WO2022027545A1 - 图像数据的处理方法、放疗设备的等中心验证方法及系统 - Google Patents
图像数据的处理方法、放疗设备的等中心验证方法及系统 Download PDFInfo
- Publication number
- WO2022027545A1 WO2022027545A1 PCT/CN2020/107663 CN2020107663W WO2022027545A1 WO 2022027545 A1 WO2022027545 A1 WO 2022027545A1 CN 2020107663 W CN2020107663 W CN 2020107663W WO 2022027545 A1 WO2022027545 A1 WO 2022027545A1
- Authority
- WO
- WIPO (PCT)
- Prior art keywords
- pixel
- light spot
- shadow
- image data
- surface fitting
- Prior art date
Links
- 238000001959 radiotherapy Methods 0.000 title claims abstract description 168
- 238000000034 method Methods 0.000 title claims abstract description 109
- 238000012795 verification Methods 0.000 title claims abstract description 49
- 238000003672 processing method Methods 0.000 title claims abstract description 21
- 238000012545 processing Methods 0.000 claims abstract description 94
- 230000000875 corresponding effect Effects 0.000 claims description 73
- 230000008569 process Effects 0.000 claims description 61
- 230000000903 blocking effect Effects 0.000 claims description 40
- 238000001514 detection method Methods 0.000 claims description 14
- 230000002596 correlated effect Effects 0.000 claims description 9
- 238000000605 extraction Methods 0.000 claims description 8
- 229910052751 metal Inorganic materials 0.000 claims description 4
- 239000002184 metal Substances 0.000 claims description 4
- 230000005855 radiation Effects 0.000 description 46
- 239000011159 matrix material Substances 0.000 description 41
- 238000010586 diagram Methods 0.000 description 21
- 238000004088 simulation Methods 0.000 description 14
- 238000010200 validation analysis Methods 0.000 description 5
- 230000008859 change Effects 0.000 description 3
- 238000004422 calculation algorithm Methods 0.000 description 2
- 230000003247 decreasing effect Effects 0.000 description 2
- 238000003384 imaging method Methods 0.000 description 2
- 206010028980 Neoplasm Diseases 0.000 description 1
- 238000004458 analytical method Methods 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000004364 calculation method Methods 0.000 description 1
- 201000011510 cancer Diseases 0.000 description 1
- 238000012937 correction Methods 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 238000003709 image segmentation Methods 0.000 description 1
- 238000009434 installation Methods 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000011275 oncology therapy Methods 0.000 description 1
- 230000003287 optical effect Effects 0.000 description 1
- 230000011218 segmentation Effects 0.000 description 1
- WFKWXMTUELFFGS-UHFFFAOYSA-N tungsten Chemical compound [W] WFKWXMTUELFFGS-UHFFFAOYSA-N 0.000 description 1
- 229910052721 tungsten Inorganic materials 0.000 description 1
- 239000010937 tungsten Substances 0.000 description 1
Images
Classifications
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B6/00—Apparatus or devices for radiation diagnosis; Apparatus or devices for radiation diagnosis combined with radiation therapy equipment
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61N—ELECTROTHERAPY; MAGNETOTHERAPY; RADIATION THERAPY; ULTRASOUND THERAPY
- A61N5/00—Radiation therapy
- A61N5/10—X-ray therapy; Gamma-ray therapy; Particle-irradiation therapy
Definitions
- the present application relates to the technical field of medical devices, and in particular, to a method for processing image data, a method and a system for isocenter verification of radiotherapy equipment.
- Radiotherapy is an important means of treating cancer, and radiotherapy equipment (referred to as radiotherapy equipment) is the key medical equipment for radiotherapy.
- Radiation therapy equipment may generally include: a rotating gantry, and a treatment head located on the rotating gantry.
- a radiotherapy device When a radiotherapy device is used to treat a patient, it is necessary to ensure that the offset between the isocenter of the radiotherapy device and the treatment isocenter is less than a preset value. Otherwise, the ray beam emitted by the treatment head may not irradiate the target area of the patient, so that the radiotherapy equipment cannot accurately treat the target area of the patient.
- the ray beam of the treatment head needs to be irradiated on the film to form a focal spot on the film, and the center of the focal spot is the treatment isocenter.
- the preset point is the isocenter of the radiotherapy equipment
- the current validation of isocenters of radiotherapy equipment by film is inefficient.
- Embodiments of the present application provide a method for processing image data, a method and a system for isocenter verification of radiotherapy equipment. It can solve the problem of low efficiency of verifying the isocenter of radiotherapy equipment through film in the prior art, and the technical solution is as follows:
- a method for processing image data where the image data is data generated based on the projection data after a processing device acquires projection data from a detector, and the image data contains the treatment of the radiotherapy device A light spot formed after the ray beam generated by the head is blocked by a ray blocking body and a shadow located in the light spot; the method includes:
- initial pixel data includes: pixel values of each pixel in the area where the light spot is located;
- a first curved surface fitting model is used to perform a curved surface fitting process on the light spot to obtain model parameters of the first curved surface fitting model, where the model parameters of the first curved surface fitting model include: : the coordinates of the center point of the light spot;
- the pixel data of the shadow is determined, and the pixel data of the shadow includes: the pixel value of each pixel in the region where the shadow is located;
- a second surface fitting model is used to perform surface fitting processing on the shadow, so as to obtain model parameters of the second surface fitting model, and model parameters of the second surface fitting model Include: the coordinates of the center point of the shadow.
- a first surface fitting model is used to perform surface fitting processing on the light spot to obtain model parameters of the first surface fitting model, including:
- At least one fitting process is performed on the light spot until a cut-off condition is reached, and the model parameters to be selected obtained from the last fitting process are determined as the model parameters of the first surface fitting model;
- the fitting process includes:
- the first curved surface fitting model is used to perform a surface fitting process on the light spot, so as to obtain the waiting area of the first curved surface model. select model parameters;
- the weight corresponding to each pixel in the area where the light spot is located is updated, and the weight is negatively correlated with the pixel value difference.
- a second surface fitting model is used to perform surface fitting processing on the shadow to obtain model parameters of the second surface fitting model, including:
- At least one fitting process is performed on the shadow until a cut-off condition is reached, and the model parameters to be selected obtained from the last fitting process are determined as the model parameters of the second surface fitting model;
- the fitting process includes:
- the second surface fitting model is used to perform surface fitting processing on the shadow, so as to obtain the second surface fitting model of the shadow.
- the model parameters to be selected
- the weight corresponding to each pixel in the region where the shadow is located is updated, and the weight is negatively correlated with the pixel value difference.
- the cut-off condition includes: performing the fitting process for a specified number of times; or, the candidate model parameters obtained after the currently performed fitting process and the candidate model parameters obtained after the last performed fitting process.
- the amount of change is less than the change threshold.
- the first surface fitting model and the second surface fitting model are both: a two-dimensional Gaussian surface fitting model.
- the determining initial pixel data includes:
- the original pixel value of each pixel in the circumscribed rectangle is determined as the initial pixel data.
- a method for isocenter validation of radiotherapy equipment comprising:
- an offset amount between the isocenter of the radiotherapy device and the isocenter of the treatment is determined.
- At least two projection data generated when the treatment heads of the radiotherapy equipment are located at different positions are acquired from the detector, and at least two image data are generated based on the at least two projection data, including:
- the offset between the isocenter of the radiotherapy equipment and the treatment isocenter is determined, including:
- an offset between the isocenter of the radiation therapy device and the treatment isocenter is determined.
- the direction of the ray beam emitted when the treatment head of the radiotherapy device is located at the first position is perpendicular to the direction of the ray beam emitted when the treatment head of the radiotherapy device is located at the second position.
- an isocenter verification system for radiotherapy equipment includes radiotherapy equipment, a radiation blocking body and a processing equipment, wherein,
- the radiotherapy equipment includes: a treatment head and a detector arranged oppositely, the detector is used for receiving the ray beam generated by the treatment head and converting it into projection data;
- the ray blocking body is detachably installed at the isocenter of the radiotherapy equipment, and the center of the ray blocking body coincides with the isocenter of the radiotherapy equipment;
- the processing device is electrically connected to the detector, and the processing device is configured to execute any of the above-mentioned isocentric verification methods for radiotherapy equipment.
- the ray blocking body is a ray blocking ball.
- the ray blocking ball is a metal ball.
- the system further includes a detection phantom, the ray blocking body is installed at a central position of the detection phantom, and the ray blocking body is detachably mounted on the radiotherapy equipment through the detection phantom. isocenter.
- the radiotherapy apparatus further includes a treatment couch, and the detection phantom is detachably installed at a preset position of the treatment couch and located at the isocenter of the radiotherapy apparatus.
- a computer-readable storage medium where at least one instruction is stored in the storage medium, and the instruction is loaded and executed by a processor to implement any of the above-mentioned image data processing methods, or any of the above-mentioned methods.
- the projection data is acquired from the detector in the radiation therapy device by the processing device, and after image data is generated based on the projection data, the image data is processed to obtain the coordinates of the center point of the light spot and the coordinates of the center point of the shadow, so, Subsequently, by determining the offset between the center point of the light spot and the center point of the shadow, the isocenter verification of the radiotherapy equipment can be realized. There is no need to verify the isocenter of the radiotherapy equipment by manually analyzing the film, which effectively improves the verification efficiency of the isocenter of the radiotherapy equipment.
- FIG. 1 is a schematic structural diagram of an isocenter verification system of a radiotherapy device provided by an embodiment of the present application
- FIG. 2 is a schematic diagram of an image data provided by an embodiment of the present application.
- FIG. 3 is a flowchart of a method for processing image data provided by an embodiment of the present application.
- FIG. 4 is a flowchart of another image data processing method provided by an embodiment of the present application.
- FIG. 5 is a schematic diagram of a light spot after contour extraction processing provided by an embodiment of the present application.
- FIG. 6 is a schematic diagram of a circumscribed rectangle of an outline of a light spot provided by an embodiment of the present application.
- FIG. 7 is a three-dimensional simulation diagram of initial pixel data provided by an embodiment of the present application.
- FIG. 8 is a three-dimensional simulation diagram of obtaining updated pixel data after updating initial pixel data according to an embodiment of the present application
- FIG. 9 is a three-dimensional simulation diagram of pixel data of a shadow determined based on updated pixel data and initial pixel data provided by an embodiment of the present application.
- FIG. 10 is another three-dimensional simulation diagram of the updated pixel data obtained after updating the initial pixel data provided by the embodiment of the present application.
- 11 is another three-dimensional simulation diagram of the pixel data of the shadow determined based on the updated pixel data and the initial pixel data provided by the embodiment of the present application;
- FIG. 13 is a flowchart of another method for isocenter verification of radiotherapy equipment provided by an embodiment of the present application.
- FIG. 1 is a schematic structural diagram of an isocenter verification system for radiotherapy equipment provided by an embodiment of the present application.
- the isocenter verification system 100 of the radiotherapy equipment may include: a radiotherapy equipment 101 , a radiation blocking body 102 and a processing equipment 103 .
- the radiotherapy equipment 101 may include: a treatment head 1011 and a detector 1012 arranged oppositely.
- the detector 1012 may be an electronic portal imaging device (English: Electronic Portal Imaging Device; abbreviation: EPID).
- EPID Electronic Portal Imaging Device
- the detector 1012 is used to receive the radiation beam generated by the treatment head 1011 and convert it into projection data.
- the ray blocking body 102 is detachably installed at the isocenter of the radiotherapy apparatus 101 , and the center of the ray blocking body 102 may coincide with the isocenter of the radiotherapy apparatus 101 .
- the processing device 103 may be electrically connected to the detector 1012 in the radiotherapy device 101 .
- the processing device 103 may acquire projection data from the detector 1012 and generate image data based on the projection data.
- the image data includes a light spot formed after the radiation beam generated by the treatment head 1011 in the radiotherapy apparatus 101 is blocked by the radiation blocking body 102 and a shadow located in the light spot.
- the treatment head 1011 in the radiotherapy apparatus 101 usually includes a plurality of radiation sources, and the radiation beam emitted by each radiation source will pass through the radiation blocking body 102 and then irradiate on the detector 1012, and the detector 1012 will receive the radiation beam.
- the ray beam is converted into projection data.
- the processing device 103 may acquire projection data from the detector 1012 and convert it into image data.
- FIG. 2 is a schematic diagram of image data provided by an embodiment of the present application. Since the radiation beam emitted by each radiation source in the treatment head 1011 will pass through the radiation blocking body 102 and then irradiate on the detector 1012, the image data generated by the processing device 103 includes multiple radiation sources corresponding to multiple radiation sources. There are several light spots 01, and each light spot 01 has a shadow 02 in it.
- the radiotherapy apparatus 101 may further include: a rotating gantry 1013, the treatment head 1011 and the detector 1012 are both disposed on the rotating gantry 1013, and the rotating gantry 1013 can simultaneously drive the treatment head 1011 and the detector 1012 to rotate . In this way, by rotating the gantry 1013, the treatment head 1011 can be controlled to be located in different positions.
- FIG. 3 is a flowchart of an image data processing method provided by an embodiment of the present application.
