Magnetic resonance scanning method, device and system

[0061] Example one

[0062] figure 1 This is a flowchart of a magnetic resonance scanning method provided in the first embodiment of the present invention. This embodiment is applicable to the situation of automatically determining the scanning strategy of the shoulder joint. The method can be implemented by a magnetic resonance scanning apparatus provided in the embodiment of the present invention. For execution, the device can be implemented in software and/or hardware. See figure 1 , The method specifically includes:

[0063] S110: Obtain a pre-scanned image of the area to be scanned of the scanned object.

[0064] In this embodiment, the area to be scanned of the scanning object is pre-scanned to obtain a pre-scanned image of the area to be scanned. Among them, pre-scan refers to scanning the scanned object through a preset radio frequency sequence, which is a radio frequency sequence used to quickly locate and image the scanned object, and has the characteristics of low energy and high speed. Among them, the pre-scan image is a low-resolution 3D (Three Dimensions, three-dimensional) image. The scanned object is scanned and imaged by a preset radio frequency sequence, which only achieves the effect of identifying the area to be scanned of the scanned object, without the need for pathological inspection of the scanned object .

[0065] S120: Automatically or semi-automatically determine a scanning strategy of the area to be scanned according to the pre-scanned image and preset rules, the scanning strategy including a scanning center and a scanning direction.

[0066] The preset rules can refer to the conditions that the scan direction and scan center need to meet. Take the scan of the shoulder joint as an example: in the coronal scan, the scan direction or characteristic direction on the cross section needs to be parallel to the supraspinatus tendon, sagittal plane The scanning direction or characteristic direction needs to be parallel to the long axis of the humerus, the coronal scanning direction or characteristic direction is parallel to the supraspinatus tendon, and the scanning center or characteristic point is the inner side of the humerus; in the sagittal scanning, the transverse scanning direction or characteristic The direction needs to be parallel to the supraspinatus tendon, the coronal scan direction or characteristic direction is parallel to the supraspinatus tendon, and the sagittal scan direction or characteristic direction needs to be parallel to the long axis of the humerus; in the cross-sectional scan, the coronal scan direction or The characteristic direction is parallel to the supraspinatus tendon, the sagittal plane scanning direction or characteristic direction is parallel to the long axis of the humerus, and the scanning center or characteristic point is the inner side of the humerus.

[0067] Wherein, the scan center refers to a position determined in the area to be scanned and corresponding to the center of the field of view (FOV) of the magnetic resonance imaging system, or a position determined in the area to be scanned and located at the center of the FOV. In this embodiment, the scan center can correspond to one or more feature points in the humerus region, and the one or more feature points can be located on the longest bone layer in the sagittal plane, the first layer of the humerus in the transverse section, or the coronal plane The largest layer of the upper humerus. The scanning direction refers to the characteristic direction corresponding to the area to be scanned. Optionally, the characteristic direction is the direction applied by the magnetic resonance scanning sequence. Further, the characteristic scanning direction may be set to be along the tendon direction. In this embodiment, the tendon is one of the key areas in the detection of the shoulder joint. Performing magnetic resonance scanning along the direction of the tendon can improve the accuracy of detecting the damage of the tendon.

[0068] In one embodiment, the area to be scanned is the shoulder joint, and automatically or semi-automatically determining the scanning direction of the area to be scanned according to the pre-scan image and preset rules includes: performing image segmentation processing on the pre-scan image to obtain a humerus image of the shoulder joint ; Determine the tendon direction of the area to be scanned according to the humerus image, where the tendon direction of the area to be scanned includes the tendon direction of the cross section and the coronal plane; respectively determine the scan direction of the area to be scanned according to the tendon direction.

[0069] Among them, the image segmentation processing refers to the processing process for extracting the target image. In this embodiment, optionally, the area to be scanned is the shoulder joint, and the segmented image is the humerus image of the shoulder joint. Optionally, the image segmentation processing of the pre-scan image of the shoulder joint includes skin segmentation and humerus segmentation to obtain a humerus image.

