4D-CT image reconstruction method

Abstract

The invention relates to the technical field of 4D-CT images, in particular to a 4D-CT image reconstruction method. The respiratory curve is obtained by utilizing the three-dimensional image body surface data of the 3D scanning equipment, so that additional equipment is not needed to collect respiratory movement information, the operation is simpler, a patient does not feel uncomfortable due to wearing of additional respiratory equipment, the experience of the patient is improved, the operation process of a doctor is simplified, and the working efficiency of the doctor is improved. The operation error is reduced to a certain extent; moreover, for thoracic and abdominal radiotherapy, in the process of collecting respiration data, collection can be carried out according to the position of the patient needing radiotherapy, and the selected ROI is directly selected in the radiotherapy area, so that the obtained respiration phase information can better fit the fluctuating motion of the area to be subjected to radiotherapy, the setting of the target area can be more accurate, and the radiotherapy accuracy is improved. The external boundary of a target region is reduced, the exposure dose of the target region is improved, and the toxic and side effects on normal tissues are reduced, so that the radiotherapy precision is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of 4D-CT images, and more specifically, to a 4D-CT image reconstruction method. Background Art

[0002] Artifacts caused by respiratory motion are a common problem in computed tomography (CT) imaging, especially during the scanning of upper abdominal organs. Due to the natural breathing of the human body, the abdominal organs will move periodically with breathing, which may result in the target organ not being on the predetermined section during the CT scan, so that the data collected by the detector is mixed with information from multiple sections, rather than a true projection of a single cross-section. This data confusion eventually manifests as respiratory motion artifacts on the CT image, which may interfere with the doctor's diagnosis, especially in the formulation of radiotherapy plans, where such artifacts may lead to incorrect positioning of the treatment target.

[0003] To solve this problem, four-dimensional computed tomography (4D-CT) technology came into being. 4D-CT technology not only captures information in the spatial dimension, but also adds the time dimension, which can record and analyze the movement changes of organs during the respiratory cycle, thereby more accurately reflecting the true position and shape of the organs. When collecting data, this technology simultaneously records the patient's respiratory signals. By analyzing these signals, the data under different respiratory phases can be classified and then reconstructed separately, and finally a set of continuous image sequences reflecting the changes of organs with respiratory movement are synthesized.

[0004] 4D-CT data acquisition faces two major challenges: one is how to minimize the impact of respiratory motion during scanning, and the other is how to accurately analyze and locate the respiratory phase. To address the first challenge, two strategies are usually adopted in clinical practice: respiratory restriction and free breathing. Respiratory restriction requires patients to keep their breathing as consistent as possible during scanning, but this is difficult to achieve for patients with poor respiratory control ability. In contrast, the free breathing strategy is more humane, allowing patients to breathe at their own pace, and then identifying and classifying data of different respiratory phases by analyzing the respiratory curve.

[0005] However, the key to the free breathing strategy is to accurately identify and locate specific respiratory phases, which is crucial to the accuracy of 4D-CT reconstruction. At present, the 4D-CT system mainly uses the following methods to collect the patient's respiratory signals: 1. Use a spirometer to measure the respiratory volume; 2. Fix infrared markers on the patient's body surface, and use an infrared camera to measure the fluctuation of the body surface markers with breathing to obtain respiratory signals; 3. Fix an abdominal pressure belt on the patient's abdomen to measure the pressure difference caused by respiratory movement, and use the pressure difference signal to characterize the respiratory movement. The above methods all require additional devices to be added to the patient's body, which not only causes discomfort to the patient, but also makes the operation more troublesome, adds more operating steps, and is prone to more operating errors, making the 4D-CT image reconstruction less accurate. Summary of the invention

[0006] In order to overcome the defects in the above-mentioned prior art, the present invention provides a 4D-CT image reconstruction method, which does not require additional devices to obtain respiratory signals, and can directly obtain respiratory signals simultaneously through a CT machine, which is simpler to operate and further improves the accuracy of the data.

