JP2018068814A - Image processing device, image processing method and image processing program - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide an image processing device which can estimate the level of the function of elements constituting an object with high accuracy while suppressing a load of processing.SOLUTION: An image processing device 1 includes: an element identification unit 102 which selects at least two sets of image sets formed of the first image and second image from a plurality of three-dimensional images obtained by photographing an object, and identifies elements constituting the object in each of the first image and second image; a first parameter acquisition unit 103 which acquires the first parameter expressing the ratio of change in the volume of the second image element identified in the second image with respect to the volume of the first image element identified in the first image for each image set; and a second parameter acquisition unit 104 which acquires the second parameter expressing the ratio of change of the first parameter with respect to the difference between the volume of the object in the first image constituting the image set and the volume of the object in the second image constituting the image set.SELECTED DRAWING: Figure 1

Description

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

  An image processing apparatus that processes a three-dimensional image in which a lung as an object is photographed is known (for example, Patent Document 1). The image processing apparatus specifies a predetermined approximate function that represents a change in Jacobian with respect to time of a displacement vector for each element constituting the lung, based on a plurality of three-dimensional images respectively acquired at a plurality of different time points. Get parameters. The approximate function includes the power of the cosine function.

  The image processing apparatus estimates the state of each element based on the acquired function specifying parameter. Thereby, the area | region where the function which performs ventilation among lungs is higher than another area | region can be pinpointed, for example. As a result, for example, in the case of irradiating the lung with radiation, the amount of radiation irradiated to the specified region can be suppressed, so that the ability of the lung to ventilate can be suppressed from decreasing.

Special table 2015-521880 gazette

  By the way, for example, when a three-dimensional image includes noise, the correlation between the Jacobian for an element and the height of the function of the element may be weak. The approximate function used by the image processing apparatus is a relatively complex function including a power of a cosine function. For this reason, the processing load for acquiring the function specifying parameter may be excessive.

  As described above, in the image processing apparatus, there is a possibility that the height of the function of the elements constituting the lung cannot be estimated with high accuracy while suppressing the processing load. This type of problem may occur as well when the object is different from the lung.

  One of the objects of the present invention is to estimate the height of the function of the elements constituting the object with high accuracy while suppressing the processing load.

In one aspect, the image processing apparatus includes:
Selecting at least two sets of images composed of a first image and a second image from a plurality of three-dimensional images, each of which is taken at a plurality of different points in time, with an object whose volume changes over time, An element specifying unit for specifying an element constituting the object in each of the first image and the second image constituting the at least two image sets;
The volume of the second image element that is the specified element in the second image that constitutes the image set with respect to the volume of the first image element that is the specified element in the first image that constitutes the image set A first parameter obtaining unit that obtains a first parameter representing a rate at which each of the at least two image sets is changed;
Represents the rate at which the first parameter changes with respect to the difference between the volume of the object in the first image constituting the image set and the volume of the object in the second image constituting the image set. A second parameter acquisition unit for acquiring a second parameter;
Is provided.

In another aspect, the image processing method includes:
Selecting at least two sets of images composed of a first image and a second image from a plurality of three-dimensional images, each of which is taken at a plurality of different points in time, with an object whose volume changes over time, The elements constituting the object are specified in each of the first image and the second image constituting the at least two image sets,
The volume of the second image element that is the specified element in the second image that constitutes the image set with respect to the volume of the first image element that is the specified element in the first image that constitutes the image set A first parameter representing a rate at which is changed for each of the at least two image sets;
Represents the rate at which the first parameter changes with respect to the difference between the volume of the object in the first image constituting the image set and the volume of the object in the second image constituting the image set. Obtain the second parameter.