[0070] The image segmentation method can adopt a voxel or region-based information-based segmentation method, or a model-based segmentation method based on a local prior model and a global model. Wherein, voxel or pixel-based image segmentation may include medical image segmentation using histograms or thresholds, image segmentation based on texture, or segmentation based on pixel statistics. Region-based image segmentation can include methods such as region growth and edge detection. Of course, a method based on artificial neural networks (ANNs, Artificial Neural Networks) can also be used for segmentation. Take the method based on artificial neural network as an example: calculate the local neighborhood around the medical image pixel to be processed; classify the pixel into the attribute area based on the texture feature vector. For the process, please refer to Bandpopadhyay S. Simulated annealing using a reversiblejump Markov chain Monte Carloalgorithm for fuzzy clustering[J].IEEETransactions on Knowledge and data Engineering,2005,17(4):479-490.

[0071] In this embodiment, the skin segmentation can be performed by a threshold segmentation method. Optionally, the threshold segmentation method can be the ostu threshold segmentation method. The ostu threshold segmentation method refers to traversing different thresholds to binarize the scanned image, dividing the scanned image into a foreground image and a background image, and determining the difference between the two Variance, the gray threshold corresponding to the maximum variance is determined as the optimal threshold. Determine the binarized image of the scanned image according to the optimal threshold, extract the largest connected domain in the binarized graph, and determine the largest connected domain as the skin segmentation result. Optionally, the optimal threshold may be determined by traversing all gray-scale pixel values, or a preset threshold may be used. Illustratively, the gray-scale pixel value range is 0-255. For the above process, please refer to Otsu N.A threshold selection method from grav-level histograms[J].IEEEtransactions on systems,man,and cybernetics,1979,9(1):62-66.

[0072] Optionally, the area to be scanned is determined to be the left shoulder joint or the right shoulder joint according to the skin segmentation result. Exemplarily, this can be achieved in the following way: a three-dimensional coordinate system is established according to the scanned image, the upright direction of the parallel human body in the scanned image is the Z axis, the horizontal direction of the human arm is the X axis, and the direction from the front of the human body to the back of the human body is Y axis. Determine the center position of the skin segmentation result in the X direction as the center point, project the skin segmentation results cumulatively on the X axis, count and compare the number of pixels projected to the left of the center point and to the right of the center point, if projected to the center point If the number of pixels on the left is greater than the number of pixels projected to the right of the center, the shoulder joint is determined to be a left shoulder joint; if the number of pixels projected to the left of the center point is less than the number of pixels projected to the right of the center, it is determined The shoulder joint is the right shoulder joint.

[0073] Optionally, perform humerus segmentation processing according to the skin segmentation result to determine the humerus image of the shoulder joint. Optionally, the humerus segmentation processing includes coarse segmentation and fine segmentation. Among them, rough segmentation is used to remove pixels whose gray value is less than the preset gray threshold in the skin segmentation result, and to binarize the skin segmentation result to determine the area of ​​each connected domain, which will be less than 30 of the largest connected domain area. % Connected domains are deleted.

[0074] Before performing fine segmentation on the humerus image, determine the initial layer group of the humerus image. Project the rough segmentation result to the Z axis to generate a projection value graph, and determine the shoulder position according to the graph. Illustratively, the shoulder position projection value is about 0.2 of the maximum projection value, and the shoulder position is lowered The 22 scan layer-25 scan layer area is determined as the initial layer group of the humerus image. Among them, according to the trend of the projection value graph, it is judged whether the pre-scan image contains the shoulder position. If the initial area of ​​the projection value graph increases from small, it is determined that there is a shoulder area; if the initial area of ​​the projection value graph is It is determined that there is no shoulder area from a large decrease or the change area is not obvious. Further, the scan layer with the projection value of 0.7 of the maximum projection value and the adjacent scan layer can be determined as the initial layer group, optional Yes, the initial layer group includes 4 scanning layers.

