  The ultrasonic image storage unit 15 a stores “a plurality of ultrasonic images along time series” received from the ultrasonic diagnostic apparatus 20. Specifically, the ultrasound image storage unit 15a stores a plurality of ultrasound images along the time series captured by the ultrasound diagnostic apparatus 20 for the liver of a subject to which an ultrasound contrast agent has been administered.

  In the following, “a plurality of ultrasonic images along the time series taken by the ultrasonic diagnostic apparatus 20 for the liver of the subject administered with the ultrasound contrast agent” will be referred to as “a plurality of ultrasonic images along the time series”. "Ultrasonic image of".

  The type staining pattern storage unit 15b classifies the imaging pattern of the ultrasound contrast agent along the time series of the liver tumor in the ultrasound image for each type of liver tumor (primary liver cancer, metastatic liver cancer, and hemangioma). The type dyed pattern is stored.

  Specifically, the type-stained pattern storage unit 15b is disclosed in “Differential Diagnosis of Liver Tumor Lesions by Levovist-Contrast Ultrasound. Rad Fan Vol. 2 No. 2: 62-65, 2004”. A type staining pattern based on a staining pattern specific to the type of tumor is stored.

  Here, with reference to FIG. 2A, a description will be given of a staining pattern along a time series specific to the type of liver tumor. In FIG. 2A, the boundary between the liver tumor and the surrounding liver parenchyma in the ultrasound image is indicated by a solid line. In FIG. 2A, the surrounding staining pattern centering on the liver tumor is schematically shown along the time series from the early vascular phase to the late vascular phase.

  As shown in FIG. 2 (A), the staining pattern along the time series of primary liver cancer shows that after the entire region of the liver tumor is gradually stained from the early vascular phase to the late vascular phase, In this case, a part of the liver tumor excluding the internal region and the liver parenchyma surrounding the liver tumor are stained, and the pattern of metastatic liver cancer is expressed from the early vascular phase to the late vascular phase. After the area from the outside to the inside centered on the boundary is gradually shaded, in the parenchyma, the whole liver tumor is not shaded, it becomes a staining pattern in which the liver parenchyma around the liver tumor is shaded, The staining pattern of the hemangioma is that the region excluding the internal region of the liver tumor was gradually stained from the early vascular phase to the late vascular phase. The surrounding liver parenchyma is shaded The shadow pattern.

  Here, the staining pattern along the time series specific to the type of liver tumor shown in FIG. 2A is the average of the luminance values of the pixels in the region including the liver tumor in the ultrasound image (hereinafter, average). Patterning based on two parameters, the standard deviation of the luminance value of each pixel (hereinafter abbreviated as standard deviation) and the type of liver tumor as described below It can be expressed as a variation pattern along a specific time series.

  That is, when the liver tumor is primary liver cancer, as shown in FIG. 2B, the average luminance increases with time and becomes a stable variation pattern, and the standard deviation (variation of luminance values) is a small value. It becomes a fluctuation pattern that rises rapidly after transition. When the liver tumor is metastatic liver cancer, as shown in FIG. 2 (B), the average luminance increases with time and then decreases, and the standard deviation (pixel value variation) increases rapidly. After rising, it becomes a gradual rise and then a fluctuation pattern that declines. Further, when the liver tumor is an hemangioma, as shown in FIG. 2B, the average brightness and the standard deviation become a fluctuation pattern that is stable after increasing with time.

  Therefore, the type shadow pattern storage unit 15b uses, as the type shadow pattern, a variation pattern (graph) along the time series of the average luminance and standard deviation for each liver tumor type as shown in FIG. Remember.

  Note that the type staining pattern stored in the type staining pattern storage unit 15b is not limited to the graph as shown in FIG. 2B, and is a numerical value of average luminance and standard deviation for each type of liver tumor. May be a table in which is associated with time series.

  Returning to FIG. 1, the differentiation degree staining pattern storage unit 15c classifies the staining pattern of the ultrasound contrast agent along the time series of the primary liver cancer in the ultrasound image according to the differentiation degree of the primary liver cancer. It memorizes as a degree dyeing pattern.

  Here, there are four types of staining in the liver tumor by the ultrasound contrast agent: “no staining”, “weak staining”, “strong staining”, and “staining similar to the surrounding liver parenchyma”. When the classification is performed, the relationship between the average luminance and the standard deviation in the liver tumor included in the ultrasonic images of each of these four classification patterns is expressed as a map shown in FIG.