[0007] In order to solve the above technical problems, the technical solution adopted by the present invention is:

[0008] A 4D-CT image reconstruction method comprises the following steps:

[0009] S1. Use a 3D scanning device to obtain the patient's three-dimensional image surface data, render the three-dimensional image surface data on the display interface, use the mouse to use the display buffer to obtain a three-dimensional point, and use the selected three-dimensional point as a reference point; set a cylinder to intercept the three-dimensional body surface point cloud within the cylinder, and the three-dimensional body surface point cloud area is the ROI of interest;

[0010] S2. Get the average value of the coordinates of the three-dimensional points in the ROI area at the current time t in the Z-axis direction as the current breathing amplitude value a t , obtain the breathing amplitude value at different times in real time, with time as the horizontal axis and the breathing amplitude value as the vertical axis to form a breathing curve;

[0011] S3. Smoothing the breathing curve using a smoothing algorithm;

[0012] S4. Identify the peaks and troughs of the respiratory curve to obtain the patient's respiratory phase information;

[0013] S5. Adding respiratory phase information to the patient's three-dimensional image surface data obtained in step S1;

[0014] S6. grouping all three-dimensional image surface data according to respiratory phase;

[0015] S7. Perform three-dimensional reconstruction on the three-dimensional image surface data at each phase using the selected reconstruction algorithm to generate a three-dimensional CT image at that phase; splice the three-dimensional CT images at different phases in chronological order to obtain a 4D-CT sequence image.

[0016] According to the above technical means, a 4D-CT image reconstruction method provided by the present invention obtains the respiratory curve by using the three-dimensional image surface data of the 3D scanning device. There is no need to use additional equipment to collect respiratory movement information, the operation is simpler, and the patient will not feel uncomfortable due to wearing additional respiratory equipment, which improves the patient experience and simplifies the doctor's operation process, reducing the operation error to a certain extent; moreover, for radiotherapy of the chest and abdomen, in the process of collecting respiratory data, it can be collected according to the position of the patient's required radiotherapy, and the selected ROI of interest is directly selected in the radiotherapy area, so that the acquired respiratory phase information can be more in line with the ups and downs of the area to be radiotherapy, and the setting of the target area can be more accurate, which helps to reduce the external boundary of the target area, increase the irradiation dose of the target area, and reduce the toxic and side effects on normal tissues, thereby improving the accuracy of radiotherapy.

[0017] Furthermore, the step S1 specifically includes:

[0018] S11. In the scanned three-dimensional image model display interface, adjust the optimal rendering angle and the scale size of the three-dimensional image model for the selected respiratory monitoring area;

[0019] S12. Obtain the XY axis coordinates a(xa,xb) of the mouse cursor and obtain the viewing angle projection matrix M of the three-dimensional image model;

[0020] S13. Traverse and project the three-dimensional point B in the three-dimensional point cloud data into a two-dimensional point b (xb, yb) on the two-dimensional image of the display interface size according to the perspective projection matrix M of the model, wherein the three-dimensional point B corresponds to the projected two-dimensional point one by one, and the corresponding formula is: b = M × B; calculate the distance d between the two-dimensional coordinate point a (xa, xb) of the cursor and each projected two-dimensional point b (xb, yb), and form a distance set;

[0021] S14. Find the two-dimensional point of the nearest projection, and the three-dimensional point corresponding to this two-dimensional point is the three-dimensional center O of the selected respiratory monitoring area;

[0022] S15. Taking the three-dimensional center O of the respiratory monitoring area as the center, setting the radius R and the height H to set a cylindrical three-dimensional space region, namely, the ROI;

[0023] S16. Traverse the three-dimensional points in the three-dimensional point cloud data to determine whether the three-dimensional point falls within the cylindrical three-dimensional space area. If so, determine that the three-dimensional point is within the respiratory monitoring area, and add the point to the respiratory monitoring area point set to obtain the ROI area three-dimensional point set; otherwise, do not add it.