[0075] Optionally, it is detected whether the initial layer group meets a preset condition, and if not, the initial layer group is determined again. The preset condition is that the circularity of the initial layer group is less than 0.8, or the area is less than 400. If the circularity of the initial layer group is greater than 0.8 and the area is greater than 400, the initial layer group that meets the preset conditions is determined in the area near the initial layer group. The circularity refers to the ratio of the number of pixels contained in the intersection of the initial layer group and the circular template to the number of pixels in the initial layer group. The method for determining the circular template is: determine the center of the circular template with the coordinates of each pixel in the initial layer group, where the circular abscissa is The ordinate of the center of the circle is Radius is Among them, n is the number of pixels, x i Is the abscissa of the i-th pixel, y i Is the ordinate of the i-th pixel, i and n are natural numbers, and their values ​​can be 5, 10, 20, 100, 1000, etc.

[0076] Optionally, the initial layer group is subdivided according to the circular black edge feature of the humerus. According to the circle center C(X gc , Y gc ) And radius r. For the initial layer group and each scanning layer, take C as the center and 0.8r-1.2r as the circular closed area, and detect whether the gray value of the pixel in the circular closed area meets the preset gray level condition, If it is, it is determined that the annular closed area is the humerus tissue, and the humerus tissue of each scan layer is merged to form a humerus image. The preset gray scale condition may be that each pixel value is within the preset grayscale range, or the average value of each pixel value is within the preset grayscale range.

[0077] In this embodiment, due to the low resolution of the pre-scan image obtained by pre-scanning the scanned object, the direction of the tendon cannot be clearly identified in the pre-scan image. In the prior art, it is mainly determined by the experience of the technician, which has a large difference. Accuracy leads to the problem of low accuracy of detection results.

[0078] In this embodiment, the principle of determining the scanning direction of the area to be scanned according to the pre-scanned image and preset rules is: performing a first-order linear structure detection on the humerus area continuous with the tendon area, and determining the tendon direction according to the structural direction of the humerus area .

[0079] In this embodiment, the direction of the tendon is determined by the humerus area in the pre-scan image that is continuous with the tendon area, instead of the method of determining the tendon by the magnetic resonance scanning technician based on experience, which improves the accuracy of the tendon direction and reduces the difference in experience caused by the technician. Uncertainty in the direction of the acquired tendon.

[0080] In this embodiment, on the basis of determining the scanning direction, the pre-scanned image is rotated according to the scanning direction, and the pixel points with the smallest distance from the inside of the body of the scanned object on the cross-sectional, sagittal, and coronal planes are determined, and the pixels are The point is determined as the scan center of the corresponding surface.

[0081] S130: Perform magnetic resonance scanning on the area to be scanned according to the scanning strategy.

[0082] In this embodiment, performing magnetic resonance scanning of the area to be scanned according to the scanning strategy includes: acquiring a pulse sequence for magnetic resonance scanning of the scanning area, the scanning pulse sequence includes a gradient pulse sequence and a radio frequency pulse sequence, and the gradient pulse sequence refers to all The scanning strategy design; excite a radio frequency pulse sequence to generate a magnetic resonance signal in the area to be scanned; excite the gradient pulse sequence to encode the magnetic resonance signal to generate k-space data; reconstruct the k-space data to generate the Magnetic resonance image of the area to be scanned.

[0083] In this embodiment, the scanning strategy determined according to the preset rule is used to scan the area to be detected, which avoids the problem that the technician determines the scanning strategy based on anatomical experience, which leads to inaccurate determination of the scanning strategy and inaccurate MRI scan results. At the same time, the increase in scanning time caused by the technician's independent determination of the scanning strategy is avoided.

[0084] The technical solution of this embodiment solves the problem of scanning center and scanning center caused by the technician’s experience by automatically or semi-automatically determining the scanning strategy of the area to be scanned according to the pre-scanned image and preset rules, and performing magnetic resonance scanning of the area to be scanned according to the scanning strategy. The problem of the uncertainty of the scanning direction and the low detection accuracy improves the uniformity and accuracy of the scanning strategy of the pre-scan area, and improves the accuracy of the magnetic resonance scanning result.

