A method and apparatus for puncturing image to suppress enhancement artifacts

Abstract

The present application provides a kind of puncture image inhibits the method for enhancing artifact, by including the following steps: according to the deflection scanning angle, prior estimation is carried out to needle angle and position, delete the artifact in the middle of the linear and the needle channel artifact left around the tissue outside estimated range;The needle body line segment is connected and template filling, and the needle body area is established;The needle body area is carried out connected domain analysis processing, and the needle body area template of single connected domain is determined;The single connected domain needle body area template and the last frame template are carried out frame correlation processing, and stable needle body template image is generated;The needle body stable needle body template image and non-deflection needle body image are carried out image fusion, and the image with clear and stable needle body can be generated.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of image processing, and in particular to a method and device for suppressing and enhancing artifacts in puncture images. BACKGROUND

[0002] Puncture enhancement technology has been widely used in the field of medical ultrasound, which is mainly used to guide doctors to perform puncture surgery. This technology can clearly display the fusion image of the needle and the tissue during the puncture process, making the needle completely visible during the puncture process, greatly improving the safety and efficiency of such surgery. The existing puncture enhancement technology is to first cross-scan a non-deflection two-dimensional image and a large-deflection two-dimensional image, then binarize the large-deflection image using a binarization method, then obtain the straight line position and angle through Hough transform, and finally select the position of the needle with the highest probability as the needle body. After the position of the needle body is obtained, the region of the large-deflection image is extracted and then fused with the non-deflection image to obtain the final puncture enhancement display output image. SUMMARY

[0003] In view of the above problems, the present application is proposed to provide a method and device for suppressing and enhancing artifacts in puncture images, which can overcome the above problems or at least partially solve the problems, comprising:

[0004] A method for suppressing and enhancing artifacts in puncture images, comprising the steps of:

[0005] Priori estimating the angle and position of the needle body according to the deflection scan angle, deleting straight lines outside the estimated range and artifacts appearing in the middle of the tissue and needle path artifacts left around the needle entry;

[0006] Connecting and template filling the needle body line segment to establish a needle body region;

[0007] Performing connected component analysis on the needle body region to determine a single connected component needle body region template;

[0008] Performing frame correlation processing on the single connected component needle body region template and the previous frame template to generate a stable needle body template image;

[0009] Performing image fusion on the stable needle body template image and the non-deflection needle body image to generate an image with a clear and stable needle body.

[0010] Further, the priori estimation of the angle and position of the needle body according to the deflection scan angle, and the deletion of straight lines outside the estimated range and artifacts appearing in the middle of the tissue and needle path artifacts left around the needle entry, comprises the steps of:

[0011] The probe emits an ultrasound wave with no deflection angle and an ultrasound wave with a preset deflection angle in sequence to generate an image of the needle body with no deflection and an image of the needle body with a large-angle deflection;

[0012] The image of the needle body with a large-angle deflection is transformed in a coordinate conversion manner to determine the image coordinate of the needle body when the image of the needle body with a large-angle deflection is not deflected,

[0013] The image coordinate of the needle body when the image of the needle body with a large-angle deflection is not deflected is generated according to the image of the needle body with a large-angle deflection and the image coordinate of the needle body when the image of the needle body with a large-angle deflection is not deflected;

[0014] The image of the needle body after the coordinate conversion is subjected to noise suppression to generate an image of the needle body after noise suppression;

[0015] The image of the needle body after noise suppression is processed according to an edge detection algorithm to generate a binary image of the needle body edge;

[0016] The image of the needle body edge is subjected to line segment detection to obtain a needle body edge line segment;

[0017] The needle body edge line segment is subjected to angle limitation to remove a line segment with a large deviation.

[0018] Further, the image of the needle body with a large-angle deflection is transformed in a coordinate conversion manner to determine the position of the image of the needle body when the image of the needle body with a large-angle deflection is not deflected, and the image of the needle body after coordinate conversion is generated, wherein the formula of the coordinate conversion is:

[0019]

[0020]

[0021] The coordinates of the needle body image with a large-angle deflection are (il, ip), the coordinates of the needle body image after coordinate conversion are (l, p) in the coordinates without deflection, θ is the preset deflection angle, Pointspace is the point spacing, and Linespace is the line spacing.

[0022] Further, the needle body edge line segment is subjected to angle limitation to remove a line segment with a large deviation, and the method further comprises:

[0023] The formula is

[0024]

[0025] The corresponding straight line angle is calculated, wherein the coordinates of the start and end points of the straight line Ln are ((Xns, Yns), (Xne, Yne)), Point space space is the point spacing, and Line spaceInput image line spacing, unit: mm.