[0024] Furthermore, step S2 includes: calculating the average value of the coordinates of all three-dimensional points in the ROI area at the current time t in the Z-axis direction as the breathing amplitude value at the current time t; acquiring the three-dimensional point set of the ROI area at different times in real time, and calculating the average value of the coordinates in the Z-axis direction at each time to obtain the breathing amplitude value at different times; taking time as the horizontal axis and the breathing amplitude value as the vertical axis, a breathing curve is formed.

[0025] Further, the step S3 includes, assuming that y0, y1, y2, y3, y4 are the latest five consecutive breathing amplitude values, and using the following calculation formula to obtain the five smoothed breathing amplitude values ​​y'0, y1', y'2, y3', y'4: y'0 = (3.0*y0+2.0*y1+y2-y4) / 5.0

[0026] y1'=(4.0*y0+3.0*y1+2*y2+y3) / 10.0

[0027] y'2=(y0+y1+y2+y3+y4) / 5.0

[0028] y3'=(4.0*y4+3.0*y3+2*y2+y1) / 10.0

[0029] y'4=(3.0*y4+2.0*y3+y2-y0) / 5.0.

[0030] Further, in step S4, starting from obtaining the breathing curve, the first peak is first identified, and only after the first peak is identified, the first trough is identified; as the breathing curve is continuously updated, only after the i-th peak is identified, the i-th trough is identified, and only after the i-th trough is identified, the i+1-th peak is identified, where i≥0.

[0031] Further, in step S4, it includes: S41. Acquire at least five latest breathing amplitude values ​​of the breathing curve in chronological order, which are recorded as: p1, p2, p3, p4, p5; and record the type T (peak, valley, nan) of the identified peak and valley points and the five breathing amplitude values ​​that are nearest neighbors in time, and identify the peak or valley according to formula (1), which is as follows:

[0032]

[0033] Wherein, R(t)=1 represents that p3 is a peak, R(t)=-1 represents that p3 is a trough, and R(t)=0 represents that p3 is neither a peak nor a trough.

[0034] Furthermore, in the peak recognition process, the peak recognized at the current moment is used as the temporary peak p m (t1), as the breathing curve is continuously updated, the peaks and troughs are continuously identified in the manner of step S41; if the new peak p n (t2) is recognized first, then compare p m (t1) and p n The amplitude of (t2) is determined by the following formula:

[0035]

[0036] If the trough is identified first, then p(t) = p m (t1).

[0037] Furthermore, in the process of identifying the trough, the trough identified at the current moment is used as the temporary trough v m (t1), as the breathing curve is continuously updated, the peaks and troughs are continuously identified in the manner of step S41. If the new trough v n (t2) is recognized first, then compare v m (t1) and v n The amplitude of (t2) is determined by the following formula:

[0038]

[0039] If the peak is identified first, then v(t) = v m (t1).

[0040] Furthermore, in step S6, the collected three-dimensional image body surface data are divided according to the respiratory phase information, and the three-dimensional image body surface data in the same phase are grouped together.

[0041] Furthermore, the reconstruction algorithm includes a filtered back-projection reconstruction algorithm and an iterative reconstruction algorithm.

[0042] Compared with the prior art, the beneficial effects are as follows: the 4D-CT image reconstruction method provided by the present invention does not need to use additional equipment to collect respiratory motion information, the operation is simpler, and the patient will not feel uncomfortable due to wearing additional respiratory equipment, which improves the patient experience and simplifies the doctor's operation process, reducing the operation error to a certain extent; moreover, the acquired respiratory phase information can be made to fit the ups and downs of the area to be radiotherapy more accurately to ensure that the target area can be set more accurately, which helps to reduce the external boundary of the target area, increase the irradiation dose of the target area, and reduce the toxic and side effects on normal tissues, thereby improving the accuracy of radiotherapy. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] Figure 1 It is a schematic flow chart of the method of the present invention.

[0044] Figure 2 This is a schematic diagram of selecting respiratory monitoring points in Example 2.

[0045] Figure 3 Schematic diagram of the breathing curve smoothing effect in Example 3.