- the image data processing method can be applied to the processing device 103 in the isocenter verification system 100 of the radiotherapy device shown in FIG. 1 .
- the image data may be data generated based on the projection data after the processing device 103 acquires the projection data from the detector 1012 in the radiotherapy device 101 .
- the image data can refer to the image shown in FIG. 2
- the image data includes a light spot 01 formed after the radiation beam generated by the treatment head 1011 of the radiotherapy apparatus 101 is blocked by the ray blocking body 102 and a shadow 02 located in the light spot 01 .
- the processing method of the image data may include:
- Step 201 Determine initial pixel data.
- the initial pixel data includes: pixel values of each pixel in the area where the light spot is located.
- Step 202 Based on the initial pixel data, use the first surface fitting model to perform surface fitting processing on the light spot to obtain model parameters of the first surface fitting model.
- the model parameters of the first surface fitting model include: coordinates of the center point of the light spot.
- Step 203 based on the first curved surface fitting model and the obtained model parameters, update the pixel value of each pixel in the area where the light spot is located to obtain updated pixel data.
- Step 204 Determine the pixel data of the shadow based on the updated pixel data and the initial pixel data.
- the pixel data of the shadow includes: pixel values of each pixel in the region where the shadow is located.
- Step 205 Based on the pixel data of the shadow, use the second surface fitting model to perform surface fitting processing on the shadow to obtain model parameters of the second surface fitting model.
- the model parameters of the second surface fitting model include: coordinates of the center point of the shadow.
- projection data is acquired from a detector in a radiotherapy device through a processing device, and after image data is generated based on the projection data, the image data is processed to obtain The coordinates of the center point of the light spot and the center point of the shadow are obtained.
- the verification of the isocenter of the radiotherapy equipment can be realized. There is no need to verify the isocenter of the radiotherapy equipment by manually analyzing the film, which effectively improves the verification efficiency of the isocenter of the radiotherapy equipment.
- FIG. 4 is a flowchart of another image data processing method provided by an embodiment of the present application.
- the image data processing method can be applied to the processing equipment 103 in the isocenter verification system 100 of the radiotherapy equipment shown in FIG. 1 .
- the image data may be data generated based on the projection data after the processing device 103 acquires the projection data from the detector 1012 in the radiotherapy device 101 .
- the image data can refer to the image shown in FIG. 2
- the image data includes a light spot 01 formed after the radiation beam generated by the treatment head 1011 of the radiotherapy apparatus 101 is blocked by the ray blocking body 102 and a shadow 02 located in the light spot 01 .
- the processing method of the image data may include:
- Step 301 Perform contour extraction processing on the light spot in the image data to obtain the contour of the light spot.
- the processing device may use an image segmentation algorithm such as a watershed segmentation algorithm to perform contour extraction processing on the light spot in the image, so as to obtain the contour of the light spot.
- an image segmentation algorithm such as a watershed segmentation algorithm to perform contour extraction processing on the light spot in the image, so as to obtain the contour of the light spot.
- FIG. 5 is a schematic diagram of a light spot after contour extraction processing provided by an embodiment of the present application. After the contour extraction process is performed on the light spot in the image data shown in FIG. 2 , the contour 03 of the light spot can be obtained.
- Step 302 Based on the outline of the light spot, determine a circumscribed rectangle of the outline of the light spot.
- the processing device may determine a circumscribed rectangle of the contour of the light spot based on the contour of the light spot.
- the ray beams emitted by multiple radiation sources in the treatment head can be analyzed, and the ray beams emitted by one of the multiple radiation sources can also be analyzed.
- the radiation beams emitted by multiple radiation sources in each treatment head need to be analyzed, the radiation beams emitted by the multiple radiation sources in the treatment head need to be emitted at the same time, and the image data generated by the processing device includes multiple light spots.
- the image data generated by the processing device includes multiple light spots.
- FIG. 6 is a schematic diagram of a circumscribed rectangle of an outline of a light spot provided by an embodiment of the present application.
- the contour of each light spot needs to be complemented to obtain the contour 04 after the complementing process, and the contour 04 after the complementing process is approximately an ellipse.
- the circumscribed rectangle of the ellipse can be determined as the circumscribed rectangle 05 of the outline of the light spot. In this way, the circumscribed rectangle of the outline of each light spot can be obtained.
- the image data generated by the processing device contains a light spot.
- the contour of the light spot obtained after the contour extraction process is performed on the light spot is approximately an ellipse, so that the contour of the light spot does not need to be complemented.
- Step 303 Determine the original pixel value of each pixel in the circumscribed rectangle as initial pixel data.
- the processing device may determine the original pixel value of each pixel within the circumscribed rectangle as the initial pixel data.
- the initial pixel data may include: pixel values of each pixel in the area where the light spot is located.
- the initial pixel data may further include: pixel values of respective pixel points located outside the light spot and within the circumscribed rectangle of the area where the light spot is located. If the image data includes multiple light spots, in step 303, multiple initial pixel data needs to be determined, so that the subsequent processing device can determine the position of the center point of each light spot.
- Step 304 using the first surface fitting model to perform surface fitting processing on the light spot based on the initial pixel data to obtain model parameters of the first surface fitting model.
- the processing device may use the first surface fitting model to perform surface fitting processing on the light spot based on the initial pixel data, so as to obtain model parameters of the first surface fitting model.
- the model parameters of the first fitting model include: coordinates of the center point of the light spot.
- the first surface fitting model may be a two-dimensional Gaussian surface fitting model.
- the expression of the two-dimensional Gaussian surface fitting model is as follows:
- (x, y) represents the coordinates of the pixel in the circumscribed rectangle of the outline of the light spot; f(x, y) represents the pixel value of the pixel in the circumscribed rectangle of the outline of the light spot, that is, the initial pixel data; G represents the maximum value of the pixel value of each pixel in the circumscribed rectangle of the outline of the light spot; x 0 represents the abscissa of the center point of the light spot; y 0 represents the ordinate of the center point of the light spot; ⁇ x is the standard deviation in the x direction ; ⁇ y is the standard deviation in the y direction.
- the left side of the equal sign in the above formula (1) can be represented as initial pixel data
- the parameters on the right side of the equal sign can be represented as model parameters of the first surface fitting model.
- the model parameters of the first surface fitting model include: coordinates of the center point of the light spot.
- the above-mentioned formula (1) may be converted into the following formula.
- formula (2) can be obtained, as follows:
- the initial pixel data includes N data points, that is, the number of pixel points within the circumscribed rectangle of the outline of the light spot is N.
- A is an N ⁇ 1 matrix
- the elements in the N ⁇ 1 matrix are:
- a i represents the ith element in the matrix in the N ⁇ 1 matrix
- f i represents the ith data point in the N data points.
- N ⁇ 5 matrix B is an N ⁇ 5 matrix, and the N ⁇ 5 matrix can be expressed as:
- x i represents the abscissa corresponding to the ith data point among the N data points
- y i represents the ordinate corresponding to the ith data point among the N data points.
- C is a 5 ⁇ 1 matrix, and the 5 ⁇ 1 matrix can be expressed as:
- matrix C can be obtained from matrix A and matrix B.
- each element included in the matrix C together constitutes the model parameters of the first surface fitting model in the above-mentioned embodiment, and the matrix A and the matrix B are both known quantities, so based on the matrix A and the matrix After B obtains the matrix C, the model parameters of the first surface fitting model can be obtained.
- the least squares method can be used to fit the matrix C, and the expression of the matrix C with respect to the matrix A and the matrix B is obtained as:
- the matrix C can be calculated by the above formula (3), and the model parameters of the first curved surface model can be obtained.
- the embodiment of the present application provides the following second optional implementation manner, which can effectively improve the accuracy of determining the center point of the light spot.
- a corresponding weight may be assigned to each pixel point corresponding to the initial pixel data.
- the weight is used to reflect the degree of influence of the pixel value of the corresponding pixel point on the fitting result obtained after surface fitting of the light spot. It should be noted that the numerical value of the weight is negatively correlated with the degree of influence of the fitting result obtained after surface fitting of the light spot. In this way, when the surface fitting is performed on the light spot based on the initial pixel data and the weight corresponding to each pixel point, the influence of shadows on the fitting result obtained by the surface fitting processing of the light spot can be weakened, and the final obtained light spot can be effectively improved. accuracy of the center point.
- the first surface fitting model is used to perform surface fitting processing on the light spot to obtain model parameters of the first surface fitting model, including:
- the fitting process may include the following steps:
- Step 3041 Obtain a first weight matrix.
- the processing device may acquire the first weight matrix.
- the first weight matrix includes: weights corresponding to each pixel in the light spot. Due to the plurality of data in the first weight matrix, there is a one-to-one correspondence with the plurality of data in the initial pixel data. Therefore, when the initial pixel data further includes: pixel values of each pixel located outside the light spot and within the circumscribed rectangle, the weight matrix also includes: weights corresponding to each pixel outside the light spot and within the circumscribed rectangle.
- the value range of the weight corresponding to each pixel point in this application is [0, 1].
- the weight corresponding to each pixel point in the first weight matrix obtained by the radiotherapy device is all 1.
- Step 3042 Based on the initial pixel data and the weights corresponding to each pixel in the area where the light spot is located, use the first surface fitting model to perform surface fitting processing on the light spot to obtain model parameters to be selected for the first surface fitting model.
- the processing device may use the first surface fitting model to perform surface fitting processing on the light spot based on the initial pixel data and the first weight matrix obtained in step 3041, so as to obtain the first surface fitting model the candidate model parameters.
- W represents the first weight matrix
- the matrix C can be calculated by the formula (4), and the model parameters to be selected for the first curved surface fitting model can be obtained.
- Step 3043 based on the first curved surface fitting model and the acquired parameters of the candidate model, update the initial pixel data to obtain updated candidate pixel data.
- the processing device may update the initial pixel data based on the first curved surface fitting model and the acquired parameters of the candidate model, to obtain updated candidate pixel data.
- the above formula (1) can be used to update the initial pixel data, because the parameters on the right side of the equal sign in the above formula (1) are the model parameters to be selected for the first surface fitting model obtained in step 3042. Therefore, through the formula (1), the pixel value of each pixel point can be recalculated, so as to realize the update of the initial pixel data, so as to obtain the updated pixel data to be selected.
- Step 3044 Based on the updated candidate pixel data and the initial pixel data, determine the pixel value difference corresponding to each pixel in the area where the light spot is located.
- the processing device may determine, based on the updated candidate pixel data and the initial pixel data, pixel value differences corresponding to each pixel in the area where the light spot is located. For example, assuming that for a certain pixel, the corresponding pixel value in the initial pixel data is 50, and the pixel value corresponding to the updated candidate pixel data is 60, then the pixel difference value corresponding to the pixel is 10.
- the initial pixel data also includes: the pixel values of each pixel located outside the light spot and within the circumscribed rectangle, therefore, in step 3044, it is also necessary to determine the relationship between each pixel outside the light spot and within the circumscribed rectangle. The corresponding pixel value difference.
- Step 3045 based on the pixel value difference value corresponding to each pixel in the area where the light spot is located, update the weight corresponding to each pixel in the area where the light spot is located.
- the processing device may update the weight corresponding to each pixel in the area where the light spot is located based on the pixel value difference value corresponding to each pixel in the area where the light spot is located.
- the weight is also negatively correlated with the pixel value difference. That is, when the pixel value difference corresponding to the pixel is larger, the weight corresponding to the pixel is smaller; when the pixel value difference corresponding to the pixel is smaller, the weight corresponding to the pixel is larger. .
- the value range of the weight is [0, 1], but since the pixel value of each pixel has certain noise, the weight corresponding to each pixel can be set to 0 or 1. For example, when the pixel value difference corresponding to a certain pixel is within the preset difference range, it is determined that the pixel value difference corresponding to the pixel is 1; when the pixel value difference corresponding to a certain pixel is within When it is outside the preset difference value range, it is determined that the pixel value difference value corresponding to the pixel point is 0.
- the pixel value difference value corresponding to a pixel point when the pixel value difference value corresponding to a pixel point is 1, the pixel value of the pixel point has less influence on the fitting result obtained after surface fitting of the light spot, and the pixel value corresponding to the pixel point has less influence.
- the value will participate in the process of surface fitting of the light spot; when the pixel value difference corresponding to a pixel point is 0, the pixel value of the pixel point has a greater influence on the fitting result obtained after surface fitting of the light spot. , the pixel value corresponding to this pixel point will not participate in the process of surface fitting of the light spot.
- step 3045 when the pixel value difference corresponding to each pixel located outside the light spot and within the circumscribed rectangle is determined in step 3044, step 3045 also needs to update each pixel located outside the light spot and within the circumscribed rectangle. corresponding weight.
- step 3045 a fitting process is performed.
- step 3041 needs to be performed repeatedly to perform the fitting process again.
- the radiotherapy apparatus may determine the model parameters to be selected obtained from the last fitting process as the model parameters of the first surface fitting model. At this time, the accuracy of the determined model parameters of the first curved surface fitting model is high, so that the accuracy of determining the coordinates of the center point of the light spot is high.