[0085] Example two

[0086] Figure 2A It is a flowchart of a magnetic resonance scanning method provided in the second embodiment of the present invention. On the basis of the above-mentioned embodiment, a method for determining the scanning direction according to the pre-scan image is further provided. Correspondingly, the method includes:

[0087] S210: Obtain a pre-scanned image of the area to be scanned of the scanned object.

[0088] S220: Perform image segmentation processing on the pre-scan image to obtain a humerus image of the shoulder joint.

[0089] S230. Determine the tendon direction of the area to be scanned according to the humerus image, wherein the tendon direction of the area to be scanned includes the tendon direction of the cross section and the coronal plane.

[0090] Wherein, the humerus image is pre-processed, the structural direction of each pixel in the humeral image is determined, and the tendon direction is determined according to the structural direction of each pixel.

[0091] Optionally, determining the direction of the tendon of the cross section according to the humerus image includes:

[0092] Determine the first preset area of ​​the cross section according to the first scan layer of the humeral image and the first acquisition rule, and perform linear structure detection on each pixel in the first preset area; superimpose the structure direction of each pixel to generate the first A tendon direction is determined as the tendon direction of the cross section.

[0093] Optionally, determining the first preset area of ​​the cross section according to the first scan layer of the humerus and the first acquisition rule includes: selecting a first preset number of scan layers adjacent to the first scan layer, the first preset A number of scanning layers are parallel to the first initial direction; in each scanning layer, a first preset range of pixel collection areas centered on the center of the humerus is determined; the pixel collection areas of each scanning layer are combined to form a first preset area .

[0094] Optionally, the first scan layer is the scan layer with the smallest distance from the human head in the humeral image. For example, the first acquisition rule may take the first scanning layer as the center, and extract the cross-sectional pixel acquisition areas adjacent to the first scanning layer along the Z-axis direction, where there may be three pixel acquisition areas, including the first scanning layer and the second scanning layer. Optionally, the pixel collection area can be a matrix block for two adjacent scanning layer regions on one scanning layer. In each pixel acquisition area, the X-axis direction starts with the center of the humerus, the number of pixels in the X-axis direction can range from 50-100, the Y-axis direction starts with the center of the first scan layer, and the pixels in the Y direction The number of points can range from 20-100, and the pixel collection areas are combined to form a first preset area, and the first preset area is parallel to the first initial direction. Wherein, if the humerus image belongs to the left shoulder joint figure, the first initial direction can be a direction at an angle of -30 degrees with the X axis direction; if the humerus image belongs to the right shoulder joint figure, the first initial direction can be the same as X The axis direction is at an angle of 30 degrees.

[0095] Wherein, the linear structure detection is used to obtain the structure direction of each pixel in the first preset area, and optionally, the linear structure detection is a first-order linear structure detection. Exemplarily, the linear structure detection may be based on the Harris algorithm or the Hessian algorithm to detect the structure direction of each pixel. Optionally, the structural direction of each pixel can also be determined through the Sobel edge detection operator or the gray value gradient. In this embodiment, the Harris algorithm is taken as an example to introduce the detection method of the pixel structure direction: calculate the Harris gradient matrix of each image shape pixel, and analyze the characteristic root and the characteristic vector, where the characteristic root represents the structural response value of the pixel , The feature vector represents the structural direction of the pixel.

[0096] In this embodiment, the structural direction of each pixel in the first preset area is superimposed, that is, the feature vector of each pixel is superimposed, and the superimposing direction generated after superimposition is determined as the tendon direction of the cross section, that is, the cross section is statistically The structural direction of the pixels in the first preset area of ​​the humerus image in the plane predicts the direction of the tendon in the cross-section, which automatically determines the direction of the tendon of the shoulder joint and improves the accuracy of the tendon direction. Optionally, before superimposing the structural directions of each pixel point, it includes: numerically sorting the response value of each pixel point, and filtering the pixels in a preset sorting range. In this embodiment, as an example, the response value of each pixel is sorted from large to small in numerical value, and the pixels corresponding to the top 10% of the response values ​​in the ranking are selected. The structural directions of the filtered pixels are superimposed to generate the tendon direction of the cross section. In this embodiment, the structural direction superimposition is performed by screening pixels that meet the response value conditions, which reduces the calculation workload, improves the calculation efficiency of the tendon direction, avoids the time-consuming MRI scan, and reduces the response value. The interference of small pixels improves the accuracy of tendon direction.