In another aspect, the image processing program is
Selecting at least two sets of images composed of a first image and a second image from a plurality of three-dimensional images, each of which is taken at a plurality of different points in time, with an object whose volume changes over time, The elements constituting the object are specified in each of the first image and the second image constituting the at least two image sets,
The volume of the second image element that is the specified element in the second image that constitutes the image set with respect to the volume of the first image element that is the specified element in the first image that constitutes the image set A first parameter representing a rate at which is changed for each of the at least two image sets;
Represents the rate at which the first parameter changes with respect to the difference between the volume of the object in the first image constituting the image set and the volume of the object in the second image constituting the image set. The process for obtaining the second parameter is executed by the computer.

  The height of the function of the element which comprises a target object can be estimated with high precision, suppressing the processing load.

It is a figure showing the structure of the image processing apparatus of 1st Embodiment. It is a block diagram showing the function of the image processing apparatus of FIG. It is a graph showing the change with respect to time of lung volume. It is a graph showing the change with respect to the lung volume difference of the 1st parameter. 3 is a flowchart illustrating processing executed by the image processing apparatus in FIG. 1. It is a table | surface showing the correlation coefficient between the parameter acquired by the image processing apparatus of FIG. 1, or the image processing apparatus of a comparative example, and the parameter measured by the nuclear medicine test | inspection.

  Hereinafter, embodiments of the present invention relating to an image processing apparatus, an image processing method, and an image processing program will be described.

<First Embodiment>
(Overview)
The image processing apparatus according to the first embodiment is configured by a first image and a second image from a plurality of three-dimensional images, each of which is taken at a plurality of different time points, with an object whose volume changes over time. At least two image sets to be selected are selected, and elements constituting the object are specified in each of the first image and the second image constituting the at least two image sets. Further, the image processing apparatus uses the element specified in the second image constituting the image set to the volume of the first image element that is the element specified in the first image constituting the image set. A first parameter representing a rate at which a volume of a second image element changes is acquired for each of the at least two image sets. In addition, the image processing apparatus is configured to detect the difference between the volume of the object in the first image constituting the image set and the volume of the object in the second image constituting the image set. A second parameter representing the rate at which one parameter changes is acquired.

The second parameter has a strong correlation with a predetermined function of an element constituting the object. For example, when the object is the lung, the second parameter and the function of the element to perform ventilation have a strong correlation. Therefore, according to the said structure, the height of the function of an element can be estimated with high precision based on a 2nd parameter. Thus, according to the said structure, the height of the function of an element can be estimated with high precision, suppressing the processing load.
Hereinafter, the image processing apparatus according to the first embodiment will be described in more detail.

(Constitution)
As illustrated in FIG. 1, the image processing apparatus 1 according to the first embodiment includes a processing device 11, a storage device 12, an input device 13, an output device 14, and a communication device that are connected to each other via a bus BU. 15. In this example, the image processing apparatus 1 processes a plurality of three-dimensional images obtained by capturing an in-vivo target object at a plurality of different time points. Note that a plurality of three-dimensional images obtained by shooting the object at a plurality of different points in time may be represented as four-dimensional images. In addition, a three-dimensional image obtained by photographing an object in a living body may be represented as a medical three-dimensional image. Further, the image processing apparatus 1 may be represented as a medical image processing apparatus.

  In this example, the object is the lung. The object may be an organ other than the lung (for example, heart, brain, blood vessel, or the like).

  The processing device 11 controls the storage device 12, the input device 13, and the output device 14 by executing a program stored in the storage device 12. In this example, the processing device 11 is a CPU (Central Processing Unit). Note that the processing device 11 may include an MPU (Micro Processing Unit) or a DSP (Digital Signal Processor) instead of or in addition to the CPU. Further, the number of CPUs provided in the processing device 11 may be two or more.

  The storage device 12 stores a program in advance. The storage device 12 stores information generated as the processing device 11 executes the program. In this example, the storage device 12 includes at least one of RAM (Random Access Memory), ROM (Read Only Memory), semiconductor memory, organic memory, HDD (Hard Disk Drive), and SSD (Solid State Drive). .