- the cut-off condition may include: the processing device has performed the fitting process for a specified number of times; or, the model parameters to be selected obtained after the fitting process currently performed by the processing device are the same as the parameters obtained after the fitting process performed last time.
- the variation of the parameters of the model to be selected is less than the variation threshold.
- the radiotherapy device can determine the model parameters to be selected obtained in the last fitting process as the model parameters of the first surface fitting model.
- the processing device can perform the last fitting process.
- the candidate model parameters obtained during the fitting process are determined as the model parameters of the first surface fitting model.
- Step 305 based on the first curved surface fitting model and the obtained model parameters, update the pixel value of each pixel in the light spot to obtain updated pixel data.
- the processing device may, based on the model parameters of the first curved surface fitting model, perform an analysis on the pixels of each pixel in the area where the light spot is located. The value is updated to get the updated pixel data.
- step 305 reference may be made to the foregoing step 3043, and details are not described herein again in this embodiment of the present application.
- Step 306 Determine the pixel data of the shadow based on the updated pixel data and the initial pixel data.
- the processing device may determine the pixel data of the shadow based on the updated pixel data and the initial pixel data.
- the pixel data of the shadow includes: pixel values of each pixel in the region where the shadow is located.
- the processing device may correspondingly subtract the pixel value of each pixel in the updated pixel data from the pixel value of each pixel in the original pixel data, so as to obtain the pixel data of the shadow.
- the pixel data of the shadow is obtained based on the updated pixel data and the initial pixel data, therefore, the The pixel data of the shadow also includes: pixel values of each pixel located outside the shadow and within the circumscribed rectangle.
- Step 307 Based on the pixel data of the shadow, use the second surface fitting model to perform surface fitting processing on the shadow to obtain model parameters of the second surface fitting model.
- the processing device may use the second surface fitting model to perform surface fitting processing on the shadow based on the pixel data of the shadow, so as to obtain model parameters of the second surface fitting model.
- the model parameters of the second surface fitting model include: coordinates of the center point of the shadow.
- the second surface fitting model may also be a two-dimensional Gaussian surface fitting model.
- this step 3025 reference may be made to the corresponding content in the foregoing step 3022. Therefore, based on the pixel data of the shadows, there are also many possible ways to calculate the model parameters of the second surface fitting model.
- the embodiments of the present application are schematically illustrated by taking the following two possible implementation manners as examples:
- the second surface fitting model may be directly used to perform surface fitting processing on the shadow, and reference may be made to the corresponding content in the above-mentioned first optional implementation manner. This embodiment of the present application will not be repeated here.
- corresponding weights may be assigned to each pixel point corresponding to the pixel data of the shadow.
- the weight is used to reflect the degree of influence of the pixel value of the corresponding pixel on the fitting result obtained by performing surface fitting on the shadow. It should be noted that the numerical value of the weight is negatively correlated with the degree of influence of the fitting result obtained by performing surface fitting on the shadow. In this way, when the shadow is surface-fitted based on the pixel data of the shadow and the weight corresponding to each pixel point, the accuracy of the center point of the finally obtained shadow is effectively improved.
- the second surface fitting model is used to perform surface fitting processing on the shadow, so as to obtain model parameters of the second surface fitting model, including:
- the fitting process may include the following steps:
- Step 3071 Obtain a second weight matrix.
- step 3071 reference may be made to the foregoing step 3041, and details are not described herein again in this embodiment of the present application.
- Step 3072 Based on the pixel data of the shadow and the weights corresponding to each pixel in the region where the shadow is located, use the second surface fitting model to perform surface fitting processing on the shadow to obtain model parameters to be selected for the second surface model.
- step 3072 reference may be made to the foregoing step 3042, and details are not described herein again in this embodiment of the present application.
- Step 3073 based on the second surface fitting model and the acquired parameters of the candidate model, update the pixel data of the shadow to obtain the updated candidate pixel data.
- step 3073 reference may be made to the foregoing step 3043, which is not described again in this embodiment of the present application.
- Step 3074 based on the updated pixel data to be selected and the pixel data of the shadow, determine the pixel value difference corresponding to each pixel in the region where the shadow is located.
- step 3074 reference may be made to the foregoing step 3044, and details are not described herein again in this embodiment of the present application.
- Step 3075 Based on the pixel value difference corresponding to each pixel in the region where the shadow is located, update the weight corresponding to each pixel in the shadow, where the weight is negatively correlated with the pixel value difference.
- step 3075 reference may be made to the foregoing step 3045, which is not described again in this embodiment of the present application.
- step 3075 a fitting process is performed.
- step 3071 needs to be performed repeatedly to perform the fitting process again.
- the radiotherapy apparatus may determine the model parameters to be selected obtained from the last fitting process as the model parameters of the second surface fitting model. At this time, the accuracy of the determined model parameters of the second curved surface fitting model is high, so that the accuracy of determining the coordinates of the center point of the shadow is high.
- the cut-off condition may include: the radiotherapy equipment has performed the fitting process for a specified number of times; or, the model parameters to be selected obtained after the fitting process currently performed by the radiotherapy equipment are different from the parameters obtained after the fitting process performed last time.
- the variation of the parameters of the model to be selected is less than the variation threshold.
- the present application provides two ways to determine the coordinates of the center point in the light spot and the shadow. That is, one is the coordinates of the center point in the spot and shadow determined when each pixel is not weighted; the other is the coordinates of the center point in the spot and shadow determined when each pixel is weighted.
- the coordinates of the center point in the light spot and the shadow determined when each pixel is weighted are more accurate than the coordinates of the center point in the light spot and the shadow determined when each pixel is not weighted.
- FIG. 7 is a three-dimensional simulation diagram of initial pixel data provided by an embodiment of the present application.
- the abscissa of each pixel in the numerical initial pixel data on the x-axis, the ordinate of each pixel in the numerical initial pixel data on the y-axis, and the data on the z-axis represent each pixel in the initial pixel data pixel value.
- FIG. 9 is the 3D simulation diagram of the updated pixel data obtained in the above step 3023
- FIG. 9 is the 3D simulation diagram of the pixel data of the shadow obtained in the above step 3024 .
- FIG. 10 is a 3D simulation diagram of the updated pixel data obtained in the above step 3023
- FIG. 11 is a 3D simulation diagram of the shadow pixel data obtained in the above step 3024 .
- projection data is acquired from a detector in a radiotherapy device through a processing device, and after image data is generated based on the projection data, the image data is processed to obtain The coordinates of the center point of the light spot and the center point of the shadow are obtained.
- the verification of the isocenter of the radiotherapy equipment can be realized. There is no need to verify the isocenter of the radiotherapy equipment by manually analyzing the film, which effectively improves the verification efficiency of the isocenter of the radiotherapy equipment.
- FIG. 12 is a flowchart of an isocenter verification method for radiotherapy equipment provided by an embodiment of the present application.
- the isocenter verification method for radiotherapy equipment can be applied to the isocenter verification system for radiotherapy equipment shown in FIG. 1 .
- Methods for isocentric validation of the radiotherapy device may include:
- Step 401 Acquire, from a detector, at least two projection data generated when the treatment heads of the radiotherapy equipment are located at different positions, and generate at least two image data based on the at least two projection data.
- Each image data contains a light spot formed after the radiation beam generated by the treatment head of the radiotherapy equipment is blocked by the radiation blocking body and the shadow located in the light spot.
- Step 402 using an image processing method to process each image data to obtain the coordinates of the center point of the light spot and the coordinates of the center point of the shadow in each image data.
- the image processing method shown in FIG. 3 or FIG. 4 may be used to process each image data.
- Step 403 Determine the offset between the isocenter of the radiotherapy equipment and the treatment isocenter based on the coordinates of the center point of the light spot and the coordinates of the center point of the shadow in each image data.
- the isocenter verification method for radiotherapy equipment generateds at least two image data generated by the treatment heads in the radiotherapy equipment at different positions through the processing equipment in the radiotherapy equipment, and it can be determined that each The coordinates of the center point of the light spot and the center point of the shadow in each image data, in this way, after determining the offset between the center point of the light spot and the center point of the shadow in each image data, we can get The offset between the isocenter of the radiotherapy equipment and the treatment isocenter, so as to realize the verification of the isocenter of the radiotherapy equipment. There is no need to verify the isocenter of the radiotherapy equipment by manually analyzing the film, which effectively improves the verification efficiency of the isocenter of the radiotherapy equipment.
- FIG. 13 is a flowchart of another method for isocenter verification of radiotherapy equipment provided by an embodiment of the present application.
- the isocenter verification method for radiotherapy equipment can be applied to the isocenter verification of radiotherapy equipment shown in FIG. 1 .
- Methods for isocentric validation of the radiotherapy device may include:
- Step 501 when the treatment head of the radiotherapy equipment is located at the first position, acquire projection data corresponding to the first position from the detector and generate first image data.
- the processing apparatus may acquire projection data generated when the treatment head is at the first position from the detector, and generate first image data based on the projection data.
- Step 502 When the treatment head of the radiotherapy equipment is located at the second position, acquire projection data corresponding to the second position from the detector and generate second image data.
- the processing apparatus may acquire projection data generated when the treatment head is at the second position from the detector, and generate second image data based on the projection data.
- each image data has a light spot and a shadow within the light spot.
- each image data may refer to the image shown in FIG. 2 .
- the direction of the radiation beam emitted when the treatment head of the radiotherapy device is located at the first position is perpendicular to the direction of the radiation beam emitted when the treatment head of the radiation therapy device is located at the second position. That is, the direction of the ray beam emitted when the treatment head is at the first position is perpendicular to the direction of the ray beam emitted when the treatment head is positioned at the second position. In this way, it is convenient for the subsequent radiotherapy equipment to determine the offsets between the isocenter of the radiotherapy equipment and the treatment isocenter in different directions, so that the efficiency of verifying the isocenter of the radiotherapy equipment can be further improved.
- the ray beams emitted by multiple radiation sources in the treatment head can be analyzed, and the ray beams emitted by one of the multiple radiation sources can also be analyzed.
- the image data generated by the processing device contains multiple light spots;
- the image data generated by the device contains a light spot.
- Step 503 For each image data in the first image data and the second image data, use an image processing method to process each image data to obtain the coordinates of the center point of the light spot and the center of the shadow in each image data. the coordinates of the point.
- the image data processing method shown in FIG. 3 or FIG. 4 may be used to process each image data, so as to obtain each image data.
- the coordinates of the center point of the light spot and the center point of the shadow in the image data may be used to process each image data.
- Step 504 Based on the coordinates of the center point of the light spot and the coordinates of the center point of the shadow in the first image data, determine a first offset between the center point of the light spot and the center point of the shadow in the first image data.
- the processing device may determine the distance between the center point of the light spot and the center point of the shadow in the first image data based on the coordinates of the center point of the light spot and the coordinates of the center point of the shadow in the first image data first offset.
- Step 505 based on the coordinates of the center point of the light spot and the coordinates of the center point of the shadow in the second image data, determine a second offset between the center point of the light spot and the center point of the shadow in the second image data.
- the processing device may determine the distance between the light spot and the center point and the center point of the shadow in the second image data based on the coordinates of the center point of the light spot and the coordinates of the center point of the shadow in the second image data Second offset.
- Step 506 based on the first offset and the second offset, determine the offset between the isocenter of the radiotherapy equipment and the treatment isocenter.
- the processing device may determine the offset between the center point of the light spot and the center point of the shadow in the three-dimensional space based on the first offset and the second offset, so that the processing device may determine the location of the radiation therapy device The offset between the isocenter and the treatment isocenter, so that the isocenter of the radiotherapy equipment can be verified.
- the processing device can control the treatment couch in the radiotherapy device to perform compensation movement, so as to realize the correction of the radiotherapy device.
- the isocenter of the radiotherapy equipment was calibrated.
- the isocenter verification method for radiotherapy equipment generateds at least two image data generated by the treatment heads in the radiotherapy equipment at different positions through the processing equipment in the radiotherapy equipment, and it can be determined that each The coordinates of the center point of the light spot and the center point of the shadow in each image data, in this way, after determining the offset between the center point of the light spot and the center point of the shadow in each image data, we can get The offset between the isocenter of the radiotherapy equipment and the treatment isocenter, so as to realize the verification of the isocenter of the radiotherapy equipment. There is no need to verify the isocenter of the radiotherapy equipment by manually analyzing the film, which effectively improves the verification efficiency of the isocenter of the radiotherapy equipment.
- the embodiment of the present application provides an isocenter verification system for radiotherapy equipment, as shown in FIG. in:
- the radiotherapy equipment 101 may include: a treatment head 1011 and a detector 1012 arranged oppositely.
- the detector 1012 is used for receiving the radiation beam generated by the treatment head 1011 and converting it into projection data.
- the radiation blocking body 102 is detachably installed at the isocenter of the radiotherapy equipment 101 , and the center of the radiation blocking body 102 is coincident with the isocenter of the radiotherapy equipment 101 .
- the processing device 103 is electrically connected to the detector 101 , and the processing device is used for the isocentric verification method of the radiotherapy device shown in FIG. 12 or FIG. 13 .