  That is, as shown in FIG. 3A, the map representing the relationship between the average luminance and the standard deviation is “average luminance: lowest, standard deviation: lowest” in “no staining”, and “weak staining”. “Average luminance: low, standard deviation: low to medium”, “strong luminance”, “average luminance: medium to high, standard deviation: medium to high”, “similar to the surrounding liver parenchyma” In “average luminance: highest, standard deviation: lowest”.

  Therefore, the differentiation degree staining pattern storage unit 15c is described in "Contrast findings of hepatocellular carcinoma (HCC); Trial of differentiation degree diagnosis using Levovist. Rad Fan Vol. 2 No. 2: 66-68, 2004". The disclosed staining patterns specific to the degree of differentiation of primary liver cancer are "no staining", "weak staining", "strong staining", and "staining similar to the surrounding liver parenchyma". The differentiation degree staining patterns represented by the four types of classification are stored, and the differentiation degree staining patterns are stored as variation patterns that are patterned based on two parameters of average luminance and standard deviation.

  That is, as shown in the pattern A of FIG. 3 (B), the differentiation degree staining pattern storage unit 15c sets the “vascular phase early” as a staining pattern when a liver tumor that is differentiated from primary liver cancer is a border lesion. The variation pattern of the average luminance and the standard deviation representing “: no staining, late vascular phase: weak staining, substantial phase: weak staining” is stored.

  Further, as shown in the B pattern of FIG. 3 (B), the differentiation degree staining pattern storage unit 15c has a “vascular phase early: weak staining, blood vessels” as a staining pattern in which highly differentiated hepatocytes have become malignant tumors. The variation pattern of average luminance and standard deviation representing “late phase: weak staining, substantial phase: weak staining” is stored.

  Further, as shown in the pattern C in FIG. 3B, the differentiation degree staining pattern storage unit 15c stains a hepatocyte having a low differentiation degree from the case of the pattern B as a malignant tumor. Variation pattern of average brightness and standard deviation representing “early vascular phase: weak staining, late vascular phase: similar level of staining to surrounding liver parenchyma, substantial phase: similar level of staining to surrounding liver parenchyma” as patterns Remember.

  Further, as shown in the pattern D in FIG. 3B, the differentiation degree staining pattern storage unit 15c performs staining in which hepatocytes having a low differentiation degree from the case of pattern C have become malignant. As the pattern, a variation pattern of average luminance and standard deviation representing “early vascular phase: weak staining, late vascular phase: no staining, substantial phase: no staining” is stored.

  Further, as shown in the E pattern in FIG. 3B, the differentiation degree staining pattern storage unit 15c converts the moderately differentiated hepatocytes from the pattern D into a malignant tumor. The variation pattern of the average luminance and the standard deviation representing “early vascular phase: strong staining, late vascular phase: weak staining, substantial phase: no staining” is stored as the stained pattern.

  The differentiation degree staining pattern stored in the differentiation degree staining pattern storage unit 15c is not limited to the graph for each pattern as shown in FIG. 3B, and corresponds to the differentiation degree of primary liver cancer. The table may be a table in which the numerical values of the average luminance and the standard deviation for each pattern are associated in time series.

  Returning to FIG. 1, the determination result storage unit 15 d stores determination results obtained by a type determination unit 16 b and a differentiation degree determination unit 16 c described later. The determination result storage unit 15d will be described in detail later.

  The processing unit 16 includes an internal memory for storing a control program such as an OS (Operating System), a program that defines various processing procedures, and necessary data, and executes various processes using these, and in particular, the present invention. As shown in FIG. 1, the information processing apparatus includes a tumor region setting unit 16a, a type determination unit 16b, a differentiation degree determination unit 16c, and a display control unit 16d. Here, the type determination unit 16b corresponds to the “liver tumor type determination unit” recited in the claims, the differentiation degree determination unit 16c similarly corresponds to the “differentiation degree determination unit”, and the display control unit 16d This also corresponds to “display control means”.