  The image processing apparatus 1 may be an LSI (Large Scale Integration) circuit or a programmable logic circuit (for example, a programmable logic circuit (for example, instead of the processing apparatus 11 and the storage apparatus 12). A processing circuit such as PLD or FPGA) may be provided. PLD is an abbreviation for Programmable Logic Device. FPGA is an abbreviation for Field-Programmable Gate Array.

  The input device 13 inputs information from outside the image processing device 1. In this example, the input device 13 includes a keyboard and a mouse. Note that the input device 13 may include a microphone or a camera.

The output device 14 outputs information to the outside of the image processing device 1. In this example, the output device 14 includes a display. The output device 14 may include a speaker.
Note that the image processing apparatus 1 may include a touch panel display that forms both the input device 13 and the output device 14.

  The communication device 15 communicates with a device external to the image processing device 1. In this example, the communication device 15 is connected to an image generation device that generates a plurality of three-dimensional images in which a target in a living body is captured at a plurality of different time points, and a plurality of tertiary images are generated from the image generation device. Receive the original image. Note that the communication device 15 may be connected to the image generation device via a communication network. Further, the image processing apparatus 1 may constitute a part of the image generation apparatus. In this case, the image processing apparatus 1 may not include the communication device 15.

In this example, the image generation apparatus is a CT (Computed Tomography) apparatus. In this example, the CT apparatus generates a three-dimensional image by using X-rays. Therefore, in this example, the three-dimensional image is a CT image representing the CT value for each position. In this example, the unit of CT value is Hounsfield Unit (HU). The CT value represents the degree of absorption of X-rays and represents a relative value with respect to water. The CT value for water is zero.
Note that the CT apparatus may generate a three-dimensional image by using ultrasonic waves.

  Note that the image generation apparatus is referred to as nuclear magnetic resonance imaging (MRI), positron emission tomography (PET), or single photon emission tomography (SPECT). A three-dimensional image may be generated by using a technique.

  The communication device 15 is connected to an information processing device that holds a plurality of three-dimensional images generated by the image generation device via a communication network, and receives a plurality of three-dimensional images from the information processing device. Also good. Note that the image processing apparatus 1 may constitute a part of the information processing apparatus. In this case, the image processing apparatus 1 may not include the communication device 15.

  The image processing apparatus 1 may input a plurality of three-dimensional images by reading the plurality of three-dimensional images from a recording medium on which the plurality of three-dimensional images are recorded. In this case, the image processing apparatus 1 may not include the communication device 15. For example, the recording medium is a flexible disk, an optical disk, a magneto-optical disk, or a semiconductor memory.

  The communication device 15 may be connected to a radiation irradiation device that irradiates a living body with radiation, and may transmit control information for controlling radiation irradiation by the radiation irradiation device to the radiation irradiation device. The communication device 15 may be connected to the radiation irradiation device via a communication network. Further, the image processing apparatus 1 may constitute a part of the radiation irradiation apparatus. In this case, the image processing apparatus 1 may not include the communication device 15.

  The communication device 15 is connected to an information processing device for holding control information for controlling radiation irradiation by the radiation irradiation device via a communication network, and transmits control information to the information processing device. May be. Note that the image processing apparatus 1 may constitute a part of the information processing apparatus. In this case, the image processing apparatus 1 may not include the communication device 15.

  Further, the image processing apparatus 1 may output the control information by writing control information for controlling the irradiation of radiation by the radiation irradiating apparatus on the recording medium. In this case, the image processing apparatus 1 may not include the communication device 15.

(function)
As illustrated in FIG. 2, the functions of the image processing apparatus 1 include an image acquisition unit 101, an element specifying unit 102, a first parameter acquisition unit 103, a second parameter acquisition unit 104, an output unit 105, including.