- the radiotherapy equipment 101 may further include: a rotating gantry 1013 .
- Both the treatment head 1011 and the detector 1012 are arranged on the rotating gantry 1013, and the rotating frame 1013 can drive the treatment head 1011 and the detector 1012 to rotate at the same time. In this way, by rotating the gantry 1013, the treatment head 1011 can be controlled to be located in different positions.
- the ray blocking body may be a ray blocking ball.
- the ray blocking ball may be a metal ball.
- the metal balls may be tungsten balls.
- the isocenter verification system 100 of the radiotherapy equipment may further include: a detection phantom 104 .
- the radiation blocking body 102 can be installed at the center of the detection phantom 104 , and the radiation blocking body 102 can be detachably installed at the isocenter of the radiotherapy apparatus 101 through the detection phantom 104 .
- the radiotherapy apparatus 101 may further include: a treatment couch 1014 , and the detection phantom 104 is detachably installed at a preset position of the treatment couch 1014 and located at the isocenter of the radiotherapy apparatus 100 .
- the detection phantom 104 may be a box-shaped box of any shape, for example, as shown in FIG. 1 , may be a cube-shaped box.
- the staff can adjust the height of the treatment couch 1014 so that the isocenter of the radiotherapy equipment 101 and the spherical center of the radiation blocking body 102 are at the same height; after that, work
- the staff moves the treatment couch 1014 below the treatment head 1011 to make the center of the radiation blocking body 102 coincide with the isocenter of the radiotherapy equipment 101; finally, the staff turns on the treatment head 1011, and the treatment head 1011 emits a beam of rays.
- the present application also provides an isocenter verification device for radiotherapy equipment, and the isocenter verification device for radiotherapy equipment may be the processing device in the above embodiment.
- the verification apparatus may include: a processor and a memory, wherein at least one instruction is stored in the memory, and the instruction is loaded and executed by the processor to implement the isocentric verification method of the radiotherapy apparatus shown in FIG. 12 or FIG. 13 .
- Embodiments of the present application further provide a computer-readable storage medium, where at least one instruction is stored in the storage medium, and the instruction is loaded and executed by a processor to implement the image data processing method shown in FIG. 3 or FIG. 4 , or The verification method of the isocenter of the radiotherapy equipment as shown in FIG. 12 or FIG. 13 .
Landscapes
- Health & Medical Sciences (AREA)
- Life Sciences & Earth Sciences (AREA)
- Engineering & Computer Science (AREA)
- Biomedical Technology (AREA)
- Veterinary Medicine (AREA)
- Radiology & Medical Imaging (AREA)
- Nuclear Medicine, Radiotherapy & Molecular Imaging (AREA)
- Animal Behavior & Ethology (AREA)
- General Health & Medical Sciences (AREA)
- Public Health (AREA)
- Pathology (AREA)
- Medical Informatics (AREA)
- High Energy & Nuclear Physics (AREA)
- Biophysics (AREA)
- Physics & Mathematics (AREA)
- Optics & Photonics (AREA)
- Heart & Thoracic Surgery (AREA)
- Molecular Biology (AREA)
- Surgery (AREA)
- Apparatus For Radiation Diagnosis (AREA)
- Image Processing (AREA)
Abstract
一种图像数据的处理方法、放疗设备的等中心验证方法及系统。该放疗设备的等中心验证方法包括：从探测器获取放疗设备的治疗头位于不同位置时产生的至少两个投影数据，并基于至少两个投影数据生成至少两个图像数据；采用图像数据处理方法对每个图像数据进行处理，以得到每个图像数据中的光斑的中心点的坐标和暗影的中心点的坐标；基于每个图像数据中的光斑的中心点的坐标和暗影的中心点的坐标，确定放疗设备的等中心与治疗等中心之间的偏移量，从而实现对放疗设备的等中心的验证。无需通过人工分析胶片的方式对放疗设备的等中心进行验证，有效的提高了对放疗设备的等中心的验证效率。
Description
本申请涉及医疗器械技术领域，特别涉及一种图像数据的处理方法、放疗设备的等中心验证方法及系统。
放射治疗是治疗癌症的一项重要手段，放射治疗设备(简称放疗设备)是开展放射治疗的关键医疗设备。
放疗设备通常可以包括：旋转机架，以及位于旋转机架上的治疗头。在采用放疗设备对患者进行治疗时，需要保证放疗设备的等中心与治疗等中心之间的偏移量小于预设值。否则，治疗头出射的射线束可能不会照射到患者的靶区，导致放疗设备无法对患者靶区进行准确的治疗。
相关技术中，当需要对放疗设备的等中心进行验证时，治疗头的射线束需要照射在胶片上，以在胶片上形成焦斑，该焦斑的中心即为治疗等中心。并需要人工分析该焦斑的中心与预设点(该预设点即为放疗设备的等中心)的偏移量，来实现对放疗设备的等中心的验证。但是，目前通过胶片对放疗设备的等中心进行验证的效率较低。
发明内容
本申请实施例提供了一种图像数据的处理方法、放疗设备的等中心验证方法及系统。可以解决现有技术的通过胶片对放疗设备的等中心进行验证的效率较低的问题，所述技术方案如下：
一方面，提供了一种图像数据的处理方法，所述图像数据是处理设备从探测器获取到投影数据后，基于所述投影数据生成的数据，所述图像数据中含有所述放疗设备的治疗头产生的射线束经射线阻挡体阻挡后形成的光斑和位于所述光斑中的暗影；所述方法包括：
确定初始像素数据，所述初始像素数据包括：所述光斑所在区域内的各个像素点的像素值；
基于所述初始像素数据，采用第一曲面拟合模型对所述光斑进行曲面拟合处理，以得到所述第一曲面拟合模型的模型参数，所述第一曲面拟合模型的模型参数包括：所述光斑的中心点的坐标；
基于所述第一曲面拟合模型及获取的模型参数，对所述光斑所在区域内的各个像素点的像素值进行更新，得到更新后的像素数据；
基于所述更新后的像素数据和所述初始像素数据，确定所述暗影的像素数据，所述暗影的像素数据包括：所述暗影所在区域内的各个像素点的像素值；
基于所述暗影的像素数据，采用第二曲面拟合模型对所述暗影进行曲面拟合处理，以得到所述第二曲面拟合模型的模型参数，所述第二曲面拟合模型的模型参数包括：所述暗影的中心点的坐标。
可选的，基于所述初始像素数据，采用第一曲面拟合模型对所述光斑进行曲面拟合处理，以得到所述第一曲面拟合模型的模型参数，包括：
基于所述初始像素数据，对所述光斑执行至少一次拟合过程，直至达到截止条件，将最后一次拟合过程得到的待选模型参数确定为所述第一曲面拟合模型的模型参数；
其中，所述拟合过程包括：
基于所述初始像素数据和所述光斑所在区域内的各个像素点对应的权重，采用所述第一曲面拟合模型对所述光斑进行曲面拟合处理，以得到所述第一曲面模型的待选模型参数；
基于所述第一曲面拟合模型及获取的待选模型参数，对所述初始像素数据进行更新，得到更新后的待选像素数据；
基于所述更新后的待选像素数据与所述初始像素数据，确定与所述光斑所在区域内的各个像素点对应的像素值差值；
基于与所述光斑所在区域内的各个像素点对应的像素值差值，更新与所述光斑所在区域内的各个像素点对应的权重，所述权重与所述像素值差值负相关。
可选的，基于所述暗影的像素数据，采用第二曲面拟合模型对所述暗影进行曲面拟合处理，以得到所述第二曲面拟合模型的模型参数，包括：
基于所述暗影的像素数据，对所述暗影执行至少一次拟合过程，直至达到截止条件，将最后一次拟合过程得到的待选模型参数确定为所述第二曲面拟合模型的模型参数；
其中，所述拟合过程包括：
基于所述暗影的像素数据和所述暗影所在区域内的各个像素点对应的权重，采用所述第二曲面拟合模型对所述暗影进行曲面拟合处理，以得到所述第二曲面模型的待选模型参数；
基于所述第二曲面拟合模型及获取的待选模型参数，对所述暗影的像素数据进行更新，得到更新后的待选像素数据；
基于所述更新后的待选像素数据与所述暗影的像素数据，确定与所述暗影所在区域内的各个像素点对应的像素值差值；
基于与所述暗影所在区域内的各个像素点对应的像素值差值，更新与所述暗影所在区域内的各个像素点对应的权重，所述权重与所述像素值差值负相关。
可选的，所述截止条件包括：执行了指定次数的拟合过程；或者，当前执行的拟合过程后得到的待选模型参数，与上一次执行的拟合过程后得到的待选模型参数的变化量小于变化阈值。
可选的，所述第一曲面拟合模型与所述第二曲面拟合模型均为：二维高斯曲面拟合模型。
可选的，所述确定初始像素数据，包括：
对所述图像数据中的光斑进行轮廓提取处理，得到所述光斑的轮廓；
基于所述光斑的轮廓，确定所述光斑的轮廓的外接矩形；
将所述外接矩形内的各个像素点的原始的像素值，确定为所述初始像素数据。
另一方面，提供了一种放疗设备的等中心验证方法，所述方法包括：
从探测器获取放疗设备的治疗头位于不同位置时产生的至少两个投影数据，并基于所述至少两个投影数据生成至少两个图像数据，每个所述图像数据中含有放疗设备的治疗头产生的射线束经射线阻挡体阻挡后形成的光斑和位于所述光斑中的暗影；
采用上述任一所述的图像数据处理方法对每个所述图像数据进行处理，以得到每个所述图像数据中的光斑的中心点的坐标和暗影的中心点的坐标；
基于每个所述图像数据中的光斑的中心点的坐标和暗影的中心点的坐标，确定放疗设备的等中心与治疗等中心之间的偏移量。
可选的，从探测器获取放疗设备的治疗头位于不同位置时产生的至少两个 投影数据，并基于所述至少两个投影数据生成至少两个图像数据，包括：
基于所述放疗设备的治疗头位于第一位置时，从所述探测器获取与所述第一位置对应的投影数据并生成第一图像数据；
基于所述放疗设备的治疗头位于第二位置时，从所述探测器获取与所述第二位置对应的投影数据并生成第二图像数据；