[0046] Figure 4 Schematic diagram of the breathing curve phase of Example 4. DETAILED DESCRIPTION

[0047] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all of the embodiments. The present invention is described in one of the embodiments in combination with the specific implementation methods. Among them, the drawings are only used for exemplary descriptions, and only schematic diagrams are shown, not physical drawings, and cannot be understood as limitations on the present invention; in order to better illustrate the embodiments of the present invention, some parts of the drawings may be omitted, enlarged or reduced, and do not represent the size of the actual product; for those skilled in the art, it is understandable that some well-known structures and their descriptions in the drawings may be omitted.

[0048] In the description of the present invention, it should be understood that if the terms "upper", "lower", "left", "right" and the like indicate an orientation or positional relationship based on the orientation or positional relationship shown in the drawings, it is only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation. Therefore, the terms describing the positional relationship in the drawings are only used for exemplary explanations and cannot be understood as limiting the present invention. For ordinary technicians in the field, the specific meanings of the above terms can be understood according to specific circumstances. In addition, if there are descriptions involving "first", "second", etc. in the embodiments of the present invention, the descriptions of "first", "second", etc. are only used for descriptive purposes, and cannot be understood as indicating or implying their relative importance or implicitly indicating the number of technical features indicated. Therefore, the features defined as "first" and "second" can explicitly or implicitly include at least one of the features. In addition, the meaning of "and / or" appearing in the full text is to include three parallel schemes. Taking "A and / or B" as an example, it includes scheme A, or scheme B, or schemes that satisfy both A and B.

[0049] Embodiment 1:

[0050] like Figure 1 As shown, a 4D-CT image reconstruction method comprises the following steps:

[0051] S1. Use a 3D scanning device to obtain the patient's three-dimensional image surface data, render the three-dimensional image surface data on the display interface, use the mouse to use the display buffer to obtain a three-dimensional point, and use the selected three-dimensional point as a reference point; set a cylinder to intercept the three-dimensional body surface point cloud within the cylinder, and the three-dimensional body surface point cloud area is the ROI of interest;

[0052] S2. Get the average value of the coordinates of the three-dimensional points in the ROI area at the current time t in the Z-axis direction as the current breathing amplitude value a t , obtain the breathing amplitude value at different times in real time, with time as the horizontal axis and the breathing amplitude value as the vertical axis to form a breathing curve;

[0053] S3. Smoothing the breathing curve using a smoothing algorithm;

[0054] S4. Identify the peaks and troughs of the respiratory curve to obtain the patient's respiratory phase information;

[0055] S5. Adding respiratory phase information to the patient's three-dimensional image surface data obtained in step S1;

[0056] S6. grouping all three-dimensional image surface data according to respiratory phase;

[0057] S7. Perform three-dimensional reconstruction on the three-dimensional image surface data at each phase using the selected reconstruction algorithm to generate a three-dimensional CT image at that phase; splice the three-dimensional CT images at different phases in chronological order to obtain a 4D-CT sequence image.

[0058] Among them, in step S6, the collected three-dimensional image surface data is divided according to the respiratory phase information, and the three-dimensional image surface data under the same phase is grouped together. According to the respiratory waveform data, the respiratory cycle is divided into multiple phases, such as the end-respiratory phase, the end-inspiratory phase, and several intermediate phases. Each phase represents a specific stage in the respiratory process.

[0059] In step S7, a suitable reconstruction algorithm may be selected according to specific scanning conditions and requirements, such as a filtered back-projection reconstruction algorithm and an iterative reconstruction algorithm; these reconstruction algorithms are all existing reconstruction algorithms, and are not described in detail in this embodiment because they are not the focus of the present invention.

[0060] The projection data at each phase is reconstructed in three dimensions using the selected reconstruction algorithm using the reconstruction algorithm to generate three-dimensional CT images at that phase. These images show the morphology of the thoracic and abdominal organs at different respiratory phases. The three-dimensional CT images at different phases are spliced ​​in chronological order to generate a complete 4D-CT sequence image, which shows the dynamic changes of the thoracic and abdominal organs throughout the respiratory cycle. Furthermore, the generated 4D-CT sequence images are quality controlled to check for artifacts, noise, and other problems, and necessary post-processing is performed to improve image quality.