The image acquisition unit 101 is realized by the processing device 11, the storage device 12, and the communication device 15.
The image acquisition unit 101 acquires N pieces of three-dimensional images by receiving N pieces of three-dimensional images taken at N different time points from the image generation apparatus. As described above, in this example, the object is the lung. Therefore, the volume of the object changes with time. Note that the lung volume may be expressed as a lung volume. N represents an integer of 2 or more, and represents 10 in this example.

  In this example, the respiratory phases at the N time points have equal intervals. The respiratory phase at each time point represents the ratio of the time from a predetermined reference time point to the respiratory cycle, which is the cycle of the respiratory motion, up to that time point in one respiratory motion. In this example, the reference time point is a time point at which the lung volume becomes maximum in the respiratory motion. Note that the reference time point may be a time point at which the lung volume is minimized in the respiratory motion.

  In this example, the breathing phase interval is (100 / N)%. Therefore, in this example, as shown in FIG. 3, the respiratory phases at the N time points are 0%, 10%,..., And 90%, respectively. In FIG. 3, Tm represents a point in time when the respiratory phase is m%.

  The image acquisition unit 101 captures images at N time points based on M three-dimensional images captured at M different time points (M represents an integer larger than N). The N three-dimensional images may be obtained by generating or estimating the generated N three-dimensional images.

The element specifying unit 102 is realized by the processing device 11 and the storage device 12.
The element specifying unit 102 selects at least two image sets composed of the first image and the second image from the N three-dimensional images acquired by the image acquisition unit 101.

  In this example, the element specifying unit 102 selects N-1 sets of images from the N three-dimensional images acquired by the image acquisition unit 101. In this example, the element specifying unit 102 selects one three-dimensional image from among the N three-dimensional images acquired by the image acquisition unit 101 as the first image common to the N-1 image sets. To do. In this example, the first image may be represented as a reference image.

  In this example, the reference image is a three-dimensional image taken at the time when the lung volume becomes substantially minimum in the respiratory motion. For example, the element specifying unit 102 selects a three-dimensional image captured at time T50 when the respiratory phase is 50% as the reference image. The element specifying unit 102 selects, as a reference image, a 3D image taken at time T40 when the respiratory phase is 40% or a 3D image taken at time T60 when the respiratory phase is 60%. May be. Further, the reference image may be a three-dimensional image taken at a time different from the time when the lung volume becomes substantially minimum in the respiratory motion (for example, time when the lung volume becomes substantially maximum).

  Furthermore, in this example, the element specifying unit 102 selects N−1 three-dimensional images other than the three-dimensional image selected as the reference image from among the N three-dimensional images acquired by the image acquisition unit 101. , N-1 second images constituting the N-1 image sets are selected respectively. In this example, the second image may be represented as a comparative image. As described above, the first image and the second image constituting each image set are two three-dimensional images taken at different time points.

Note that the number of image sets selected by the element specifying unit 102 may be two or more and smaller than N-1. Further, the number of image sets selected by the element specifying unit 102 may be N or more.
In addition, the element specifying unit 102 may select a three-dimensional image that differs between the two image sets as the first image. For example, the element specifying unit 102 may select a different three-dimensional image for each image set as the first image.

  The element specifying unit 102 specifies each of P different elements constituting the object in the selected reference image. P represents an integer of 2 or more. Each element in the reference image may be represented as a reference image element. In this example, each reference image element is a rectangular parallelepiped having a predetermined length in each direction of the X axis, the Y axis, and the Z axis, which are orthogonal to each other in the reference image. Each reference image element may be represented as a voxel. In this example, the reference image element may be expressed as a first image element.

  The element specifying unit 102 specifies a comparison image element that is an element corresponding to each reference image element in each of the selected comparison images. In this example, the element specifying unit 102 specifies a comparison image element corresponding to each reference image element in each of the selected comparison images by using a technique called non-rigid registration (DIR; Deformable Image Registration). To do. Thereby, the element specifying unit 102 acquires a displacement vector from the position of each reference image element to the position of the comparison image element corresponding to the reference image element for each of the selected comparison images. In this example, the comparative image element may be represented as a second image element.