基于每个所述图像数据中的光斑的中心点的坐标和暗影的中心点的坐标，确定放疗设备的等中心与治疗等中心之间的偏移量，包括：
基于所述第一图像数据中的光斑的中心点的坐标和暗影的中心点的坐标，确定所述第一图像数据中的光斑的中心点和暗影的中心点之间的第一偏移量；
基于所述第二图像数据中的光斑的中心点的坐标和暗影的中心点的坐标，确定所述第二图像数据中的光斑的中心点和暗影的中心点之间的第二偏移量；
基于所述第一偏移量和所述第二偏移量，确定放疗设备的等中心与治疗等中心之间的偏移量。
可选的，所述放疗设备的治疗头位于第一位置时出射的射线束的方向，与所述放疗设备的治疗头位于第二位置时出射的射线束的方向垂直。
又一方面，提供了一种放疗设备的等中心验证系统，所述系统包括放疗设备、射线阻挡体和处理设备，其中，
所述放疗设备包括：相对设置的治疗头和探测器，所述探测器用于接收所述治疗头产生的射线束并转换为投影数据；
所述射线阻挡体可拆卸安装在所述放疗设备的等中心处，所述射线阻挡体的中心与所述放疗设备的等中心相重合；
所述处理设备与所述探测器电连接，所述处理设备用于执行上述任一所述的放疗设备的等中心验证方法。
可选的，所述射线阻挡体为射线阻挡球。
可选的，所述射线阻挡球为金属球。
可选的，所述系统还包括检测模体，所述射线阻挡体安装在所述检测模体的中心位置处，所述射线阻挡体通过所述检测模体可拆卸安装在所述放疗设备的等中心处。
可选的，所述放疗设备还包括治疗床，所述检测模体可拆卸安装在所述治疗床的预设位置处，且位于所述放疗设备的等中心处。
再一方面，提供了一种计算机可读存储介质，所述存储介质中存储有至少一条指令，所述指令由处理器加载并执行以实现上述任一所述的图像数据处理方法，或上述任一所述的放疗设备的等中心验证方法。
本申请实施例提供的技术方案带来的有益效果至少包括：
通过处理设备从放疗设备中的探测器获取投影数据，并基于该投影数据生成的图像数据后，对该图像数据进行处理，以得到光斑的中心点的坐标和暗影的中心点的坐标，如此，后续通过确定光斑的中心点与暗影的中心点之间的偏移量，即可实现对放疗设备的等中心的验证。无需通过人工分析胶片的方式对放疗设备的等中心进行验证，有效的提高了对放疗设备的等中心的验证效率。
为了更清楚地说明本申请实施例中的技术方案，下面将对实施例描述中所需要使用的附图作简单地介绍，显而易见地，下面描述中的附图仅仅是本申请的一些实施例，对于本领域普通技术人员来讲，在不付出创造性劳动的前提下，还可以根据这些附图获得其他的附图。
图1是本申请实施例提供的一种放疗设备的等中心验证系统的结构示意图；
图2是本申请实施例提供的一种图像数据的示意图；
图3是本申请实施例提供的一种图像数据的处理方法的流程图；
图4是本申请实施例提供的另一种图像数据的处理方法的流程图；
图5是本申请实施例提供的一种对光斑进行轮廓提取处理后的示意图；
图6是本申请实施例提供的一种光斑的轮廓的外接矩形的示意图；
图7是本申请实施例提供的一种初始像素数据的三维模拟图；
图8是本申请实施例提供的一种对初始像素数据进行更新后得到更新后的像素数据的三维模拟图；
图9是本申请实施例提供的一种基于更新后的像素数据和初始像素数据确定出的暗影的像素数据的三维模拟图；
图10是本申请实施例提供的另一种对初始像素数据进行更新后得到更新后的像素数据的三维模拟图；
图11是本申请实施例提供的另一种基于更新后的像素数据和初始像素数据确定出的暗影的像素数据的三维模拟图；
图12是本申请实施例提供的一种放疗设备的等中心验证方法的流程图；
图13是本申请实施例提供的另一种放疗设备的等中心验证方法的流程图。
为使本申请的目的、技术方案和优点更加清楚，下面将结合附图对本申请实施方式作进一步地详细描述。
请参考图1，图1是本申请实施例提供的一种放疗设备的等中心验证系统的结构示意图。该放疗设备的等中心验证系统100可以包括：放疗设备101、射线阻挡体102和处理设备103。
该放疗设备101可以包括：相对设置的治疗头1011和探测器1012。该探测器1012可以为：电子射野影像装置(英文：Electronic Portal Imaging Device；简称：EPID)。该探测器1012用于接收治疗头1011产生的射线束并转化为投影数据。
该射线阻挡体102可拆卸安装在放疗设备101的等中心处，该射线阻挡体102的中心可以与放疗设备101的等中心相重合。
该处理设备103可以与放疗设备101中的探测器1012电连接。该处理设备103可以从该探测器1012获取投影数据，并基于该投影数据生成图像数据。该图像数据中含有放疗设备101中的治疗头1011产生的射线束经射线阻挡体102阻挡后形成的光斑和位于该光斑内的暗影。
示例的，放疗设备101中的治疗头1011通常包含多个放射源，每个放射源出射的射线束均会经过射线阻挡体102后照射在探测器1012上，并由探测器1012将接收到的射线束转化为投影数据。之后，处理设备103可以从探测器1012获取投影数据，并将其转换为图像数据。例如，请参考图2，图2是本申请实施例提供的一种图像数据的示意图。由于治疗头1011中的每个放射源发出的射线束均会经过射线阻挡体102后照射在探测器1012上，因此，由处理设备103生出的图像数据包括与多个放射源一一对应的多个光斑01，且每个光斑01内均具有暗影02。
可选的，该放疗设备101还可以包括：旋转机架1013，治疗头1011和探测器1012均设置在该旋转机架1013上，该旋转机架1013能够同时带动治疗头1011和探测器1012转动。如此，通过旋转机架1013可以控制治疗头1011位于不同 的位置。
请参考图3，图3是本申请实施例提供的一种图像数据的处理方法的流程图。该图像数据处理方法可以应用于图1示出的放疗设备的等中心验证系统100中的处理设备103。该图像数据可以是处理设备103从放疗设备101中的探测器1012获取到投影数据后，基于该投影数据生成的数据。例如，该图像数据可以参考图2示出的图像，该图像数据中含有放疗设备101的治疗头1011产生的射线束经射线阻挡体102阻挡后形成的光斑01和位于该01光斑中的暗影02。该图像数据的处理方法可以包括：
步骤201、确定初始像素数据。该初始像素数据包括：光斑所在区域内的各个像素点的像素值。
步骤202、基于初始像素数据，采用第一曲面拟合模型对光斑进行曲面拟合处理，以得到第一曲面拟合模型的模型参数。该第一曲面拟合模型的模型参数包括：光斑的中心点的坐标。
步骤203、基于第一曲面拟合模型及获取的模型参数，对光斑所在区域内的各个像素点的像素值进行更新，得到更新后的像素数据。
步骤204、基于更新后的像素数据和初始像素数据，确定暗影的像素数据。该暗影的像素数据包括：暗影所在区域内的各个像素点的像素值。
步骤205、基于暗影的像素数据，采用第二曲面拟合模型对暗影进行曲面拟合处理，以得到第二曲面拟合模型的模型参数。该第二曲面拟合模型的模型参数包括：暗影的中心点的坐标。
综上所述，本申请实施例提供的图像数据的处理方法，通过处理设备从放疗设备中的探测器获取投影数据，并基于该投影数据生成的图像数据后，对该图像数据进行处理，以得到光斑的中心点的坐标和暗影的中心点的坐标，如此，后续通过确定光斑的中心点与暗影的中心点之间的偏移量，即可实现对放疗设备的等中心的验证。无需通过人工分析胶片的方式对放疗设备的等中心进行验证，有效的提高了对放疗设备的等中心的验证效率。
请参考图4，图4是本申请实施例提供的另一种图像数据的处理方法的流程图。该图像数据处理方法可以应用于图1示出的放疗设备的等中心验证系统100 中的处理设备103。该图像数据可以是处理设备103从放疗设备101中的探测器1012获取到投影数据后，基于该投影数据生成的数据。例如，该图像数据可以参考图2示出的图像，该图像数据中含有放疗设备101的治疗头1011产生的射线束经射线阻挡体102阻挡后形成的光斑01和位于该01光斑中的暗影02。该图像数据的处理方法可以包括：
步骤301、对图像数据中的光斑进行轮廓提取处理，得到该光斑的轮廓。
在本申请实施例中，处理设备可以采用诸如分水岭分割算法的图像分割算法对图像中的光斑进行轮廓提取处理，以得到该光斑的轮廓。
例如，如图5所示，图5是本申请实施例提供的一种对光斑进行轮廓提取处理后的示意图。在对图2示出的图像数据中的光斑进行轮廓提取处理后，可以得到光斑的轮廓03。
步骤302、基于该光斑的轮廓，确定该光斑的轮廓的外接矩形。
在本申请实施例中，处理设备可以基于光斑的轮廓，确定光斑的轮廓的外接矩形。
需要说明的是，本申请实施例既可以对治疗头中的多个放射源出射的射线束进行分析，也可以对多个放射源中的某一个放射出射的射线束进行分析。
当需要对个治疗头中的多个放射源出射的射线束进行分析时，需要让治疗头中的多个放射源同时出射射线束，如此处理设备生成的图像数据包含了多个光斑。在这种情况下，如图2和图5所示，由于在多个光斑中两个相邻的光斑的距离较近，因此，若对图像中的多个光斑进行轮廓提取后，两个相邻的光斑的轮廓是相连的。
如图6所示，图6是本申请实施例提供的一种光斑的轮廓的外接矩形的示意图。为了得到各个光斑的外接矩形，需要将各个光斑的轮廓进行补齐处理，以得到补齐处理后的轮廓04，该补齐处理后的轮廓04近似为椭圆。之后，可以将椭圆的外接矩形确定为光斑的轮廓的外接矩形05。如此，可以得到各个光斑的轮廓的外接矩形。
当需要对治疗头中的某一个放射源出射的射线束进行分析时，需要让治疗头中待分析的放射源出射射线束，而屏蔽除待分析的放射源之外的放射源出射的射线束，如此处理设备生成的图像数据包含一个光斑。在这种情况下，对该光斑进行轮廓提取处理后得到的光斑的轮廓近似为椭圆，如此便无需对该光斑 的轮廓进行补齐处理。
步骤303、将该外接矩形内的各个像素点的原始的像素值，确定为初始像素数据。
在本申请实施例中，处理设备可以将外接矩形内的各个像素点的原始的像素值，确定为初始像素数据。该初始像素数据可以包括：光斑所在区域内的各个像素点的像素值。该初始像素数据还可以包括：位于光斑外且位于该光斑所在区域的外接矩形内的各个像素点的像素值。若图像数据中包括多个光斑，则该步骤303需要确定多个初始像素数据，以使后续处理设备能够确定出各个光斑的中心点的位置。
步骤304、基于初始像素数据，采用第一曲面拟合模型对光斑进行曲面拟合处理，以得到第一曲面拟合模型的模型参数。
在本申请实施例中，处理设备可以基于初始像素数据，采用第一曲面拟合模型对光斑进行曲面拟合处理，以得到第一曲面拟合模型的模型参数。该第一拟合模型的模型参数包括：光斑的中心点的坐标。
示例的，该第一曲面拟合模型可以为二维高斯曲面拟合模型。该二维高斯曲面拟合模型的表达式如下：
其中，(x，y)表示光斑的轮廓的外接矩形内的像素点的坐标；f(x，y)表示光斑的轮廓的外接矩形内的像素点的像素值，也即是，初始像素数据；G表示光斑的轮廓的外接矩形内各个像素点的像素值的最大值；x
0表示光斑的中心点的横坐标；y
0表示光斑的中心点的纵坐标；δ
x为x方向上的标准差；δ
y为y方向上的标准差。
在本申请中，上述公式(1)中的等号左边可以表示为初始像素数据，等号右边的各个参数可以表示为第一曲面拟合模型的模型参数。该第一曲面拟合模型的模型参数包括：光斑的中心点的坐标。如此，放疗设备可以通过初始像素数据确定出光斑的中心点的坐标，该光斑的中心点的坐标即为光斑的中心点的位置。
需要说明的是，在基于初始像素数据，计算第一曲面拟合模型中的模型参数时的方式有多种，本申请实施例以以下两种可实现方式为例进行示意性的说明：
在第一种可选的实现方式中，为了便于计算上述第一曲面拟合模型的模型参数，可以对上述公式(1)进行以下内容的公式转换。
首先，可以对公式(1)的等号两边同时取对数，并展开平方项，整理后可以得到公式(2)，如下：
之后，假设初始像素数据中包含N个数据点，也即是，光斑的轮廓的外接矩形内的像素点的个数为N个。则上述公式(2)可以用矩阵的形式表示，其可以表示为：A＝BC。
其中，A为N×1的矩阵，该N×1的矩阵中的元素为：
a
i＝f
i×lnf
i；
其中，a
i表示为N×1的矩阵中的矩阵中第i个元素；f
i表示为N个数据点中的第i个数据点。
B为N×5的矩阵，该N×5的矩阵可以表示为：
其中，x
i表示为N个数据点中的第i个数据点对应的横坐标；y
i表示为N个数据点中的第i个数据点对应的纵坐标。
C为5×1的矩阵，该5×1的矩阵可以表示为：
最后，根据矩阵A和矩阵B可以求出矩阵C。
在本申请实施例中，矩阵C中包含的各个元素共同构成了上述实施例中的第一曲面拟合模型的模型参数，且矩阵A和矩阵B均为已知量，因此基于矩阵A和矩阵B求出矩阵C后，便能够得到第一曲面拟合模型的模型参数。
需要说明的是，由于存在拟合误差，矩阵B和矩阵C相乘后通常并不等于距矩阵A，因此，N个数据点的误差E可以表示为：E＝A－BC。为此，在本申请实施例中可以采用最小二乘法对矩阵C进行拟合，得到矩阵C关于矩阵A和矩阵B的表达式为：
C＝[B
TB]
-1B
TA (3)
通过最小二乘法对矩阵C进行拟合得到的结果，在将其乘以矩阵B后，所得到的结果最接近矩阵A。
在本申请实施例中，通过上述公式(3)可以计算出矩阵C，即可得到第一曲面模型的模型参数。
需要说明的是，对于上述第一种可选的实现方式，由于光斑内还包含有暗影，该暗影会影响采用第一曲面拟合模型对光斑进行曲面拟合的拟合结果，若直接对光斑进行曲面拟合处理，得到的光斑的中心点的误差较大。因此，本申请实施例提供了下述第二种可选的实现方式，可以有效的提高确定光斑的中心点的准确性。
在第二种可选的实现方式中，在采用第一曲面拟合模型对光斑进行曲面拟合处理时，可以对初始像素数据所对应的各个像素点赋予相应的权重。该权重用于反映对应的像素点的像素值对光斑进行曲面拟合后得到的拟合结果的影响程度。需要说明的是，该权重的数值大小与对光斑进行曲面拟合后得到的拟合结果的影响程度负相关。如此，在基于初始像素数据以及与各个像素点对应的权重对光斑进行曲面拟合时，可以削弱暗影对光斑进行曲面拟合处理得到的拟合结果的影响程度，有效的提高了最终得到的光斑的中心点的准确性。
示例的，基于初始像素数据，采用第一曲面拟合模型对光斑进行曲面拟合处理，以得到第一曲面拟合模型的模型参数，包括：
基于初始像素数据，对光斑执行至少一次拟合过程，直至达到截止条件，将最后一次拟合过程得到的待选模型参数确定为第一曲面拟合模型的模型参数。其中，该拟合过程可以包括以下几个步骤：