[0026] Further, the connecting and template filling of the line segments of the needle body establishes a needle body region, comprising the steps of:

[0027] Classifying the needle body line segments according to the upper and lower boundaries of the needle body to determine the upper and lower boundary coordinates;

[0028] Determining the left and right boundary point coordinates in the upper and lower boundaries;

[0029] Establishing a rectangular region similar to the needle body region according to the four boundary points;

[0030] Performing fusion template filling in the rectangular region;

[0031] Performing spatial filtering processing on the fusion template.

[0032] Further, the connecting and template filling of the line segments of the needle body establishes a needle body region, comprising the steps of:

[0033] After smoothing the interrupted needle body region, connecting the interrupted needle body region to establish a plurality of connected domains;

[0034] Calculating the continuous connected domain ratio of each connected domain in the plurality of connected domains to determine the connected domain with the highest confidence coefficient;

[0035] Attenuating the weight value in the other connected domains except the connected domain with the highest confidence coefficient.

[0036] Further, the connecting and template filling of the line segments of the needle body establishes a needle body region, comprising the steps of:

[0037] Through the formula

[0038]

[0039] Calculating the continuous connected domain ratio of each connected domain in the plurality of connected domains, wherein,

[0040] Pn represents the number of continuous connected domains in the connected domain n,

[0041] Pn represents the total number of pixels in the connected domain n;

[0042] Determining the connected domain with the maximum Pn value as the connected domain with the highest confidence coefficient.

[0043] A puncture image suppression and enhancement artifact device, which implements the steps of the puncture image suppression and enhancement artifact method described in any of the above, comprising:

[0044] a priori estimation module configured to perform a priori estimation on the needle angle and position according to the deflection scan angle, and delete straight lines outside the estimation range, artifacts appearing in the tissue, and needle path artifacts left around the needle entry;

[0045] a needle region establishing module configured to connect the needle line segments and perform template filling to establish a needle region;

[0046] a connected domain analysis module configured to perform connected domain analysis on the needle region to determine a single connected domain needle region template;

[0047] a frame correlation processing module configured to perform frame correlation processing on the single connected domain needle region template and a previous frame template to generate a stable needle template image;

[0048] an image generation module configured to perform image fusion on the stable needle template image and a non-deflection needle image to generate an image with a clear stable needle.

[0049] An electronic device includes a processor, a memory, and a computer program stored on the memory and capable of running on the processor, and the computer program, when executed by the processor, implements the steps of the puncture image artifact suppression and enhancement method of any one of the above.

[0050] A computer readable storage medium stores a computer program, and the computer program, when executed by a processor, implements the steps of the puncture image artifact suppression and enhancement method of any one of the above.

[0051] The present application has the following advantages:

[0052] The present application carries out prior estimation on the needle body angle and position according to the deflection scanning angle, deletes the straight line outside the estimation range and the artifact appearing in the tissue and the needle path artifact left around the needle insertion; connects and template fills the needle body line segment, establishes the needle body region; carries out connected domain analysis and processing on the needle body region, determines the single connected domain needle body region template; carries out frame correlation processing on the single connected domain needle body region template and the last frame template, generates a stable needle body template image; carries out image fusion on the stable needle body template image and the non-deflection needle body image, generates an image with clear and stable needle body. The present application does not depend on the estimation of the prior width of the needle body, when the needle shakes, the needle will not be directly identified as a straight line completely deviating from the needle path due to the bending caused by the shaking, for the needle body identified within the angle limit, the needle body image region of the previous frame is also used as a prior value and compared with the current identification, so that the artifact with large shaking is excluded and aliasing phenomenon is not generated. The method in the present application classifies and connects the identified line segment, and then carries out connected domain processing, so that the identified needle body will not be interrupted and affect the puncture effect. For the flickering needle body, the method excludes the line segment directly appearing in the image when screening the line segment, so that the flickering needle path in the tissue is avoided. The flickering phenomenon of the identified needle body is further weakened through the frame correlation processing on the identified needle body template. After the artifact suppression processing, when the user punctures, the aliasing, discontinuous and flickering needle body will not appear in the puncture enhanced image. Therefore, the image quality after fusion can be effectively improved, the artifact in the deflection image is brought into the fusion image due to the position mis-detection of the needle body, and finally a clear and stable needle body appears in the puncture enhanced image. BRIEF DESCRIPTION OF DRAWINGS

[0053] In order to more clearly illustrate the technical solutions of the present application, the following will briefly introduce the drawings needed to be used in the description of the present application. Obviously, the drawings in the following description are only some embodiments of the present application, and other drawings can be obtained by those skilled in the art without any creative labor.