[0097] Optionally, determining the direction of the tendon of the coronal plane by determining the image of the humerus includes: rotating the image of the humerus according to the direction of the first tendon; determining the image of the humerus according to the second scan layer of the rotated humerus image and a second acquisition rule The second preset area of ​​the coronal plane, and linear structure detection is performed on each pixel of the second preset area; the structure direction of each pixel is superimposed to generate a second tendon direction, which is determined as the coronal The tendon direction of the face.

[0098] In this embodiment, the humerus image is centered on the Z axis and rotated in the direction of the first tendon to display the coronal plane of the humerus image.

[0099] Optionally, determining the second preset area of ​​the coronal plane according to the second scan layer of the rotated humeral image and the second acquisition rule includes: selecting a second preset number of scan layers adjacent to the second scan layer, The second preset number of scan layers are parallel to the second initial direction; the pixel collection area of ​​the second preset range centered on the center of the humerus is determined in each scan layer; the pixel collection areas of each scan layer are combined to form the first 2. Preset area.

[0100] In this embodiment, optionally, the second scan layer is the largest scan layer of the humerus image, where the largest scan layer refers to the scan layer with the largest volume in the humerus image. Exemplarily, the number of pixels in each scan layer is counted, and the scan layer with the largest number of pixels is determined as the largest scan layer; or the humerus image is projected to the Z axis, and the scan layer with the largest projection value is determined as the largest scan Floor.

[0101] In this embodiment, a second preset number of pixel collection areas adjacent to the second scanning layer are selected in the Y-axis direction of the rotated humerus image to form a second preset area, for example, the second preset number It may be 7, that is, the second preset area includes the second scanning layer and six pixel collection areas adjacent and continuous up and down to the second scanning layer. Optionally, the pixel collection area may be a matrix block. In each pixel acquisition area, the X-axis direction starts with the center of the humerus, the number of pixels in the X-axis direction can range from 50-100, the Y-axis direction starts with the center of the first scan layer, and the pixels in the Y direction The number of points can range from 20 to 100, and the pixel collection areas are combined to form a second preset area, and the second preset area is parallel to the second initial direction. Optionally, for the humerus images of the left shoulder joint and the right shoulder joint, the second initial direction is both parallel to the X-axis direction.

[0102] In this embodiment, linear structure detection is performed on each pixel in the second preset area, the structure direction of each pixel in the second preset area is superimposed, and the feature vector of each pixel is superimposed, and the superimposed The generated superimposition direction is determined as the direction of the tendon in the coronal plane, that is, the direction of the tendon in the coronal plane is predicted by counting the structural direction of the pixels in the first preset area of ​​the humerus image in the coronal plane, which automatically determines the tendon direction of the shoulder joint and improves The accuracy of the direction of the tendon. Optionally, before superimposing the structural directions of each pixel point, it includes: numerically sorting the response value of each pixel point, and filtering the pixels in a preset sorting range.

[0103] S240: Determine the scanning direction of the cross section and the coronal plane of the area to be scanned according to the direction of the tendon.

[0104] In this embodiment, magnetic resonance scanning is performed along the direction of the tendon, which is beneficial to improve the scanning accuracy of the tendon area and determine the damage of the tendon area.

[0105] The technical solution of this embodiment, by selecting a preset area in the pre-scan image, and determining the scanning direction of the cross section and the coronal plane according to the structural direction of each pixel in the preset area, it is solved that the pre-scan image cannot reflect the tendon The direction problem realizes the automatic determination of the tendon direction of the shoulder joint, improves the accuracy of the tendon direction, and improves the accuracy of the detection result of the area to be scanned.

[0106] On the basis of the foregoing embodiment, the method further includes:

[0107] Perform image segmentation processing on the pre-scan image to obtain the humerus image of the shoulder joint; obtain the humeral midline of the humerus image, perform linear fitting on the humerus midline, and calculate the bone long axis direction of the humerus image.