The first parameter acquisition unit 103 is realized by the processing device 11 and the storage device 12.
The first parameter acquisition unit 103 is an image in which the element specifying unit 102 selects a first parameter that represents a rate at which the volume of the comparison image element corresponding to the reference image element changes with respect to the volume of each reference image element. Get for each of the pairs.

In this example, the first parameter acquisition unit 103 acquires the first parameter V _HU (x) for each reference image element based on Equation 1 for each reference image element. In other words, in this example, the first parameter acquisition unit 103 acquires N−1 first parameters V _HU (x) corresponding to the N−1 image sets for each reference image element.

In Equation 1, x represents the position of the reference image element, u (x) represents a displacement vector from the position of the reference image element to the position of the comparison image element, and HU ₁ represents the CT value of the reference image element. HU ₂ represents the CT value of the comparative image element. u may be taken to represent the displacement vector field.

The first parameter acquisition unit 103 may acquire the first parameter V _jac (x) for each reference image element for each image set based on Expression 2 instead of Expression 1.

The second parameter acquisition unit 104 is realized by the processing device 11 and the storage device 12.
The second parameter acquisition unit 104 estimates the volume difference of the object (in this example, the lung volume difference) in each of the image sets selected by the element specifying unit 102. The difference in lung volume may be expressed as a lung volume difference.

  The difference in the volume of the object in the image set (in other words, the object volume difference) forms the image set with the volume of the object in the first image (in this example, the reference image) constituting the image set. It is the difference between the volume of the object in the second image (comparative image in this example). In this example, the object volume difference is a value obtained by subtracting the volume of the object in the first image constituting the image set from the volume of the object in the second image constituting the image set.

  The second parameter acquisition unit 104 acquires, for each reference image element, a second parameter that represents a rate at which the first parameter acquired by the first parameter acquisition unit 103 changes with respect to the estimated object volume difference. . In this example, the second parameter acquisition unit 104 acquires, for each reference image element, the slope of a straight line represented by a linear function representing the change in the first parameter with respect to the estimated object volume difference as the second parameter. .

In this example, the slope of a straight line represented by a linear function that represents a change in the first parameter with respect to the object volume difference represents a rate at which the first parameter changes with respect to the object volume difference.
In this example, the second parameter acquisition unit 104 estimates a linear function representing a change in the first parameter with respect to the estimated object volume difference by using the least square method.

  For example, as shown in FIG. 4, the second parameter acquisition unit 104 estimates the linear function. In FIG. 4, a circle M <b> 1 represents N−1 first parameters acquired for the first reference image element, and a straight line L <b> 1 is a second parameter acquisition unit for the first reference image element. A linear function estimated by 104 is represented. Similarly, a square M2 represents N−1 first parameters acquired for the second reference image element, and a straight line L2 indicates the second parameter acquisition unit 104 for the second reference image element. Represents a linear function estimated by.

  When only one three-dimensional image is selected as the first image as in this example, the second parameter acquisition unit 104 replaces the object volume difference with the second image (in this example, the comparison You may acquire a 2nd parameter using the volume of the target object in an image.

The output unit 105 is realized by the processing device 11, the storage device 12, and the output device 14.
In the output unit 105, a region (in other words, a high-function region) in which a predetermined function of an element constituting the target object is higher than other regions is acquired by the second parameter acquisition unit 104. Based on the second parameter.

As described above, in this example, the object is the lung. In this example, the predetermined function is a function of performing ventilation. In the case of an organ other than the lung, the predetermined function may be a function different from the function of performing ventilation.
The output unit 105 outputs information representing the specified high-functional area via the output device 14.

  In this example, the output unit 105 identifies an area of the target object in which the second parameter acquired by the second parameter acquisition unit 104 is greater than or equal to a predetermined threshold as a high-function area.