[0061] In this embodiment, the respiratory curve is obtained by using the three-dimensional image surface data of the 3D scanning device. There is no need to use additional equipment to collect respiratory movement information, the operation is simpler, and the patient will not feel uncomfortable due to wearing additional respiratory equipment, which improves the patient experience and simplifies the doctor's operation process, reducing the operation error to a certain extent; moreover, for radiotherapy of the chest and abdomen, in the process of collecting respiratory data, it can be collected according to the position of the patient's required radiotherapy, and the selected ROI of interest can be directly selected in the radiotherapy area, so that the acquired respiratory phase information can be more in line with the ups and downs of the area to be radiotherapy, and the target area can be set more accurately, which helps to reduce the external boundary of the target area, increase the irradiation dose of the target area, and reduce the toxic and side effects on normal tissues, thereby improving the accuracy of radiotherapy.

[0062] During the operation, a 3D scanning device is used to obtain three-dimensional image surface data and a respiratory curve to obtain respiratory phase information. In the subsequent 4D-CT image reconstruction process, a 3D scanning device is also used to obtain three-dimensional image surface data and reconstruct the three-dimensional image. The data obtained by the same device is used to obtain respiratory phase information and reconstruct the three-dimensional image. This not only simplifies the operation process, but also avoids system errors between different devices and improves data accuracy.

[0063] Embodiment 2:

[0064] In this embodiment, other steps are the same as those in Embodiment 1. This embodiment provides a method for obtaining a breathing curve; specifically, the method includes the following steps:

[0065] S11. In the scanned three-dimensional image model display interface, adjust the optimal rendering angle of the selected respiratory monitoring area and the scaling size of the three-dimensional image model.

[0066] S12. Obtain the XY axis coordinates a(xa, xb) of the mouse cursor, and obtain the viewing projection matrix M of the three-dimensional image model.

[0067] S13. Traverse and project the three-dimensional point B in the three-dimensional point cloud data into a two-dimensional point b (xb, yb) on the two-dimensional image of the display interface size according to the perspective projection matrix M of the model, wherein the three-dimensional point B corresponds one-to-one with the projected two-dimensional point, and the corresponding formula is: b=M×B; calculate the distance d between the two-dimensional coordinate point a (xa, xb) of the cursor and each projected two-dimensional point b (xb, yb) to form a distance set.

[0068] Among them, the traversal is to project the 3D point B in the 3D point cloud data according to the model perspective projection matrix M, which refers to the product of the perspective matrix with the smallest current perspective and the projection matrix. The coordinates a(xa,xb) obtained in step S12 and the current perspective projection matrix M, so the purpose of step S13 is to project the 3D point onto the currently displayed 2D image screen, so that the distance relationship between the 3D point projection point and the coordinate a(xa,xb) selected by the mouse cursor can be established in the same coordinate system. The projection of the three-dimensional point cloud to the current display screen needs to take into account the perspective of the three-dimensional point cloud model and the model scaling size (reflected in the view projection matrix). The projection of the three-dimensional point cloud model to the current screen image is to traverse the three-dimensional point B in the three-dimensional point cloud, and according to the S12 perspective projection matrix M, project B to the two-dimensional point b (xb, yb) on the two-dimensional screen image of the display window, wherein the three-dimensional point B corresponds one-to-one with the two-dimensional point b: the corresponding relationship is b=M×B; finally, the distance between the two-dimensional points a and b is calculated, and the traversal is completed to obtain the distance set between the projection point and the point a, and the distance set is used for the S14 step to find the three-dimensional center point O of the selected breathing area.

[0069] S14. Find the two-dimensional point of the projection that is closest to the target, and the three-dimensional point corresponding to the two-dimensional point is the three-dimensional center O of the selected respiratory monitoring area.

[0070] S15. With the three-dimensional center O of the respiratory monitoring area as the center, a radius R and a height H are set to set a cylindrical three-dimensional space region, namely, the ROI of interest; Figure 2 As shown in the figure, it is the effect of selecting the respiratory monitoring point, and the red area is the selected small ROI.