[0108] In this embodiment, the humerus layer with the longest bone is compared and selected in the sagittal plane, and the midline of the humerus is determined, and linear fitting is performed. The fitting result is determined as the direction of the long axis of the bone. The direction determines the scanning direction of the sagittal plane of the area to be detected.

[0109] Optionally, rotate the humerus image according to the direction of the long axis of the bone, the direction of the first tendon, and the direction of the second tendon, re-determine the new bone long axis direction according to the rotated humerus image, and determine the new bone long axis direction as The direction of the long axis of the bone in the sagittal plane.

[0110] It should be noted that the determination of the direction of the long axis of the bone and the direction of the tendon has no sequence relationship, and can be executed simultaneously or in any sequence relationship.

[0111] Optionally, the scanning direction of the area to be scanned includes: the scanning direction of the cross section is: the zero degree direction, the tendon direction of the coronal plane and the long axis of the bone; the scanning direction of the sagittal plane is: the tendon direction of the cross section, the coronal plane The direction of the tendon and the long axis of the bone; the scanning directions of the coronal plane are: the tendon direction of the cross section, the tendon direction of the coronal plane and the long axis of the bone.

[0112] Exemplary, see Figure 2B , Figure 2C with Figure 2D , Figure 2B It is a schematic diagram of the sagittal scan of the shoulder joint provided in the second embodiment of the present invention. From top to bottom, the cross-sectional view, coronal view, and sagittal view of the sagittal scan are shown in sequence. The box indicates the area to be scanned. , The horizontal line in the box indicates the scanning direction. The scanning directions of the coronal view and the sagittal view respectively pass through the center of the humerus, and the intersection of the two scanning directions displayed on the sagittal plane is the determined scan center. Located at or near the center of the humeral joint. Figure 2C It is a schematic diagram of the shoulder joint coronal scan provided in the second embodiment of the present invention. From top to bottom, the cross-sectional view, coronal view, and sagittal view during the sagittal scan are shown in order. The box indicates the area to be scanned. The horizontal line in the box represents the scan direction. Only the scan direction of the sagittal view passes through the center of the humerus, and the intersection of the two scan directions displayed on the coronal plane is the determined scan center, which is located at the edge of the humeral joint . Figure 2D It is a schematic diagram of a cross-sectional scan of the shoulder joint provided in the second embodiment of the present invention. From top to bottom, the cross-sectional view, coronal view, and sagittal view during the sagittal plane scan are shown in sequence, where: the box indicates the area to be scanned, The horizontal line in the box represents the scanning direction, the intersection of the two scanning directions displayed on the coronal plane is the determined scanning center, and the scanning center is located at the edge of the humeral joint.

[0113] In this embodiment, the scanning direction of the area to be scanned is automatically determined according to the above method, instead of determining the scanning direction of the magnetic resonance technician based on his own experience in the prior art, reducing the uncertainty of the scanning direction, and improving the uniformity and accuracy of the scanning direction. It improves the accuracy of the scanning result of the area to be scanned.

[0114] Example three

[0115] image 3 It is a magnetic resonance scanning method provided in the third embodiment of the present invention. On the basis of the foregoing embodiment, a method for determining the scanning center according to the pre-scanned image is further provided. Correspondingly, the method specifically includes:

[0116] S310. Obtain a pre-scan image of the area to be scanned of the scanning object.

[0117] S320: Automatically or semi-automatically determine the scanning direction of the area to be scanned according to the pre-scanned image.

[0118] S330: Rotate the humerus image according to the scanning direction.

[0119] In this embodiment, when determining the scan centers of different virtual planes, the humerus image is rotated according to the scan direction of the corresponding virtual plane. Exemplarily, if the scan center of the cross section is determined, the humerus image is rotated according to the zero-degree direction, the coronal tendon direction and the bone long axis direction; if the scan center of the sagittal plane is determined, the humerus image is rotated according to the cross section Rotate the tendon direction, the tendon direction of the coronal plane and the long axis direction of the bone; if the scan center of the coronal plane is determined, the humerus image will be rotated according to the tendon direction of the cross section, the tendon direction of the coronal plane and the long axis direction of the bone.