步骤3041、获取第一权重矩阵。
在本申请实施例中，处理设备可以获取第一权重矩阵。该第一权重矩阵包括：与光斑内的各个像素点对应的权重。由于该第一权重矩阵中的多个数据，与初始像素数据中的多个数据是一一对应的。因此，当初始像素数据还包括：位于光斑外且位于外接矩形内的各个像素点的像素值时，该权重矩阵也还包括：与位于光斑外且位于外接矩形内的各个像素点对应的权重。
需要说明的是，本申请中与各个像素点对应的权重的取值范围为[0，1]。当第一次执行拟合过程时，放疗设备获取的第一权重矩阵中的各个像素点对应的权重均为1。
步骤3042、基于初始像素数据和光斑所在区域内的各个像素点对应的权重，采用第一曲面拟合模型对光斑进行曲面拟合处理，以得到第一曲面拟合模型的待选模型参数。
在本申请实施例中，处理设备可以基于初始像素数据以及步骤3041中获取到的第一权重矩阵，采用第一曲面拟合模型对光斑进行曲面拟合处理，从而可以得到第一曲面拟合模型的待选模型参数。
需要说明的是，在采用初始像素数据以及第一权重矩阵，对光斑进行拟合以得到第一曲面拟合模型的待选模型参数的过程，即为对上述公式(3)进行优化，可以得到新的矩阵C的表达式，如下：
C＝[B
TW
TWB]
-1B
TW
TWA (4)
其中，W表示第一权重矩阵。
在本申请实施例中，通过该公式(4)可以计算出矩阵C，即可得到第一曲面拟合模型的待选模型参数。
步骤3043、基于第一曲面拟合模型及获取的待选模型参数，对初始像素数据进行更新，得到更新后的待选像素数据。
在本申请实施例中，处理设备可以基于第一曲面拟合模型及获取的待选模型参数，对初始像素数据进行更新，得到更新后的待选像素数据。
示例的，可以采用上述公式(1)对初始像素数据进行更新，由于上述公式(1)中等号右边的各个参数即为步骤3042获取到的第一曲面拟合模型的待选模型参数。因此，通过该公式(1)可以重新对各个像素点的像素值进行计算，从而实现对初始像素数据的更新，以得到更新后的待选像素数据。
步骤3044、基于更新后的待选像素数据与初始像素数据，确定与光斑所在区域内的各个像素点对应的像素值差值。
在本申请实施例中，处理设备可以基于更新后的待选像素数据与初始像素数据，确定与光斑所在区域内的各个像素点对应的像素值差值。例如，假设对于某个像素点，在初始像素数据中对应的像素值为50，在更新后的待选像素数据对应的像素值为60，则与该像素点对应的像素差值为10。
需要说明的是，由于初始像素数据还包括：位于光斑外且位于外接矩形内的各个像素点的像素值，因此，在步骤3044中还需要确定与位于光斑外且位于外接矩形内的各个像素点对应的像素值差值。
步骤3045、基于与光斑所在区域内的各个像素点对应的像素值差值，更新与光斑所在区域内的各个像素点对应的权重。
在本申请实施例中，处理设备可以基于与光斑所在区域内的各个像素点对应的像素值差值，更新与光斑所在区域内的各个像素点对应的权重。
由于权重的数值大小与对光斑进行曲面拟合后得到的拟合结果的影响程度负相关，而与各个像素点对应的像素值差值即可反映对光斑进行曲面拟合后得到的拟合结果的影响程度。因此，该权重与像素值差值也呈负相关。也即是，当与像素点对应的像素值差值越大时，与该像素点对应的权重越小；当与像素点对应的像素值差值越小时，与该像素点对应的权重越大。
在本申请实施例中，权重的取值范围为[0，1]，但由于各个像素点的像素值本身存在一定噪声，因此可以将与各个像素点对应的权重设置为0或1。示例的，当某个像素点对应的像素值差值在预设的差值范围内时，确定与该像素点对应的像素值差值为1；当某个像素点对应的像素值差值在预设的差值范围外时，确定与该像素点对应的像素值差值为0。
需要说明的是，当某个像素点对应的像素值差值为1时，该像素点的像素值对光斑进行曲面拟合后得到的拟合结果的影响程度较小，该像素点对应的像素值会参与对光斑进行曲面拟合的过程；当某个像素点对应的像素值差值为0时，该像素点的像素值对光斑进行曲面拟合后得到的拟合结果的影响程度较大，该像素点对应的像素值不会参与对光斑进行曲面拟合的过程。
还需要说明的是，当步骤3044中确定与位于光斑外且位于外接矩形内的各个像素点对应的像素值差值时，步骤3045还需要更新定与位于光斑外且位于外接矩形内的各个像素点对应的权重。
在本申请实施例中，在执行步骤3045后，即执行完一次拟合过程。此时，需要重复执行步骤3041，以重新执行一次拟合过程。在执行至少一次拟合过程后，若达到截止条件，则放疗设备可以将最后一次拟合过程得到的待选模型参数确定为第一曲面拟合模型的模型参数。此时，确定出的第一曲面拟合模型的模型参数的准确性较高，使得确定光斑的中心点的坐标的准确性较高。
可选的，该截止条件可以包括：处理设备执行了指定次数的拟合过程；或者，处理设备当前执行的拟合过程后得到的待选模型参数，与上一次执行的拟合过程后得到的待选模型参数的变化量小于变化阈值。
在本申请实施例中，在处理设备执行了指定次数的拟合过程后，放疗设备即可将最后一次拟合过程得到的待选模型参数确定为第一曲面拟合模型的模型参数。或者，在处理设备当前执行的拟合过程后得到的待选模型参数，与上一次执行的拟合过程后得到的待选模型参数的变化量小于变化阈值后，处理设备即可将最后一次拟合过程得到的待选模型参数确定为第一曲面拟合模型的模型参数。
需要说明的是，对于上述第二种可选的实现方式，由于在采用第一曲面拟合模型对光斑进行曲面拟合处理时，对初始像素数据所对应的各个像素点赋予相应的权重，可以削弱暗影对光斑进行曲面拟合处理得到的拟合结果的影响程度，有效的提高了最终得到的光斑的中心点的准确性。
步骤305、基于第一曲面拟合模型及获取的模型参数，对光斑内的各个像素点的像素值进行更新，得到更新后的像素数据。
在本申请实施例中，在步骤304确定出第一曲面拟合模型的模型参数后，该处理设备可以基于该第一曲面拟合模型的模型参数，对光斑所在区域内的各个像素点的像素值进行更新，得到更新后的像素数据。
需要说明的是，该步骤305可以参考上述步骤3043，本申请实施例在此不再赘述。
步骤306、基于更新后的像素数据和初始像素数据，确定暗影的像素数据。
在本申请实施例中，处理设备可以基于更新后的像素数据和初始像素数据，确定暗影的像素数据。该暗影的像素数据包括：暗影所在区域内的各个像素点的像素值。
示例的，处理设备可以将更新后的像素数据中的各个像素点的像素值，与初始像素数据中各个像素点的像素值对应相减，即可得到该暗影的像素数据。
需要说明的是，由于初始像素数据还包括：位于光斑外且位于外接矩形内的各个像素点的像素值，该暗影的像素数据是基于更新后的像素数据和初始像素数据得到的，因此，该暗影的像素数据还包括：位于暗影外且位于外接矩形内的各个像素点的像素值。
步骤307、基于暗影的像素数据，采用第二曲面拟合模型对暗影进行曲面拟合处理，以得到第二曲面拟合模型的模型参数。
在本申请实施例中，处理设备可以基于暗影的像素数据，采用第二曲面拟 合模型对暗影进行曲面拟合处理，以得到第二曲面拟合模型的模型参数。该第二曲面拟合模型的模型参数包括：暗影的中心点的坐标。
在本申请中，该第二曲面拟合模型也可为二维高斯曲面拟合模型。示例的，该步骤3025可以参考上述步骤3022中的对应内容。因此，基于暗影的像素数据，计算第二曲面拟合模型的模型参数也有多种可实现方式。本申请实施例以以下两种可实现方式为例进行示意性说明的：
在第一种可实现方式中，可以直接采用第二曲面拟合模型对该暗影进行曲面拟合处理，其可以参考上述第一种可选的实现方式中的对应内容。本申请实施例在此不再赘述。
在第二种可实现方式中，在采用第二曲面拟合模型对暗影进行曲面拟合处理时，可以对暗影的像素数据所对应的各个像素点赋予相应的权重。该权重用于反映对应的像素点的像素值对暗影进行曲面拟合后得到的拟合结果的影响程度。需要说明地是，该权重的数值大小与对暗影进行曲面拟合后得到的拟合结果的影响程度负相关。如此，在基于暗影的像素数据以及与各个像素点对应的权重对暗影进行曲面拟合时，有效的提高了最终得到的暗影的中心点的准确性。
示例的，基于暗影的像素数据，采用第二曲面拟合模型对暗影进行曲面拟合处理，以得到第二曲面拟合模型的模型参数，包括：
基于暗影的像素数据，对暗影执行至少一次拟合过程，直至达到截止条件，将最后一次拟合过程得到的待选模型参数确定为第二曲面拟合模型的模型参数。其中，该拟合过程可以包括以下几个步骤：
步骤3071、获取第二权重矩阵。
该步骤3071可以参考上述步骤3041，本申请实施例在此不再赘述。
步骤3072、基于暗影的像素数据和暗影所在区域内的各个像素点对应的权重，采用第二曲面拟合模型对暗影进行曲面拟合处理，以得到第二曲面模型的待选模型参数。
该步骤3072可以参考上述步骤3042，本申请实施例在此不再赘述。
步骤3073、基于第二曲面拟合模型及获取的待选模型参数，对暗影的像素数据进行更新，得到更新后的待选像素数据。
该步骤3073可以参考上述步骤3043，本申请实施例在此不再赘述。
步骤3074、基于更新后的待选像素数据与暗影的像素数据，确定与暗影所 在区域内的各个像素点对应的像素值差值。
该步骤3074可以参考上述步骤3044，本申请实施例在此不再赘述。
步骤3075、基于与暗影所在区域内的各个像素点对应的像素值差值，更新与暗影内的各个像素点对应的权重，该权重与像素值差值负相关。
该步骤3075可以参考上述步骤3045，本申请实施例在此不再赘述。
在本申请实施例中，在执行步骤3075后，即执行完一次拟合过程。此时，需要重复执行步骤3071，以重新执行一次拟合过程。在执行至少一次拟合过程后，若达到截止条件，则放疗设备可以将最后一次拟合过程得到的待选模型参数确定为第二曲面拟合模型的模型参数。此时，确定出的第二曲面拟合模型的模型参数的准确性较高，使得确定暗影的中心点的坐标的准确性较高。
可选的，该截止条件可以包括：放疗设备执行了指定次数的拟合过程；或者，放疗设备当前执行的拟合过程后得到的待选模型参数，与上一次执行的拟合过程后得到的待选模型参数的变化量小于变化阈值。
结合上述实施例可知，本申请提供了两种确定光斑和暗影内的中心点的坐标的方式。即一种是对各个像素点未赋予权重时确定出的光斑和暗影内的中心点的坐标；另一种是对各个像素点赋予权重时确定出的光斑和暗影内的中心点的坐标。而对各个像素点赋予权重时确定出的光斑和暗影内的中心点的坐标，相较于对各个像素点未赋予权重时确定出的光斑和暗影内的中心点的坐标更为准确。
示例的，如图7所示，图7是本申请实施例提供的一种初始像素数据的三维模拟图。其中，x轴上的数值初始像素数据中的各个像素点的横坐标，y轴上的数值初始像素数据中的各个像素点的纵坐标，z轴上的数据表示初始像素数据中的各个像素点的像素值。
在对光斑进行曲面拟合时，若未对各个像素点赋予权重，则对光斑进行曲面拟合，且得到拟合结果后，对初始像素数据进行更新后得到更新后的像素数据的三维模拟图可以参考图8。基于更新后的像素数据和初始像素数据确定出的暗影的像素数据的三维模拟图可以参考图9。其中，该图8即为上述步骤3023获取到的更新后的像素数据的三维模拟图，该图9即为上述步骤3024获取到的暗影的像素数据的三维模拟图。
在对光斑进行曲面拟合时，若对各个像素点赋予权重，则对光斑进行曲面 拟合，且得到拟合结果后，对初始像素数据进行更新后得到更新后的像素数据的三维模拟图可以参考图10。基于更新后的像素数据和初始像素数据确定出的暗影的像素数据的三维模拟图可以参考图11。其中，该图10即为上述步骤3023获取到的更新后的像素数据的三维模拟图，该图11即为上述步骤3024获取到的暗影的像素数据的三维模拟图。
根据上述图8和图10可知，对各个像素点赋予权重时得到的更新后的像素数据中的中央区域的像素值，大于未对各个像素点赋予权重时得到的更新后的像素数据中的中央区域的像素值。因此，对各个像素赋予权重时对光斑进行曲面拟合后得到的拟合结果较为准确，使得对各个像素点赋予权重时确定出的光斑和暗影内的中心点的坐标的准确性较高。
需要说明的是，本申请实施例提供的图像数据的处理方法的步骤的先后顺序可以进行适当调整，步骤也可以根据情况进行相应增减，任何熟悉本技术领域的技术人员在本申请揭露的技术范围内，可轻易想到变化的方法，都应涵盖在本申请的保护范围之内，因此不再赘述。
综上所述，本申请实施例提供的图像数据的处理方法，通过处理设备从放疗设备中的探测器获取投影数据，并基于该投影数据生成的图像数据后，对该图像数据进行处理，以得到光斑的中心点的坐标和暗影的中心点的坐标，如此，后续通过确定光斑的中心点与暗影的中心点之间的偏移量，即可实现对放疗设备的等中心的验证。无需通过人工分析胶片的方式对放疗设备的等中心进行验证，有效的提高了对放疗设备的等中心的验证效率。
请参考图12，图12是本申请实施例提供的一种放疗设备的等中心验证方法的流程图，该放疗设备的等中心验证方法可以应用于图1示出的放疗设备的等中心验证系统100中的处理设备103。该放疗设备的等中心验证方法可以包括：
步骤401、从探测器获取放疗设备的治疗头位于不同位置时产生的至少两个投影数据，并基于该至少两个投影数据生成至少两个图像数据。每个图像数据中含有放疗设备的治疗头产生的射线束经射线阻挡体阻挡后形成的光斑和位于该光斑中的暗影。
步骤402、采用图像处理方法对每个图像数据进行处理，以得到每个图像数据中的光斑的中心点的坐标和暗影的中心点的坐标。
在本申请实施例中，可以采用图3或图4示出的图像处理方法对每个图像数据进行处理。
步骤403、基于每个图像数据中的光斑的中心点的坐标和暗影的中心点的坐标，确定放疗设备的等中心与治疗等中心之间的偏移量。
综上所述，本申请实施例提供的放疗设备的等中心验证方法，通过放疗设备中的处理设备生成放疗设备中的治疗头位于不同位置所产生的至少两个图像数据，并且可以确定出每个图像数据中的光斑的中心点的坐标和暗影的中心点的坐标，如此，在确定出每个图像数据中的光斑的中心点与暗影的中心点之间的偏移量后，即可得到放疗设备的等中心与治疗等中心之间的偏移量，从而实现对放疗设备的等中心的验证。无需通过人工分析胶片的方式对放疗设备的等中心进行验证，有效的提高了对放疗设备的等中心的验证效率。
请参考图13，图13是本申请实施例提供的另一种放疗设备的等中心验证方法的流程图，该放疗设备的等中心验证方法可以应用于图1示出的放疗设备的等中心验证系统100中的处理设备103。该放疗设备的等中心验证方法可以包括：