  The output unit 105 outputs the second parameter for each reference image element via the output device 14 instead of outputting the information representing the high-function area or in addition to outputting the information representing the high-function area. May be.

(Operation)
Next, the operation of the image processing apparatus 1 will be described.
As illustrated in FIG. 5, the image processing apparatus 1 receives N pieces of three-dimensional images, each of which is captured at N different points in time, from the image generation apparatus. A three-dimensional image is acquired (step S101 in FIG. 5).

  Next, the image processing apparatus 1 obtains N-1 sets of 3D images taken at the time when the lung volume becomes substantially minimum in the respiratory motion among the N 3D images acquired in step S101. Are selected as reference images constituting each of the image sets. Furthermore, the image processing apparatus 1 converts N−1 three-dimensional images other than the three-dimensional image selected as the reference image out of the N three-dimensional images acquired in step S101 into N−1 sets. Are selected as N-1 comparison images constituting each image set. As a result, the image processing apparatus 1 selects N-1 image sets (step S102 in FIG. 5).

  Next, the image processing apparatus 1 specifies each of P different elements (in other words, reference image elements) constituting the object in the reference image selected in step S102 (step S103 in FIG. 5).

  Next, the image processing apparatus 1 specifies a comparison image element that is an element corresponding to each of the P reference image elements specified in step S103 in each of the comparison images selected in step S102. As a result, the image processing apparatus 1 uses, in step S102, the displacement vector from the position of each of the P reference image elements specified in step S103 to the position of the comparison image element corresponding to the reference image element. Obtained for each of the selected image sets (step S104 in FIG. 5).

Next, the image processing apparatus 1 performs, based on Equation 1 and the displacement vector acquired in Step S104, for each reference image element for each of the image sets selected in Step S102. The parameter V _HU (x) is acquired (step S105 in FIG. 5).

  Next, the image processing apparatus 1 estimates an object volume difference (in this example, a lung volume difference) in each of the image sets selected in step S102. Further, the image processing apparatus 1 acquires, for each reference image element, a second parameter that represents a rate at which the first parameter acquired in step S105 changes with respect to the estimated object volume difference (FIG. 5). Step S106).

Next, the image processing apparatus 1 specifies the high-function area of the target based on the second parameter acquired in step S106, and sends information representing the specified high-function area via the output device 14. Output (step S107 in FIG. 5).
Next, the image processing apparatus 1 ends the process of FIG.

  As described above, the image processing apparatus 1 according to the first embodiment uses the first from a plurality of three-dimensional images, each of which is taken at a plurality of different points in time, with the volume changing with time. At least two image sets constituted by the image and the second image are selected, and elements constituting the object are specified in each of the first image and the second image constituting the at least two image sets. Further, the image processing apparatus 1 is configured to detect the element specified in the second image constituting the image set with respect to the volume of the first image element that is the specified element in the first image constituting the image set. The first parameter representing the rate at which the volume of the second image element is changed is acquired for each of the at least two image sets. In addition, the image processing apparatus 1 is configured to detect the difference between the volume of the object in the first image that configures the image set and the volume of the object in the second image that configures the image set. A second parameter representing the rate at which the first parameter changes is acquired.

  The second parameter has a strong correlation with a predetermined function of an element constituting the object. For example, when the object is the lung, the second parameter and the function of the element to perform ventilation have a strong correlation. Therefore, according to the image processing apparatus 1, the height of the function of the element can be estimated with high accuracy based on the second parameter. Thus, according to the image processing apparatus 1, the height of the function of the element can be estimated with high accuracy while suppressing the processing load.

  Furthermore, the image processing apparatus 1 according to the first embodiment responds to the difference between the volume of the object in the first image that constitutes the image set and the volume of the object in the second image that constitutes the image set. Then, the slope of a straight line represented by a linear function representing the change of the first parameter is acquired as the second parameter.