  The tumor region setting unit 16a includes a plurality of discrimination target super images that are a plurality of ultrasonic images photographed in time series using an ultrasonic contrast agent in order to distinguish the liver tumor stored in the ultrasonic image storage unit 15a. A region of a liver tumor included in each of the sound wave images is set. That is, the tumor region setting unit 16a reads out all the discrimination target ultrasound images that are the targets of the discrimination request input by the operator via the input unit 11, from the ultrasound image storage unit 15a, and stores them in each discrimination target ultrasound image. Set the area of the included liver tumor.

  Specifically, since it is ensured that the position of the ultrasound probe during imaging is fixed, the tumor region setting unit 16a can select one arbitrarily selected discrimination target as shown in FIG. Extract and set a liver tumor area whose brightness is lower than the surroundings in an ultrasound image (for example, an ultrasound image for discrimination immediately after administration of an ultrasound contrast agent), and By applying the coordinates to other discrimination target ultrasonic images, liver tumor regions in all the discrimination target ultrasonic images are set.

  The extraction and setting of the liver tumor region by the tumor region setting unit 16a may be performed for each of the plurality of discrimination target ultrasonic images.

  In the present embodiment, the case where the liver tumor region is automatically set by the image processing of the tumor region setting unit 16a has been described. However, the present invention is not limited to this, and the ultrasonic image storage unit 15a Each discrimination target ultrasonic image to be stored is displayed on a monitor provided in the output unit 12, and an operator of the image processing apparatus 10 referring to this sets the liver tumor region manually via the mouse of the input unit 11 or the like. It may be the case.

  Returning to FIG. 1, the type determination unit 16b determines whether the type of the liver tumor in which the region is set in the plurality of discrimination target ultrasound images by the tumor region setting unit 16a is primary liver cancer, metastatic liver cancer, or hemangioma. Whether or not it corresponds is determined based on the type dyeing pattern stored in the type dyeing pattern storage unit 15b (see FIG. 2B).

  Hereinafter, a specific example of the determination process by the type determination unit 16b will be described with reference to the flowchart shown in FIG.

  As shown in FIG. 5, when the tumor region setting unit 16a sets a liver tumor region in a plurality of discrimination target ultrasound images (Yes in step S501), the type determination unit 16b applies liver to each discrimination target ultrasound image. A center point of the tumor region is set (step S502).

  For example, as shown in FIG. 6A, the type determination unit 16b calculates the center of gravity of the liver tumor region set in the discrimination target ultrasound image, and sets the calculated center of gravity as the center point. Alternatively, the type determination unit 16b calculates and sets the center point by distance conversion based on the distance from the tumor region outer periphery.

  Then, the type determination unit 16b sets a plurality of circles centered on the center point set for each discrimination target ultrasound image (step S503).

  For example, as shown in FIG. 6A, the type determination unit 16b has three circles (circles 1, 3) at predetermined intervals around the center point of the liver tumor region set in the discrimination target ultrasound image. Set circle 2 and circle 3).

  A specific example of setting three circles will be described below. For example, the type determination unit 16b calculates the average value of the radius of the circle circumscribing the tumor region outer periphery and the radius of the circle inscribed in the tumor region outer periphery among the circles centered on the center point, and calculates the calculated average value. A circle with a radius is set as “circle 2”. Then, the type determining unit 16b sets, as “circle 1”, a circle whose radius is a value obtained by multiplying the radius of “circle 2” by a predetermined value (for example, “0.4”). Furthermore, the type determination unit 16b sets a circle having a radius that is a value obtained by multiplying the radius of “circle 2” by a predetermined value (for example, “1.2”) as “circle 3”.

  Then, the type determination unit 16b calculates an average luminance and a standard deviation (variation in luminance) of pixel values inside a plurality of circles set for each discrimination target ultrasonic image (step S504).

  The type determination unit 16b calculates a predetermined luminance in each of the discrimination target ultrasonic images when calculating the average luminance and the standard deviation for each of the three circles set in each of the plurality of discrimination target ultrasonic images along the time series. Set the reference brightness value. Then, the type determination unit 16b calculates the relative luminance value of the luminance value inside the circle set in the discrimination target ultrasonic image from the reference luminance value, calculates the average value of the relative luminance values as the average luminance, and calculates the relative luminance. Standard deviation is calculated from the value.