[0120] S340: Determine the scan center of the humerus image according to the rotated humerus image and the scan center determination rule.

[0121] In this embodiment, the humerus image is rotated according to the scanning direction, the plane with the smallest distance from the center of the body is selected among the rotated planes, and the tangent point of the plane with the humerus is determined as the scan center of the corresponding virtual plane. Exemplarily, the scan direction of the sagittal plane is taken as an example to introduce the method of determining the scan center: the humerus image is rotated in turn according to the tendon direction of the cross section, the tendon direction of the coronal plane, and the long axis direction of the bone, and the above rotation is determined. The angle is the plane of the normal direction, the distance between each plane and the center of the body is detected, and the point tangent to the humerus in the plane with the smallest distance is determined as the scanning direction of the sagittal plane.

[0122] Optionally, step S340 includes:

[0123] Determine the body center of the scanned object; determine the pixel point with the smallest distance from the body center in the rotated humerus image as the scan center of the humerus image.

[0124] Wherein, the body center of the scanned object may be a preset straight line segment. Illustratively, the body center may be determined according to the position of the human spine. Calculate the distance between each pixel in the rotated humeral image and the center of the body, and determine the pixel with the smallest distance as the scan center.

[0125] Exemplary, see Figure 2E , Figure 2E It is a schematic diagram of the scanning strategy provided in the second embodiment of the present invention. Among them, the small dots in the second row are the scan centers of the transverse, coronal and sagittal planes. In this embodiment, during the coronal scan, the scan direction of the cross section is parallel to the supraspinatus tendon, the scan direction of the sagittal plane is parallel to the long axis of the humerus, and the scan layer of the coronal plane is parallel to the supraspinatus tendon, and the scan center It is the medial side of the humerus; in the sagittal scan, the scan direction of the cross section is parallel to the supraspinatus tendon, the scan direction of the coronal plane is parallel to the supraspinatus tendon, and the scan direction of the sagittal plane is parallel to the direction of the long axis of the humerus; When the scan direction of the coronal plane is parallel to the supraspinatus tendon, the scan direction of the sagittal plane is parallel to the long axis of the humerus, and the scan center is the inner side of the humerus.

[0126] In this embodiment, a method for quickly determining the scan center is provided. The rotated humerus image is placed in a three-dimensional coordinate system. If the humerus image is a left shoulder and humerus image, the pixel with the largest X coordinate in the rotated humerus image Determine as the scan center of the humerus image; if the humerus image is a right shoulder humerus image, the pixel with the smallest X coordinate in the humerus image after rotation is determined as the scan center of the humerus image. Among them, the three-dimensional coordinate system is determined according to the initial scanned image. In the scanned image, the upright direction of the parallel human body is the Z axis, the horizontal direction of the human arm is the X axis, and the direction from the front of the human body to the back of the human body is the Y axis.

[0127] Further, the method may further include the following steps: determining a radio frequency pulse sequence and a gradient pulse sequence according to the scanning center and scanning direction; driving the radio frequency coil to generate a corresponding radio frequency pulse according to the radio frequency pulse sequence, and driving the gradient coil to generate a corresponding gradient pulse according to the gradient pulse sequence; The radio frequency pulse further excites the subject's area to be scanned to generate a magnetic resonance signal; the gradient pulse generates a gradient field that encodes the magnetic resonance signal to generate K-space data; the K-space data is reconstructed to obtain the area to be scanned Magnetic resonance image.

[0128] In the above method for determining the scan center, only by comparing the coordinates of each pixel point in the humeral image, there is no need to determine the body center of the scanned object and calculate the distance between the pixel point and the body center, which is simple and fast, and improves the efficiency of determining the scan center.

[0129] In the technical solution of this embodiment, the scan center of the humeral image is determined by rotating the humerus image according to the scan direction and the scan center determination rule, which solves the problem of manually determining the scan center inaccurately and realizes the automatic and rapid determination of the area to be scanned. The scan center improves the accuracy and determination efficiency of the scan center.