  There is a strong correlation between the slope of the straight line and the function of the elements constituting the object. Therefore, according to the image processing apparatus 1, the height of the function of the element can be estimated with high accuracy based on the inclination of the straight line. Thus, according to the image processing apparatus 1, the height of the function of the element can be estimated with high accuracy while suppressing the processing load.

  Furthermore, the image processing apparatus 1 according to the first embodiment specifies the first image element and the second image element for each of a plurality of different elements constituting the object. Further, the image processing apparatus 1 acquires the first parameter for each of the plurality of elements. In addition, the image processing apparatus 1 acquires the second parameter for each of the plurality of elements.

  According to this, the height of the function which each of the some element which comprises a target object has can be estimated with high precision. Thereby, the area | region where the function of an element is higher than another area | region can be specified among objects. Therefore, for example, when the object is a lung, it is possible to specify a region of the lung that has a higher function of ventilation than other regions. As a result, for example, in the case of irradiating the lung with radiation, the amount of radiation irradiated to the specified region can be suppressed, so that the ability of the lung to ventilate can be suppressed from decreasing.

  In FIG. 6, “Comparative example” is a correlation between the first parameter acquired by the image processing apparatus of the comparative example and the parameter representing the height of the function of ventilation measured by the nuclear medicine examination. Represents a number. A nuclear medicine test may be referred to as a radioisotope (RI) test.

  The image processing apparatus of the comparative example selects a three-dimensional image taken at the time when the lung volume becomes the smallest in the respiratory motion as a reference image, and the tertiary taken at the time when the lung volume becomes the largest in the respiratory motion. The original image is selected as a comparison image.

  Furthermore, the image processing apparatus of the comparative example identifies each of P different elements (in other words, reference image elements) constituting the object in the reference image, and assigns each of the specified P reference image elements to each of the specified P image elements. A comparison image element which is a corresponding element is identified in the selected comparison image. Thereby, the image processing apparatus of the comparative example converts the displacement vector from the position of each of the specified P reference image elements to the position of the comparison image element corresponding to the reference image element to the selected comparison image. Get against.

The image processing apparatus of the comparative example acquires the first parameter V _HU (x) for the selected comparison image based on Expression 1 and the acquired displacement vector for each reference image element.

In FIG. 6, “9 phase” is the interval between the second parameter acquired by the image processing apparatus 1 of the first embodiment and the parameter representing the height of the ventilation function measured by the nuclear medicine examination. Represents the correlation coefficient.
Further, in FIG. 6, “5 phase” indicates the second parameter acquired by the image processing apparatus 1 when only five image sets are selected in the image processing apparatus 1 of the first embodiment, and nuclear medicine. The correlation coefficient between the parameter showing the height of the function which performs ventilation measured by the test | inspection is represented.

As described above, the second parameter acquired by the image processing apparatus 1 according to the first embodiment is a function of performing ventilation, which is measured by the nuclear medicine examination, rather than the first parameter acquired by the image processing apparatus according to the comparative example. It has a strong correlation with the parameter representing the height of
Therefore, according to the image processing apparatus 1, the height of the function of the element can be estimated with high accuracy based on the second parameter. Thus, according to the image processing apparatus 1, the height of the function of the element can be estimated with high accuracy while suppressing the processing load.

  In addition, this invention is not limited to embodiment mentioned above. For example, various modifications that can be understood by those skilled in the art may be added to the above-described embodiments without departing from the spirit of the present invention. For example, any combination of the above-described embodiment and modification may be adopted as another modification of the above-described embodiment without departing from the spirit of the present invention.