  That is, when the brightness and contrast of each discrimination target ultrasonic image are adjusted by the operators of the ultrasonic diagnostic apparatus 20 and the image processing apparatus 10, when the average luminance value is calculated from the absolute value of the luminance value, the discrimination target ultrasonic wave is calculated. It is not possible to accurately grasp the fluctuation pattern with the passage of time between images. For this reason, the type determination unit 16b, for example, in order to accurately grasp the variation pattern with the passage of time between the discrimination target ultrasound images, for example, the luminance value of the region away from the liver included in the discrimination target ultrasound image Set as a reference luminance value, and calculate a relative luminance value using the reference luminance value.

  Then, the type determination unit 16b acquires the staining patterns of the plurality of discrimination target ultrasonic images from the average luminance and the standard deviation calculated in each discrimination target ultrasonic image, and the acquired staining pattern and the type staining pattern. Pattern matching is performed with the type dyed pattern stored in the storage unit 15b (step S505).

  For example, the type determination unit 16b creates a graph showing the variation of the average luminance and standard deviation for each of the three circles calculated in each of the discrimination target ultrasound images, and each of the graphs of the circles 1, 2 and 3 and the type The pattern matching is performed with the type pattern stored in the type pattern storage unit 15b, that is, the variation pattern (graph) along the time series of the average luminance and standard deviation for each type of liver tumor.

  Then, the type determination unit 16b determines the type of the liver tumor included in the discrimination-target ultrasound image based on the pattern matching result (step S506), and ends the process.

  For example, as shown in FIG. 6 (B), the type determination unit 16b, among the acquired staining patterns (graphs) of the circle 1, the circle 2, and the circle 3, the staining pattern of the circle 2 and the primary liver cancer Therefore, the type of liver tumor included in the discrimination target ultrasound image is determined as “primary liver cancer”.

  The type determination unit 16b stores the type determination result of the liver tumor in the determination result storage unit 15d.

  Note that the liver tumor determination processing by the type determination unit 16b is not limited to pattern matching of the shape of the graph as described above, and there is the following method.

  That is, the type dyeing pattern storage unit 15b stores, as a type dyeing pattern, a table in which the numerical values of the average luminance and standard deviation for each type of liver tumor are associated in time series. Then, as shown in FIG. 7, the type determination unit 16b includes the inside of “circle 1, circle 2 and circle 3” set in the ultrasound image including the liver tumor in time series (discrimination target ultrasound image). Calculate the average brightness and standard deviation. Then, as shown in FIG. 7, the type determination unit 16b calculates the average luminance and standard deviation values of the type staining patterns corresponding to the time phases of the discrimination target ultrasonic images for which the average luminance and the standard deviation are calculated. The average brightness and standard deviation of the calculated “circle 1, circle 2 and circle 3” read from the table stored in the shadow pattern storage unit 15b are compared to determine which liver tumor type staining pattern is closest to.

  Then, the type determination unit 16b determines the type of the liver tumor included in the discrimination-target ultrasound image by, for example, majority determination by integrating the comparison determination results of the respective time phases.

  In the present embodiment, the case of determining the type of liver tumor based on the average luminance and standard deviation inside the set circle has been described, but the present invention is not limited to this, and the set circle is not limited to this. It may be a case where the type of liver tumor is determined based on the surrounding average brightness and standard deviation.

  Returning to FIG. 1, when the type of liver tumor included in each of the plurality of discrimination target ultrasonic images determined by the type determination unit 16b is the primary liver cancer, the differentiation degree determination unit 16c determines the primary liver cancer. The degree of differentiation is determined based on the degree of differentiation staining pattern stored in the differentiation degree staining pattern storage unit 15c.

  That is, the degree-of-differentiation determination unit 16c includes a variation pattern along a time series of average luminance and standard deviation calculated from the relative luminance values of pixels in primary liver cancer in which regions are set in a plurality of discrimination target ultrasound images, Differentiation of the primary liver cancer is performed by pattern matching the average brightness and standard deviation variation pattern (see FIG. 3B) for each differentiation degree of the primary liver cancer stored in the differentiation degree staining pattern storage unit 15c. Determine the degree.

  For example, as shown in FIG. 8A, the degree-of-differentiation determination unit 16c uses the circle 2 set by the type determination unit 16b, and calculates the average luminance and standard deviation around the circle 2 in time series. It calculates anew about each of several discrimination object ultrasonic image. Then, as shown in FIG. 8B, the differentiation degree determination unit 16c acquires a staining pattern (graph) from the calculated average luminance and standard deviation, and the acquired staining pattern and differentiation degree staining. By pattern matching with patterns (A to E patterns), the differentiation degree of primary liver cancer is determined as “C pattern”.