步骤501、基于放疗设备的治疗头位于第一位置时，从探测器获取与第一位置对应的投影数据并生成第一图像数据。
在本申请实施例中，在放疗设备的治疗头位于第一位置时，处理设备可以从探测器获取治疗头位于该第一位置时产生的投影数据，并基于该投影数据生成第一图像数据。
步骤502、基于放疗设备的治疗头位于第二位置时，从探测器获取与第二位置对应的投影数据并生成第二图像数据。
在本申请实施例中，在放疗设备的治疗头位于第二位置时，处理设备可以从探测器获取治疗头位于第二位置时产生的投影数据，并基于该投影数据生成第二图像数据。
需要说明的是，由于放疗设备中的治疗头不管位于何种位置，该治疗头出射的射线束均会经过放疗设备中的射线阻挡体后射向探测器，因此，处理设备生成的第一图像数据和第二图像数据中的每个图像数据均具有：光斑以及位于该光斑内的暗影。示例的，该每个图像数据均可以参考图2示出的图像。
可选的，放疗设备的治疗头位于第一位置时出射的射线束的方向，与放疗 设备的治疗头位于第二位置时出射的射线束的方向垂直。也即是，治疗头位于第一位置时出射的射线束方向与治疗头位于第二位置时出射的射线束的方向垂直。如此，便于后续放疗设备确定该放疗设备的等中心与治疗等中心在不同方向上的偏移量，从而可以进一步的提高对放疗设备的等中心进行验证的效率。
需要说明的是，本申请实施例既可以对治疗头中的多个放射源出射的射线束进行分析，也可以对多个放射源中的某一个放射出射的射线束进行分析。当需要对个治疗头中的多个放射源出射的射线束进行分析时，需要让治疗头中的多个放射源同时出射射线束，如此处理设备生成的图像数据包含多个光斑；当需要对治疗头中的某一个放射源出射的射线束进行分析时，需要让治疗头中待分析的放射源出射射线束，而屏蔽除待分析的放射源之外的放射源出射的射线束，如此处理设备生成的图像数据包含一个光斑。
步骤503、对于第一图像数据和第二图像数据中的每个图像数据，采用图像处理方法对每个图像数据进行处理，以得到每个图像数据中的光斑的中心点的坐标和暗影的中心点的坐标。
在本申请实施例中，对于第一图像数据和第二图像数据中的每个图像数据，可以采用图3或图4示出的图像数据的处理方法对每个图像数据进行处理，以得到每个图像数据中的光斑的中心点的坐标和暗影的中心点的坐标。
步骤504、基于第一图像数据中的光斑的中心点的坐标和暗影的中心点的坐标，确定第一图像数据中的光斑的中心点和暗影的中心点之间的第一偏移量。
在本申请实施例中，处理设备可以基于第一图像数据中的光斑的中心点的坐标和暗影的中心点的坐标，确定第一图像数据中的光斑的中心点和暗影的中心点之间的第一偏移量。
步骤505、基于第二图像数据中的光斑的中心点的坐标和暗影的中心点的坐标，确定第二图像数据中的光斑的中心点和暗影的中心点第二偏移量。
在本申请实施例中，处理设备可以基于第二图像数据中的光斑的中心点的坐标和暗影的中心点的坐标，确定第二图像数据中的光斑和中心点和暗影的中心点之间的第二偏移量。
步骤506、基于第一偏移量和第二偏移量，确定放疗设备的等中心与治疗等中心之间的偏移量。
在本申请实施例中，处理设备可以基于第一偏移量和第二偏移量，确定光 斑的中心点与暗影的中心点在三维空间内的偏移量，使得处理设备可以确定处放疗设备的等中心与治疗等中心之间的偏移量，从而可以实现对放疗设备的等中心进行验证。
可选的，处理设备在确定出放疗设备的等中心与治疗等中心之间的偏移量大于预设偏移量阈值时，处理设备可以控制放疗设备中的治疗床进行补偿移动，从而实现对放疗设备的等中心进行校正。
需要说明的是，本申请实施例提供的放疗设备的等中心的验证方法的步骤的先后顺序可以进行适当调整，步骤也可以根据情况进行相应增减，任何熟悉本技术领域的技术人员在本申请揭露的技术范围内，可轻易想到变化的方法，都应涵盖在本申请的保护范围之内，因此不再赘述。
综上所述，本申请实施例提供的放疗设备的等中心验证方法，通过放疗设备中的处理设备生成放疗设备中的治疗头位于不同位置所产生的至少两个图像数据，并且可以确定出每个图像数据中的光斑的中心点的坐标和暗影的中心点的坐标，如此，在确定出每个图像数据中的光斑的中心点与暗影的中心点之间的偏移量后，即可得到放疗设备的等中心与治疗等中心之间的偏移量，从而实现对放疗设备的等中心的验证。无需通过人工分析胶片的方式对放疗设备的等中心进行验证，有效的提高了对放疗设备的等中心的验证效率。
本申请实施例提供了一种放疗设备的等中心验证系统，如图1所示，该放疗设备的等中心验证系统100可以包括：放疗设备101、射线阻挡体102和处理设备103。其中：
该放疗设备101可以包括：相对设置的治疗头1011和探测器1012。该探测器1012用于接收治疗头1011产生的射线束并转换为投影数据。该射线阻挡体102可拆卸安装在放疗设备101的等中心处，该射线阻挡体102的中心与放疗设备101的等中心相重合。
该处理设备103与探测器101电连接，该处理设备用于图12或图13示出的放疗设备的等中心验证方法。
可选的，该放疗设备101还可以包括：旋转机架1013。治疗头1011和探测器1012均设置在该旋转机架1013上，该旋转机架1013能够同时带动治疗头1011和探测器1012转动。如此，通过旋转机架1013可以控制治疗头1011位于不同 的位置。
可选的，该射线阻挡体可以为射线阻挡球。示例的，该射线阻挡球可以为金属球。例如，该金属球可以为钨球。
在本申请实施例中，为了方便将射线阻挡体102安装在放疗设备101上，该放疗设备的等中心验证系统100还可以包括：检测模体104。射线阻挡体102可以安装在该检测模体104的中心位置处，射线阻挡体102通过检测模体104可拆卸安装在放疗设备101的等中心处。
示例的，放疗设备101还可以包括：治疗床1014了，检测模体104可拆卸安装在该治疗床1014的预设位置处，且位于放疗设备100的等中心处。检测模体104可以为任意形状的盒状箱体，例如，如图1所示，可以是正方体的箱体。工作人员将检测模体104固定在治疗床1014的预设位置之后，工作人员可以调整治疗床1014的高度，使放疗设备101的等中心与射线阻挡体102的球心处于同一高度；之后，工作人员将治疗床1014移向治疗头1011的下方，使射线阻挡体102的中心与放疗设备101的等中心相重合；最后，工作人员开启治疗头1011，治疗头1011向外出射射线束。
需要说明的是，放疗设备的等中心验证系统的工作原理，可以参考前述放疗设备的等中心验证方法的实施例中的对应内容，本申请实施例在此不再赘述。
本申请还提供了一种放疗设备的等中心的验证装置，放疗设备的等中心的验证装置可以为上述实施例中的处理设备。该验证装置可以包括：处理器和存储器，存储器中存储有至少一条指令，指令由所述处理器加载并执行以实现图12或图13示出的放疗设备的等中心的验证方法。
本申请实施例还提供了一种计算机可读存储介质，该存储介质中存储有至少一条指令，该指令由处理器加载并执行以实现如图3或图4示出的图像数据处理方法，或如图12或图13示出的放疗设备的等中心的验证方法。
在本申请中，术语“第一”和“第二”仅用于描述目的，而不能理解为指示或暗示相对重要性。术语“多个”指两个或两个以上，除非另有明确的限定。
本领域普通技术人员可以理解实现上述实施例的全部或部分步骤可以通过 硬件来完成，也可以通过程序来指令相关的硬件完成，所述的程序可以存储于一种计算机可读存储介质中，上述提到的存储介质可以是只读存储器，磁盘或光盘等。
以上所述仅为本申请的可选的实施例，并不用以限制本申请，凡在本申请的精神和原则之内，所作的任何修改、等同替换、改进等，均应包含在本申请的保护范围之内。
Claims (15)
- 一种图像数据的处理方法，其特征在于，所述图像数据是处理设备从探测器获取到投影数据后，基于所述投影数据生成的数据，所述图像数据中含有所述放疗设备的治疗头产生的射线束经射线阻挡体阻挡后形成的光斑和位于所述光斑中的暗影；所述方法包括：确定初始像素数据，所述初始像素数据包括：所述光斑所在区域内的各个像素点的像素值；基于所述初始像素数据，采用第一曲面拟合模型对所述光斑进行曲面拟合处理，以得到所述第一曲面拟合模型的模型参数，所述第一曲面拟合模型的模型参数包括：所述光斑的中心点的坐标；基于所述第一曲面拟合模型及获取的模型参数，对所述光斑所在区域内的各个像素点的像素值进行更新，得到更新后的像素数据；基于所述更新后的像素数据和所述初始像素数据，确定所述暗影的像素数据，所述暗影的像素数据包括：所述暗影所在区域内的各个像素点的像素值；基于所述暗影的像素数据，采用第二曲面拟合模型对所述暗影进行曲面拟合处理，以得到所述第二曲面拟合模型的模型参数，所述第二曲面拟合模型的模型参数包括：所述暗影的中心点的坐标。
- 根据权利要求1所述的方法，其特征在于，基于所述初始像素数据，采用第一曲面拟合模型对所述光斑进行曲面拟合处理，以得到所述第一曲面拟合模型的模型参数，包括：基于所述初始像素数据，对所述光斑执行至少一次拟合过程，直至达到截止条件，将最后一次拟合过程得到的待选模型参数确定为所述第一曲面拟合模型的模型参数；其中，所述拟合过程包括：基于所述初始像素数据和所述光斑所在区域内的各个像素点对应的权重，采用所述第一曲面拟合模型对所述光斑进行曲面拟合处理，以得到所述第一曲面模型的待选模型参数；基于所述第一曲面拟合模型及获取的待选模型参数，对所述初始像素数据 进行更新，得到更新后的待选像素数据；基于所述更新后的待选像素数据与所述初始像素数据，确定与所述光斑所在区域内的各个像素点对应的像素值差值；基于与所述光斑所在区域内的各个像素点对应的像素值差值，更新与所述光斑所在区域内的各个像素点对应的权重，所述权重与所述像素值差值负相关。
- 根据权利要求1所述的方法，其特征在于，基于所述暗影的像素数据，采用第二曲面拟合模型对所述暗影进行曲面拟合处理，以得到所述第二曲面拟合模型的模型参数，包括：基于所述暗影的像素数据，对所述暗影执行至少一次拟合过程，直至达到截止条件，将最后一次拟合过程得到的待选模型参数确定为所述第二曲面拟合模型的模型参数；其中，所述拟合过程包括：基于所述暗影的像素数据和所述暗影所在区域内的各个像素点对应的权重，采用所述第二曲面拟合模型对所述暗影进行曲面拟合处理，以得到所述第二曲面模型的待选模型参数；基于所述第二曲面拟合模型及获取的待选模型参数，对所述暗影的像素数据进行更新，得到更新后的待选像素数据；基于所述更新后的待选像素数据与所述暗影的像素数据，确定与所述暗影所在区域内的各个像素点对应的像素值差值；基于与所述暗影所在区域内的各个像素点对应的像素值差值，更新与所述暗影所在区域内的各个像素点对应的权重，所述权重与所述像素值差值负相关。
- 根据权利要求2或3所述的方法，其特征在于，所述截止条件包括：执行了指定次数的拟合过程；或者，当前执行的拟合过程后得到的待选模型参数，与上一次执行的拟合过程后得到的待选模型参数的变化量小于变化阈值。
- 根据权利要求1至3任一所述的方法，其特征在于，所述第一曲面拟合模型与所述第二曲面拟合模型均为：二维高斯曲面拟合模型。
- 根据权利要求1至3任一所述的方法，其特征在于，所述确定初始像素数据，包括：对所述图像数据中的光斑进行轮廓提取处理，得到所述光斑的轮廓；基于所述光斑的轮廓，确定所述光斑的轮廓的外接矩形；将所述外接矩形内的各个像素点的原始的像素值，确定为所述初始像素数据。
- 一种放疗设备的等中心验证方法，其特征在于，所述方法包括：从探测器获取放疗设备的治疗头位于不同位置时产生的至少两个投影数据，并基于所述至少两个投影数据生成至少两个图像数据，每个所述图像数据中含有放疗设备的治疗头产生的射线束经射线阻挡体阻挡后形成的光斑和位于所述光斑中的暗影；采用权利要求1至6任一所述的图像数据处理方法对每个所述图像数据进行处理，以得到每个所述图像数据中的光斑的中心点的坐标和暗影的中心点的坐标；基于每个所述图像数据中的光斑的中心点的坐标和暗影的中心点的坐标，确定放疗设备的等中心与治疗等中心之间的偏移量。
- 根据权利要求7所述的方法，其特征在于，从探测器获取放疗设备的治疗头位于不同位置时产生的至少两个投影数据，并基于所述至少两个投影数据生成至少两个图像数据，包括：基于所述放疗设备的治疗头位于第一位置时，从所述探测器获取与所述第一位置对应的投影数据并生成第一图像数据；基于所述放疗设备的治疗头位于第二位置时，从所述探测器获取与所述第二位置对应的投影数据并生成第二图像数据；基于每个所述图像数据中的光斑的中心点的坐标和暗影的中心点的坐标，确定放疗设备的等中心与治疗等中心之间的偏移量，包括：基于所述第一图像数据中的光斑的中心点的坐标和暗影的中心点的坐标，确定所述第一图像数据中的光斑的中心点和暗影的中心点之间的第一偏移量；基于所述第二图像数据中的光斑的中心点的坐标和暗影的中心点的坐标， 确定所述第二图像数据中的光斑的中心点和暗影的中心点之间的第二偏移量；基于所述第一偏移量和所述第二偏移量，确定放疗设备的等中心与治疗等中心之间的偏移量。
- 根据权利要求8所述的方法，其特征在于，所述放疗设备的治疗头位于第一位置时出射的射线束的方向，与所述放疗设备的治疗头位于第二位置时出射的射线束的方向垂直。
- 一种放疗设备的等中心验证系统，其特征在于，所述系统包括放疗设备、射线阻挡体和处理设备，其中，所述放疗设备包括：相对设置的治疗头和探测器，所述探测器用于接收所述治疗头产生的射线束并转换为投影数据；所述射线阻挡体可拆卸安装在所述放疗设备的等中心处，所述射线阻挡体的中心与所述放疗设备的等中心相重合；所述处理设备与所述探测器电连接，所述处理设备用于执行如权利要求7至9任一所述的放疗设备的等中心验证方法。
- 根据权利要求10所述的系统，其特征在于，所述射线阻挡体为射线阻挡球。
- 根据权利要求11所述的系统，其特征在于，所述射线阻挡球为金属球。
- 根据权利要求10所述的系统，其特征在于，所述系统还包括检测模体，所述射线阻挡体安装在所述检测模体的中心位置处，所述射线阻挡体通过所述检测模体可拆卸安装在所述放疗设备的等中心处。
- 根据权利要求13所述的系统，其特征在于，所述放疗设备还包括治疗床，所述检测模体可拆卸安装在所述治疗床的预设位置处，且位于所述放疗设备的等中心处。