DESCRIPTION OF SYMBOLS 1 Image processing apparatus 11 Processing apparatus 12 Storage apparatus 13 Input apparatus 14 Output apparatus 15 Communication apparatus 101 Image acquisition part 102 Element specific | specification part 103 1st parameter acquisition part 104 2nd parameter acquisition part 105 Output part BU Bus

Claims (9)

Selecting at least two sets of images composed of a first image and a second image from a plurality of three-dimensional images, each of which is taken at a plurality of different points in time, with an object whose volume changes over time, An element specifying unit for specifying an element constituting the object in each of the first image and the second image constituting the at least two image sets;
The volume of the second image element that is the specified element in the second image that constitutes the image set with respect to the volume of the first image element that is the specified element in the first image that constitutes the image set A first parameter obtaining unit that obtains a first parameter representing a rate of change for each of the at least two image sets;
Represents the rate at which the first parameter changes with respect to the difference between the volume of the object in the first image constituting the image set and the volume of the object in the second image constituting the image set. A second parameter acquisition unit for acquiring a second parameter;
An image processing apparatus comprising: The image processing apparatus according to claim 1,
The second parameter acquisition unit is configured to determine the first parameter with respect to a difference between the volume of the object in the first image constituting the image set and the volume of the object in the second image constituting the image set. An image processing apparatus that acquires, as the second parameter, the slope of a straight line represented by a linear function that represents a change in. The image processing apparatus according to claim 1 or 2,
The three-dimensional image is a CT image representing a CT (Computed Tomography) value for each position,
The first parameter acquisition unit acquires the first parameter V _HU (x) based on Equation 1, where x represents the position of the first image element, and u (x) is The displacement vector from the position of the first image element to the position of the second image element is represented, HU ₁ represents the CT value of the first image element, and HU ₂ represents the CT value of the second image element. An image processing apparatus representing

The image processing apparatus according to claim 1 or 2,
The first parameter acquisition unit acquires the first parameter V _jac (x) based on Formula 2, where x represents the position of the first image element, and u (x) is An image processing apparatus representing a displacement vector from a position of the first image element to a position of the second image element.

An image processing apparatus according to any one of claims 1 to 4,
The element specifying unit specifies the first image element and the second image element for each of a plurality of different elements constituting the object,
The first parameter acquisition unit acquires the first parameter for each of the plurality of elements,
The image processing apparatus, wherein the second parameter acquisition unit acquires the second parameter for each of the plurality of elements. The image processing apparatus according to claim 5,
The information which specifies the area | region where the predetermined function which the element which comprises the target object has among the objects is higher than another area based on the acquired 2nd parameter, and represents the specified area An image processing apparatus comprising an output unit for outputting The image processing apparatus according to claim 6,
The output unit identifies an area of the object in which the acquired second parameter is equal to or greater than a predetermined threshold as an area of the object in which the function is higher than other areas. Image processing device. Selecting at least two sets of images composed of a first image and a second image from a plurality of three-dimensional images, each of which is taken at a plurality of different points in time, with an object whose volume changes over time, The elements constituting the object are specified in each of the first image and the second image constituting the at least two sets of images,
The volume of the second image element that is the specified element in the second image that constitutes the image set with respect to the volume of the first image element that is the specified element in the first image that constitutes the image set Obtaining a first parameter representing a rate at which for each of the at least two image sets;
Represents the rate at which the first parameter changes with respect to the difference between the volume of the object in the first image constituting the image set and the volume of the object in the second image constituting the image set. An image processing method for acquiring a second parameter. Selecting at least two sets of images composed of a first image and a second image from a plurality of three-dimensional images, each of which is taken at a plurality of different points in time, with an object whose volume changes over time, The elements constituting the object are specified in each of the first image and the second image constituting the at least two sets of images,
The volume of the second image element that is the specified element in the second image that constitutes the image set with respect to the volume of the first image element that is the specified element in the first image that constitutes the image set Obtaining a first parameter representing a rate at which for each of the at least two image sets;
Represents the rate at which the first parameter changes with respect to the difference between the volume of the object in the first image constituting the image set and the volume of the object in the second image constituting the image set. An image processing program for causing a computer to execute processing for acquiring a second parameter.

Images