[0071] S16. Traverse the three-dimensional points in the three-dimensional point cloud data to determine whether the three-dimensional point falls within the cylindrical three-dimensional space area. If so, determine that the three-dimensional point is within the respiratory monitoring area, and add the point to the respiratory monitoring area point set to obtain the ROI area three-dimensional point set; otherwise, do not add it.

[0072] To determine whether a three-dimensional point is within the respiratory monitoring area, the following formula can be used: assuming that the coordinates of the three-dimensional point are (xb, yb, zb), the three-dimensional center of the cylinder is O(xo, yo, zo), and the three-dimensional cylindrical area is expressed as: (x-xo)×(x-xo)+(y-yo)×(y-yo)<=R×R, and |z-zo|<=H.

[0073] S17. Calculate the average value of the coordinates of all three-dimensional points in the ROI area at the current time t in the Z-axis direction as the breathing amplitude value at the current time t; obtain the three-dimensional point set of the ROI area at different times in real time, and calculate the average value of the coordinates in the Z-axis direction at each time to obtain the breathing amplitude value at different times; use time as the horizontal axis and the breathing amplitude value as the vertical axis to form a breathing curve.

[0074] After obtaining the 3D point set in the ROI area (n 3D points), calculate the average value of the Z coordinates of all 3D points, average_z = (z1+z2+...+zn) / n, and the value of Average_z is the current breathing amplitude value.

[0075] Embodiment 3:

[0076] In this embodiment, other steps are the same as those in Embodiment 1. This embodiment provides a method for smoothing a breathing curve. Specifically, assuming that y0, y1, y2, y3, and y4 are the latest five consecutive breathing amplitude values, the following calculation formula is used to obtain the five smoothed breathing amplitude values ​​y'0, y1', y'2, y3', and y'4: y'0 = (3.0*y0+2.0*y1+y2-y4) / 5.0

[0077] y1'=(4.0*y0+3.0*y1+2*y2+y3) / 10.0

[0078] y'2=(y0+y1+y2+y3+y4) / 5.0

[0079] y3'=(4.0*y4+3.0*y3+2*y2+y1) / 10.0

[0080] y'4=(3.0*y4+2.0*y3+y2-y0) / 5.0.

[0081] like Figure 3 As shown, the red one is the actual breathing curve, and the black one is the smoothed breathing curve.

[0082] Embodiment 4:

[0083] In this embodiment, a method for identifying the peaks and troughs of a respiratory curve is provided. Starting from the acquisition of the respiratory curve, the first peak is first identified. Only after the first peak is identified, the first trough is identified. As the respiratory curve is continuously updated, only after the i-th peak is identified, the i-th trough is identified. Only after the i-th trough is identified, the i+1-th peak is identified, where i≥0. The peaks and troughs of the respiratory curve are continuously updated according to such rules. The respiratory curve of a real patient is not very smooth, and there is a curve jitter. The currently identified peak or trough is used as a temporary peak or trough. If a higher peak or a lower trough appears in the future in the same period, the currently identified temporary peak or trough is updated.

[0084] Specifically, the following steps are included:

[0085] S41. Obtain at least five latest respiratory amplitude values ​​of the respiratory curve in chronological order, recorded as: p1, p2, p3, p4, p5; and record the type T (peak, valley, nan) of the identified peak and valley points and the nearest neighbors of the five respiratory amplitude values ​​in time, and identify the peak or valley according to formula (1), which is as follows:

[0086]

[0087] Wherein, R(t)=1 represents that p3 is a peak, R(t)=-1 represents that p3 is a trough, and R(t)=0 represents that p3 is neither a peak nor a trough.

[0088] It should be noted that, during the identification process, the first peak needs to be identified first, and then the first trough is identified; the identification of the first peak and the first trough are both performed according to step S41, except that the identification of the first peak and the first trough does not require a neighbor type comparison.