  In addition, the differentiation degree determination unit 16c stores the differentiation degree determination result of the primary liver cancer in the determination result storage unit 15d.

  Note that the differentiation degree determination process of the primary liver cancer by the differentiation degree determination unit 16c is not limited to the pattern matching of the shape of the graph as described above, but is modified in the liver tumor determination process by the type determination unit 16b. As described as an example, there are also the following methods.

  That is, the differentiation degree staining pattern storage unit 15c stores, as a type staining pattern, a table in which the numerical values of the average luminance and standard deviation for each differentiation degree of primary liver cancer are associated in time series, and the differentiation degree determination unit 16c The average brightness and standard deviation around the circle 2 are calculated. Then, the degree-of-differentiation determination unit 16c calculates the values of the average luminance and the standard deviation of the type-stained pattern corresponding to the time phase of the discrimination-target ultrasonic image for which the average luminance and the standard deviation are calculated, and the degree-of-differentiation staining pattern storage unit 15c A comparison is made as to which differentiation level of the shade pattern is closest to the calculated average luminance and standard deviation.

  Then, the differentiation degree determination unit 16c determines the differentiation degree of the primary liver cancer included in the discrimination-target ultrasound image by, for example, majority determination by combining the comparison determination results of the respective time phases.

  Returning to FIG. 1, the display control unit 16 d performs control so that the determination result by the type determination unit 16 b stored in the determination result storage unit 15 d is displayed on the monitor of the output unit 12. When the determination by the differentiation degree determination unit 16c is made, the display control unit 16d uses the differentiation degree determination unit 16c stored in the determination result storage unit 15d together with the determination result (primary liver cancer) by the type determination unit 16b. The determination result is also controlled to be displayed on the monitor of the output unit 12.

  For example, as shown in FIG. 9, the display control unit 16d includes all of the ultrasonic images to be differentiated, the liver tumor type is “primary liver cancer”, and the differentiation degree of the primary liver cancer is “C pattern”. Is displayed on the monitor.

  Next, processing of the image processing apparatus 10 in the present embodiment will be described with reference to FIG. FIG. 10 is a flowchart for explaining the processing of the image processing apparatus according to the present embodiment.

  As shown in FIG. 10, when the image processing apparatus 10 in the present embodiment receives a discrimination request from the operator via the input unit 11 (Yes in step S1001), the tumor region setting unit 16a becomes a target of the discrimination request. All of the plurality of discrimination target ultrasound images along the time series are read from the ultrasound image storage unit 15a, and a liver tumor region included in each discrimination target ultrasound image is set (step S1002).

  Then, the type determining unit 16b determines whether the type of the liver tumor in which the region is set in the plurality of discrimination target ultrasonic images by the tumor region setting unit 16a corresponds to primary liver cancer, metastatic liver cancer, or hemangioma. The determination is made with reference to the type image pattern stored in the type image pattern storage unit 15b (step S1003).

  Here, when the determination result by the type determination unit 16b is not primary liver cancer but metastatic liver cancer or hemangioma (No in step S1004), the display control unit 16d displays the determination result by the type determination unit 16b exceeding the discrimination target. Control is performed so that all the sound wave images are displayed on the monitor of the output unit 12 (step S1006), and the process ends.

  On the other hand, when the determination result by the type determination unit 16b is primary liver cancer (Yes at step S1004), the differentiation degree determination unit 16c stores the degree of differentiation of the primary liver cancer stored in the differentiation degree staining pattern storage unit 15c. The determination is made with reference to the dyed pattern (step S1005).

  After that, the display control unit 16d controls to display the determination result (primary liver cancer) by the type determination unit 16b and the determination result by the differentiation degree determination unit 16c on the monitor of the output unit 12 together with all the discrimination target ultrasonic images. (Step S1006), the process ends.