[0054] Figure 1 It is a step flow chart of the puncture image artifact suppression and enhancement method provided by an embodiment of the present application;

[0055] Figure 2 It is the edge and line segment detection result of the needle body provided by an embodiment of the present application;

[0056] Figure 3 It is the angle limit result provided by an embodiment of the present application;

[0057] Figure 4The region restriction result provided by an embodiment of the present application;

[0058] Figure 5 The needle body image after line segment connection and template filling provided by an embodiment of the present application;

[0059] Figure 6 The needle body image after spatial filtering provided by an embodiment of the present application;

[0060] Figure 7 The needle body image after connected domain processing provided by an embodiment of the present application;

[0061] Figure 8 The needle body image after frame correlation processing provided by an embodiment of the present application;

[0062] Figure 9 The image without deflection provided by an embodiment of the present application;

[0063] Figure 10 The deflected image provided by an embodiment of the present application;

[0064] Figure 11 The fused image provided by an embodiment of the present application;

[0065] Figure 12 The module structure diagram of the puncture image suppression and enhancement artifact device provided by an embodiment of the present application;

[0066] Figure 13 The structure diagram of a computer device provided by an embodiment of the present application. DETAILED DESCRIPTION

[0067] In order to make the purpose, features and advantages of the present application more obvious and easy to understand, the present application will be further described in detail below in combination with the drawings and specific embodiments. Obviously, the described embodiments are some embodiments of the present application, but not all the embodiments. Based on the embodiments in the present application, all the other embodiments obtained by those skilled in the art without creative labor fall within the protection scope of the present application. In an embodiment of the present application, a method for suppressing and enhancing artifacts of a puncture image is provided;

[0068] The method as shown in Figure 1 includes the following steps:

[0069] S110, prior estimation is made on the needle body angle and position according to the deflection scanning angle, and the straight lines outside the estimated range and the artifacts appearing in the middle of the tissue and the needle path artifacts left around the needle insertion are deleted.

[0070] S120, the needle body line segments are connected and template filled, and the needle body region is established.

[0071] S130, the needle body region is subjected to connected domain analysis processing to determine a single connected domain needle body region template;

[0072] S140, the single connected domain needle body region template is subjected to frame correlation processing with the previous frame template to generate a stable needle body template image;

[0073] S150, the stable needle body template image is subjected to image fusion with a non-deflected needle body image to generate an image with a clear stable needle body.

[0074] In the embodiments of the present application, the needle angle and position are estimated a priori according to the deflection scanning angle, and the straight lines outside the estimated range and the artifacts appearing in the middle of the tissue and the needle path artifacts left around the needle insertion site are deleted; the needle line segments are connected and template filled to establish a needle body region; the needle body region is subjected to connected domain analysis processing to determine a single connected domain needle body region template; the single connected domain needle body region template is subjected to frame correlation processing with the previous frame template to generate a stable needle body template image; and the stable needle body template image is subjected to image fusion with a non-deflected needle body image to generate an image with a clear stable needle body. The present application does not rely on the estimation of the a priori width of the needle, and when the needle is shaken, the needle will not be directly identified as a straight line completely deviating from the needle path due to the bending caused by the shaking, and for the needle identified within the angle limit, the needle body image region of the previous frame is also used as a priori value for comparison with the current identification to exclude the artifacts with large shaking and to avoid aliasing. The method in the present application classifies and connects the identified line segments, and then performs connected domain processing, so that the identified needle body will not be interrupted to affect the puncture effect. For the flickering needle body, the present method excludes the line segments directly appearing in the image when performing line segment screening to avoid the flickering needle path in the tissue. The flickering phenomenon of the identified needle body is further weakened by performing frame correlation processing on the identified needle body template. After the artifact suppression processing, the aliasing, discontinuity and flickering needle body will not appear in the puncture enhanced image when the user is puncturing. Therefore, the image quality after fusion can be effectively improved, and the artifacts in the deflection image caused by the position misidentification of the needle body are brought into the fusion image. Finally, a clear and stable needle body appears in the puncture enhanced image.

[0075] In the following, the method for suppressing and enhancing artifacts in the puncture image in the present exemplary embodiments will be further described. As described in step S110, the specific process of "estimating the needle angle and position a priori according to the deflection scanning angle, and deleting the straight lines outside the estimated range and the artifacts appearing in the middle of the tissue and the needle path artifacts left around the needle insertion site" described in step S110 can be further described in combination with the following description.

[0076] The probe emits an ultrasound wave with no deflection angle and an ultrasound wave with a preset deflection angle in sequence to generate an image of the needle body with no deflection and an image of the needle body with large-angle deflection according to the following steps.

[0077] It should be noted that the purpose of this step is to generate two different images, and by coordinate conversion, the two images are combined to remove artifacts, flicker and discontinuous parts, thereby obtaining a clear needle body image.