[0089] S42. In the peak recognition process, the peak recognized at the current moment is used as the temporary peak pm (t1), as the breathing curve is continuously updated, the peaks and troughs are continuously identified in the manner of step S41; if the new peak p n (t2) is recognized first, then compare p m (t1) and p n The amplitude of (t2) is determined by the following formula:

[0090]

[0091] If the trough is identified first, then p(t) = p m (t1).

[0092] S43. In the process of identifying the trough, the trough identified at the current moment is used as the temporary trough v m (t1), as the breathing curve is continuously updated, the peaks and troughs are continuously identified in the manner of step S41. If the new trough v n (t2) is recognized first, then compare v m (t1) and v n The amplitude of (t2) is determined by the following formula:

[0093]

[0094] If the peak is identified first, then v(t) = v m (t1).

[0095] When a peak or trough point is identified in real time, the software immediately sends a signal through the communication interface to mark and classify the CT image sequence of this scanning phase for subsequent 4D-CT reconstruction.

[0096] This embodiment can identify the peaks and troughs of the breathing curve in real time from the complex pattern of free breathing, thereby extracting clear breathing phase markers. The peak and trough recognition method can identify the start and end of breathing, and can accurately determine key phases such as the end of exhalation (trough) and the end of inspiration (peak), so as to classify the data corresponding to these phases for subsequent accurate reconstruction.

[0097] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a suitable manner. In addition, those skilled in the art may combine and combine the different embodiments or examples described in this specification and the features of the different embodiments or examples, without contradiction.

[0098] Obviously, the above embodiments of the present invention are merely examples for clearly illustrating the present invention, and are not intended to limit the embodiments of the present invention. For those skilled in the art, other different forms of changes or modifications can be made based on the above description. It is not necessary and impossible to list all the embodiments here. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present invention should be included in the protection scope of the claims of the present invention.

Claims

1. A 4D-CT image reconstruction method, characterized in that: The following steps are involved: S1. Use a 3D scanning device to obtain the patient's three-dimensional image surface data, render the three-dimensional image surface data on the display interface, use the mouse to use the display buffer to obtain a three-dimensional point, and use the selected three-dimensional point as a reference point; set a cylinder to intercept the three-dimensional body surface point cloud within the cylinder, and the three-dimensional body surface point cloud area is the ROI of interest; S2. Get the average value of the coordinates of the three-dimensional points in the ROI area at the current time t in the Z-axis direction as the current breathing amplitude value a t , obtain the breathing amplitude value at different times in real time, with time as the horizontal axis and the breathing amplitude value as the vertical axis to form a breathing curve; S3. Smoothing the breathing curve using a smoothing algorithm; S4. Identify the peaks and troughs of the respiratory curve to obtain the patient's respiratory phase information; S5. Adding respiratory phase information to the patient's three-dimensional image surface data obtained in step S1; S6. grouping all three-dimensional image surface data according to respiratory phase; S7. Perform three-dimensional reconstruction on the three-dimensional image surface data at each phase using the selected reconstruction algorithm to generate a three-dimensional CT image at that phase; splice the three-dimensional CT images at different phases in chronological order to obtain a 4D-CT sequence image.

2. The 4D-CT image reconstruction method according to claim 1, characterized in that: The step S1 specifically includes: S11. In the scanned three-dimensional image model display interface, adjust the optimal rendering angle and the scale size of the three-dimensional image model for the selected respiratory monitoring area; S12. Obtain the XY axis coordinates a(xa,xb) of the mouse cursor and obtain the viewing angle projection matrix M of the three-dimensional image model; S13. Traverse and project the three-dimensional point B in the three-dimensional point cloud data into a two-dimensional point b (xb, yb) on the two-dimensional image of the display interface size according to the perspective projection matrix M of the model, wherein the three-dimensional point B corresponds to the projected two-dimensional point one by one, and the corresponding formula is: b = M × B; calculate the distance d between the two-dimensional coordinate point a (xa, xb) of the cursor and each projected two-dimensional point b (xb, yb), and form a distance set; S14. Find the two-dimensional point of the nearest projection, and the three-dimensional point corresponding to this two-dimensional point is the three-dimensional center O of the selected respiratory monitoring area; S15. Taking the three-dimensional center O of the respiratory monitoring area as the center, setting the radius R and the height H to set a cylindrical three-dimensional space region, namely, the ROI; S16. Traverse the three-dimensional points in the three-dimensional point cloud data to determine whether the three-dimensional point falls within the cylindrical three-dimensional space area. If so, determine that the three-dimensional point is within the respiratory monitoring area, and add the point to the respiratory monitoring area point set to obtain the ROI area three-dimensional point set; otherwise, do not add it.