  As described above, in the present embodiment, the tumor region setting unit 16a reads all the plurality of discrimination target ultrasonic images along the time series that are subject to the discrimination request from the ultrasound image storage unit 15a, and performs the discrimination target. The liver tumor region included in each of the ultrasound images is set, and the type determination unit 16b determines that the type of the liver tumor in which the region is set in the plurality of discrimination target ultrasound images by the tumor region setting unit 16a is primary liver cancer, metastasis It is determined by referring to the type dyeing pattern stored in the type dyeing pattern storage unit 15b which corresponds to the metastatic liver cancer or hemangioma.

  When the determination result by the type determination unit 16b is primary liver cancer, the differentiation degree determination unit 16c refers to the differentiation degree staining pattern stored in the differentiation degree staining pattern storage unit 15c. Judgment. Then, the display control unit 16d outputs the type determination result by the type determination unit 16b and the differentiation level determination result by the differentiation level determination unit 16c when the type of the liver tumor is primary liver cancer, together with all the discrimination target ultrasonic images. Since it is controlled to be displayed on the monitor of the unit 12, it is not necessary to compare and interpret the staining pattern by visual observation of the operator, and the liver tumor differentiation is performed automatically without depending on the subjectivity or experience of the operator. Therefore, as described above, the objective liver tumor discrimination result can be quickly obtained.

  In this embodiment, the type determination and the degree of differentiation determination can be performed based on a plurality of objective parameters such as average luminance and standard deviation, so that an accurate discrimination result can be obtained.

  In addition, although the present Example demonstrated the case where the image processing apparatus 10 performed determination processing, such as a kind of liver tumor, with respect to the ultrasonic image image | photographed with the ultrasonic diagnostic apparatus 20, and displayed a determination result, The present invention is not limited to this, and the ultrasonic diagnostic apparatus 20 includes the function of the image processing apparatus 10 described in the present embodiment, and the type of liver tumor and the like for the ultrasonic image captured by itself. The determination process may be performed and the determination result may be displayed.

  Each component of each illustrated device is functionally conceptual and does not necessarily need to be physically configured as illustrated. In other words, the specific form of distribution / integration of each device is not limited to that shown in the figure, and all or a part thereof may be functionally or physically distributed or arbitrarily distributed in arbitrary units according to various loads or usage conditions. Can be integrated and configured. Further, all or any part of each processing function performed in each device may be realized by a CPU and a program analyzed and executed by the CPU, or may be realized as hardware by wired logic.

  As described above, the image processing apparatus, the ultrasound diagnostic apparatus, and the image processing program according to the present invention are photographed in time series based on the reflected wave of the ultrasound transmitted to the subject to which the contrast agent is administered. This is useful when processing a plurality of ultrasonic images, and is particularly suitable for quickly obtaining an objective liver tumor discrimination result.

It is a figure for demonstrating the structure of the image processing apparatus in a present Example. It is a figure for demonstrating a classification dyeing pattern memory | storage part. It is a figure for demonstrating a differentiation degree staining pattern memory | storage part. It is a figure for demonstrating a tumor area | region setting part. It is a flowchart for demonstrating the process of a classification determination part. It is a figure for demonstrating a classification determination part. It is a figure for demonstrating the modification of a classification determination part. It is a figure for demonstrating a differentiation degree determination part. It is a figure for demonstrating a display control part. 4 is a flowchart for explaining processing of the image processing apparatus according to the present exemplary embodiment. It is a figure for demonstrating the staining pattern specific to the kind of liver tumor. It is a figure for demonstrating the staining pattern specific to the differentiation degree of primary liver cancer.

Explanation of symbols

DESCRIPTION OF SYMBOLS 10 Image processing apparatus 11 Input part 12 Output part 13 Communication part 14 Input / output control I / F part 15 Storage part 15a Ultrasound image storage part 15b Type dyeing pattern memory part 15c Differentiation degree dyeing pattern memory part 15d Determination result memory part DESCRIPTION OF SYMBOLS 16 Processing part 16a Tumor area | region setting part 16b Type determination part 16c Differentiation degree determination part 16d Display control part 20 Ultrasound diagnostic apparatus

Claims (6)