- 一种计算机可读存储介质，其特征在于，所述存储介质中存储有至少一条指令，所述指令由处理器加载并执行以实现如权利要求1-6任一所述的图像数据处理方法，或如权利要求7至9任一所述的放疗设备的等中心验证方法。
Priority Applications (2)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202080100524.1A CN115484869A (zh) | 2020-08-07 | 2020-08-07 | 图像数据的处理方法、放疗设备的等中心验证方法及系统 |
| PCT/CN2020/107663 WO2022027545A1 (zh) | 2020-08-07 | 2020-08-07 | 图像数据的处理方法、放疗设备的等中心验证方法及系统 |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| PCT/CN2020/107663 WO2022027545A1 (zh) | 2020-08-07 | 2020-08-07 | 图像数据的处理方法、放疗设备的等中心验证方法及系统 |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| WO2022027545A1 true WO2022027545A1 (zh) | 2022-02-10 |
Family
ID=80119006
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| PCT/CN2020/107663 WO2022027545A1 (zh) | 2020-08-07 | 2020-08-07 | 图像数据的处理方法、放疗设备的等中心验证方法及系统 |
Country Status (2)
| Country | Link |
|---|---|
| CN (1) | CN115484869A (zh) |
| WO (1) | WO2022027545A1 (zh) |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115591135A (zh) * | 2022-09-29 | 2023-01-13 | 中山大学肿瘤防治中心（中山大学附属肿瘤医院、中山大学肿瘤研究所）（Cn） | 一种治疗设备的多功能质控方法及模体 |
| CN115671579A (zh) * | 2022-10-31 | 2023-02-03 | 大连大学附属中山医院 | 一种图像引导放射治疗模拟定位系统与方法 |
Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105825067A (zh) * | 2016-03-29 | 2016-08-03 | 上海联影医疗科技有限公司 | 直线加速器的虚源模型的优化方法 |
| CN107693959A (zh) * | 2017-10-09 | 2018-02-16 | 沈阳东软医疗系统有限公司 | 一种光射野一致性检测模体、方法、装置及设备 |
| CN107913079A (zh) * | 2017-11-22 | 2018-04-17 | 上海联影医疗科技有限公司 | 医疗设备的射野验证装置及验证方法 |
| CN108122203A (zh) * | 2016-11-29 | 2018-06-05 | 上海东软医疗科技有限公司 | 一种几何参数的校正方法、装置、设备及系统 |
| US20180272155A1 (en) * | 2016-02-05 | 2018-09-27 | Varian Medical Systems International Ag* | Systems, methods, and devices for radiation beam alignment and radiation beam measurements using electronic portal imaging devices |
| CN111077562A (zh) * | 2019-12-20 | 2020-04-28 | 上海联影医疗科技有限公司 | 一种束流偏移量确定方法、装置、设备及存储介质 |
Family Cites Families (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2785340B2 (ja) * | 1989-06-23 | 1998-08-13 | 日本電気株式会社 | 放射線治療機の照射野決定装置 |
| GB2516282B (en) * | 2013-07-17 | 2017-07-26 | Vision Rt Ltd | Method of calibration of a stereoscopic camera system for use with a radio therapy treatment apparatus |
| CN203483752U (zh) * | 2013-09-02 | 2014-03-19 | 张伟 | 放射治疗等中心及射野验证模体 |
| WO2020010842A1 (zh) * | 2018-07-12 | 2020-01-16 | 西安大医集团有限公司 | 放疗设备等中心与治疗等中心一致性检测方法和系统 |
| CN110930351A (zh) * | 2018-09-20 | 2020-03-27 | 武汉光谷航天三江激光产业技术研究院有限公司 | 一种光斑检测方法、装置及电子设备 |
-
2020
- 2020-08-07 CN CN202080100524.1A patent/CN115484869A/zh active Pending
- 2020-08-07 WO PCT/CN2020/107663 patent/WO2022027545A1/zh active Application Filing
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20180272155A1 (en) * | 2016-02-05 | 2018-09-27 | Varian Medical Systems International Ag* | Systems, methods, and devices for radiation beam alignment and radiation beam measurements using electronic portal imaging devices |
| CN105825067A (zh) * | 2016-03-29 | 2016-08-03 | 上海联影医疗科技有限公司 | 直线加速器的虚源模型的优化方法 |
| CN108122203A (zh) * | 2016-11-29 | 2018-06-05 | 上海东软医疗科技有限公司 | 一种几何参数的校正方法、装置、设备及系统 |
| CN107693959A (zh) * | 2017-10-09 | 2018-02-16 | 沈阳东软医疗系统有限公司 | 一种光射野一致性检测模体、方法、装置及设备 |
| CN107913079A (zh) * | 2017-11-22 | 2018-04-17 | 上海联影医疗科技有限公司 | 医疗设备的射野验证装置及验证方法 |
| CN111077562A (zh) * | 2019-12-20 | 2020-04-28 | 上海联影医疗科技有限公司 | 一种束流偏移量确定方法、装置、设备及存储介质 |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115591135A (zh) * | 2022-09-29 | 2023-01-13 | 中山大学肿瘤防治中心（中山大学附属肿瘤医院、中山大学肿瘤研究所）（Cn） | 一种治疗设备的多功能质控方法及模体 |
| CN115591135B (zh) * | 2022-09-29 | 2023-05-05 | 中山大学肿瘤防治中心（中山大学附属肿瘤医院、中山大学肿瘤研究所） | 一种治疗设备的多功能质控方法及模体 |
| CN115671579A (zh) * | 2022-10-31 | 2023-02-03 | 大连大学附属中山医院 | 一种图像引导放射治疗模拟定位系统与方法 |
Also Published As
| Publication number | Publication date |
|---|---|
| CN115484869A (zh) | 2022-12-16 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| US9830718B2 (en) | Image processor, image processing method, and treatment system | |
| US9616247B2 (en) | Treatment plan evaluation in radiotherapy by stochastic analysis of delineation uncertainty | |
| US7697662B2 (en) | Online verification of radiation field, collimator position and/or leakage | |
| CN110314290A (zh) | 带电粒子束治疗装置 | |
| CN110075428B (zh) | 一种射束检验、测量方法及装置 | |
| CN108883302B (zh) | 自适应辐射治疗规划 | |
| WO2022027545A1 (zh) | 图像数据的处理方法、放疗设备的等中心验证方法及系统 | |
| US11865361B2 (en) | System and method for scanning pattern optimization for flash therapy treatment planning | |
| JP2019136509A (ja) | オーバーラップする輪郭への放射線量の最適化 | |
| EP3302699A1 (en) | Method of selecting beam geometries | |
| EP4313289A1 (en) | Beam spot tuning in a radiation therapy system | |
| US10813205B2 (en) | Detecting motion by using a low dose x-ray image | |
| JP2017169627A (ja) | Ｘ線撮影機器のアライメント調整支援装置、方法及びプログラム | |
| US20230149742A1 (en) | Systems and methods for modeling radiation source | |
| CN113646038A (zh) | 在放射治疗计划制定中使用等剂量表面以优化剂量分布 | |
| CN116920285A (zh) | 辐射治疗计划中的监测单元优化约束 | |
| US20110058750A1 (en) | Method for registering a first imaging data set with a second imaging data set | |
| US20240139548A1 (en) | System and method for assessing the performance of a radiotherapy apparatus | |
| CN108883298B (zh) | 治疗计划模块、疗法系统、疗法装置及存储介质 | |
| US11648421B2 (en) | Beam spot tuning in a radiation therapy system based on radiation field measurements | |
| JP6744123B2 (ja) | 動体追跡装置および放射線照射システム | |
| EP3338860A1 (en) | Registration of particle beam radiography data | |
| US20240054646A1 (en) | Methods, systems and computer readable mediums for light field verification on a patient surface | |
| Niedźwiecki et al. | Application of image analysis methods for isocenter quality assurance in radiotherapy | |
| CN114288568A (zh) | 放疗设备的等中心校正方法及系统、存储介质 |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| 121 | Ep: the epo has been informed by wipo that ep was designated in this application |
Ref document number: 20948782 Country of ref document: EP Kind code of ref document: A1 |
|
| NENP | Non-entry into the national phase |
Ref country code: DE |
|
| 122 | Ep: pct application non-entry in european phase |
Ref document number: 20948782 Country of ref document: EP Kind code of ref document: A1 |