3. The 4D-CT image reconstruction method according to claim 2, characterized in that: The step S2 includes: calculating the average value of the coordinates of all three-dimensional points in the ROI area at the current time t in the Z-axis direction as the breathing amplitude value at the current time t; acquiring the three-dimensional point set of the ROI area at different times in real time, and calculating the average value of the coordinates in the Z-axis direction at each time to obtain the breathing amplitude value at different times; forming a breathing curve with time as the horizontal axis and the breathing amplitude value as the vertical axis.

4. The 4D-CT image reconstruction method according to claim 3, characterized in that: The step S3 includes, assuming that y0, y1, y2, y3, y4 are the latest five consecutive breathing amplitude values, and using the following calculation formula to obtain the five smoothed breathing amplitude values ​​y'0, y1', y'2, y3', y'4: y'0=(3.0*y0+2.0*y1+y2-y4) / 5.0 y1'=(4.0*y0+3.0*y1+2*y2+y3) / 10.0 y'2=(y0+y1+y2+y3+y4) / 5.0 y3'=(4.0*y4+3.0*y3+2*y2+y1) / 10.0 y'4=(3.0*y4+2.0*y3+y2-y0) / 5.

0.

5. The 4D-CT image reconstruction method according to claim 1, characterized in that: In step S4, starting from obtaining the breathing curve, the first peak is first identified, and only after the first peak is identified, the first trough is identified; as the breathing curve is continuously updated, only after the i-th peak is identified, the i-th trough is identified, and only after the i-th trough is identified, the i+1-th peak is identified, where i≥0.

6. The 4D-CT image reconstruction method according to claim 5, characterized in that: In step S4, it includes: S41. Obtain at least five latest respiratory amplitude values ​​of the respiratory curve in chronological order, recorded as: p1, p2, p3, p4, p5; and record the type T (peak, valley, nan) of the identified peak and valley points and the nearest neighbors of the five respiratory amplitude values ​​in time, and identify the peak or valley according to formula (1), which is as follows: Wherein, R(t)=1 represents that p3 is a peak, R(t)=-1 represents that p3 is a trough, and R(t)=0 represents that p3 is neither a peak nor a trough.

7. The 4D-CT image reconstruction method according to claim 6, characterized in that: In the peak recognition process, the peak recognized at the current moment is taken as the temporary peak p m (t1), as the breathing curve is continuously updated, the peaks and troughs are continuously identified in the manner of step S41; if the new peak p n (t2) is recognized first, then compare p m (t1) and p n The amplitude of (t2) is determined by the following formula: If the trough is identified first, then p(t) = p m (t1).

8. The 4D-CT image reconstruction method according to claim 6, characterized in that: In the process of identifying the trough, the trough identified at the current moment is taken as the temporary trough v m (t1), as the breathing curve is continuously updated, the peaks and troughs are continuously identified in the manner of step S41. If the new trough v n (t2) is recognized first, then compare v m (t1) and v n The amplitude of (t2) is determined by the following formula: If the peak is identified first, then v(t) = v m (t1).

9. The 4D-CT image reconstruction method according to any one of claims 1 to 8, characterized in that: In step S6, the collected three-dimensional image body surface data are divided according to the respiratory phase information, and the three-dimensional image body surface data in the same phase are grouped together.

10. The 4D-CT image reconstruction method according to claim 9, characterized in that: The reconstruction algorithm includes a filtered back-projection reconstruction algorithm and an iterative reconstruction algorithm.

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