An image processing apparatus for processing a plurality of ultrasonic images photographed in time series based on reflected ultrasonic waves transmitted to a subject administered with a contrast agent,
Type pattern storage means for storing the contrast agent staining pattern along the time series of the liver tumor in the ultrasound image as a type staining pattern classified for each type of the liver tumor,
After setting the region of the liver tumor included in each of a plurality of discrimination target ultrasound images that are a plurality of ultrasound images taken in time series using the contrast agent to differentiate the liver tumor, the relevant Liver tumor type determination means for determining the type of liver tumor in which regions are set in a plurality of discrimination target ultrasonic images based on the type shadow pattern stored by the type pattern storage means;
Display control means for controlling the determination result by the liver tumor type determination means to be displayed via a predetermined display unit;
An image processing apparatus comprising: The type pattern storage means stores a type staining pattern for each type of liver tumor consisting of primary liver cancer, metastatic liver cancer and hemangioma,
The liver tumor type determination means determines the type of liver tumor in which a region is set in the plurality of discrimination target ultrasonic images as one of primary liver cancer, metastatic liver cancer, or hemangioma. An image processing apparatus according to 1. A differentiation degree pattern storage means for storing the contrast pattern of the contrast agent along the time series of the primary liver cancer in an ultrasound image as a differentiation degree staining pattern classified according to the degree of differentiation of the primary liver cancer;
When the type of liver tumor included in each of the plurality of discrimination target ultrasonic images determined by the liver tumor type determination unit is the primary liver cancer, the differentiation degree pattern storage unit indicates the degree of differentiation of the primary liver cancer. And a differentiation degree determination means for determining based on the differentiation degree staining pattern stored by
The said display control means controls so that the determination result by the said differentiation degree determination means may be displayed via a predetermined | prescribed display part with the determination result by the said liver tumor classification determination means. Image processing apparatus. The type pattern storage means stores, as the type dyeing pattern, a variation pattern along a time series of an average value of pixel values and a standard deviation of pixel values in a liver tumor of an ultrasound image taken using the contrast agent. And
The degree-of-differentiation pattern storage means stores, as the degree-of-differentiation staining pattern, a variation pattern along the time series of an average value and a standard deviation of pixel values in primary liver cancer of an ultrasonic image taken using the contrast agent. And
The liver tumor type determination unit includes a variation pattern along a time series of an average value and a standard deviation of pixel values in the liver tumor in which regions are set in the plurality of discrimination target ultrasonic images, and the type pattern storage unit. Determine the type of liver tumor based on the type staining pattern stored,
The degree of differentiation determination means includes a variation pattern along a time series of an average value and a standard deviation of pixel values in the liver tumor as the primary liver cancer in which a region is set in the plurality of discrimination target ultrasonic images, 4. The image processing apparatus according to claim 3, wherein the degree of differentiation of primary liver cancer is determined based on the degree of differentiation dyeing pattern stored by the degree of differentiation pattern storage means. An ultrasound diagnostic apparatus that processes a plurality of ultrasound images taken along a time series based on reflected ultrasound waves transmitted to a subject administered with a contrast agent,
Type pattern storage means for storing the contrast agent staining pattern along the time series of the liver tumor in the ultrasound image as a type staining pattern classified for each type of the liver tumor,
After setting the region of the liver tumor included in each of a plurality of discrimination target ultrasound images that are a plurality of ultrasound images taken in time series using the contrast agent to differentiate the liver tumor, the relevant Liver tumor type determination means for determining the type of liver tumor in which regions are set in a plurality of discrimination target ultrasonic images based on the type shadow pattern stored by the type pattern storage means;
Display control means for controlling the determination result by the liver tumor type determination means to be displayed via a predetermined display unit;
An ultrasonic diagnostic apparatus comprising: An image processing program for causing a computer to execute an image processing method for processing a plurality of ultrasonic images photographed in time series based on reflected ultrasonic waves transmitted to a subject administered with a contrast agent. ,
Type pattern storage procedure for storing the contrast pattern of the contrast agent along the time series of the liver tumor in the ultrasound image in a predetermined storage unit as a type shadow pattern classified for each type of the liver tumor,
After setting the region of the liver tumor in each of a plurality of ultrasonic images to be differentiated that are a plurality of ultrasonic images taken in time series using the contrast agent in order to differentiate the liver tumor, the plurality A liver tumor type determination procedure for determining the type of the liver tumor in which the region is set in the discrimination target ultrasound image based on the type shadowing pattern stored in the predetermined storage unit;
A display control procedure for controlling the determination result of the liver tumor type determination procedure to be displayed via a predetermined display unit;
An image processing program for causing a computer to execute.

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