[0078] The image of the needle body with large-angle deflection is transformed according to the coordinate conversion to determine the needle body image coordinates when the image of the needle body with large-angle deflection is not deflected according to the following steps.

[0079] It should be noted that the formula of the coordinate conversion is:

[0080]

[0081]

[0082] Where the coordinates of the needle body image with large-angle deflection are (il, ip), the coordinates after coordinate conversion are (l, p) in the non-deflection coordinates, θ is the preset deflection angle, Pointspace is the point spacing, and Linespace is the line spacing.

[0083] The needle body image after coordinate conversion is generated according to the image of the needle body with large-angle deflection and the needle body image coordinates when the image of the needle body with large-angle deflection is not deflected according to the following steps.

[0084] It should be noted that the purpose of obtaining this image is to subsequently fuse with the non-deflection image to remove artifacts and generate a clear and complete needle body image.

[0085] The needle body image after coordinate conversion is subjected to noise suppression to generate a needle body image after noise suppression according to the following steps.

[0086] It should be noted that image noise refers to unnecessary or redundant interference information existing in image data. The existence of noise seriously affects the quality of remote sensing images, so before image enhancement processing and classification processing, various factors that hinder people's acceptance of information in the image must be corrected, which is called image noise. Noise can be theoretically defined as "unpredictable, only probabilistic and statistical methods can be used to recognize random errors". Therefore, it is appropriate to regard image noise as a multi-dimensional random process, so the method of describing noise can completely borrow the description of random processes, that is, using its probability distribution function and probability density distribution function. The purpose of this step is to generate a needle body image with less noise, which is beneficial to the detection of lines in the next step.

[0087] The noise-repressed needle image is processed according to an edge detection algorithm to generate a binary needle edge image, as described in the following steps.

[0088] In one implementation, the needle image is processed using a Canny edge detection algorithm to extract a binary needle edge image.

[0089] The needle edge image is subjected to line segment detection to obtain needle edge line segments, as described in the following steps.

[0090] In one implementation, the needle edge image is subjected to LSD (Line Segment Detector) algorithm to obtain line segments containing continuous or discontinuous needle edges.

[0091] The needle edge line segments are subjected to angle restriction to remove line segments with large deviations, as described in the following steps.

[0092] It should be noted that the angle of the corresponding straight line is calculated by the formula

[0093]

[0094] The angle of the corresponding straight line is calculated, where the straight line Ln corresponds to the coordinates of the start and end points of the straight line ((Xns, Yns), (Xne, Yne)), and Point space is the distance between image data points, and Line space is the distance between input image lines, in mm.

[0095] If the angle θ - ε < Lθ < θ + ε, it is considered to be a valid line segment, where θ is the priori estimated puncture needle angle, and ε is the redundant angle.

[0096] The value of θ is usually steerAngle, and steerAngle is the deflection scanning angle, which is known, and the value of ε is usually less than steerAngle / 2.

[0097] When the scanning angle is exactly perpendicular to the puncture needle angle, the needle is most clearly visualized in the deflection image. When the scanning angle deviates from the perpendicular angle by a certain angle, the needle visualization is also not clear because the deflection image itself has many artifacts. At this time, even if the correct needle position is found in the deflection image, and the deflection image is superimposed and fused into the non-deflection image, the needle position enhancement is not obvious, and even other artifacts may be introduced. Therefore, in the artifact suppression algorithm, the straight line segments deviating from the priori angle by a large amount are removed first.

[0098] When the angle restriction is performed, there can still be some line segments belonging to the artifacts in the center of the image or far from the actual position of the needle body, so it is important to eliminate these artifacts for the subsequent connection of the needle body. Generally, the needle body cannot be directly in the middle of the image, and the length of the artifact is usually less than the length of the actual needle body. First, the transverse distance of each identified possible needle body line segment from the position of the needle is calculated, and if the distance is greater than the length of the corresponding needle body line segment, it is likely that the line segment is an artifact in the middle of the image, so such line segments can be excluded. Then, for the artifacts that appear at the needle position but belong to the previous needle path, such needle paths are usually shortened due to tissue healing, and there is a certain distance between the positions of each needle insertion, so the longest line segment detected is taken as the center, and the centers of other line segments are within a distance of the length of the longest line segment from the center of the longest line segment, and are determined to belong to the current needle path, and the line segments of other parts that exceed the distance are determined to be artifacts of the previous needle path, as shown in Figures 2-4

[0099] As described in step S120 above, the specific process of step S120 "connecting and template filling of the needle body line segments to establish the needle body region" can be further explained in combination with the following description.

[0100] As described in the following steps, the needle body line segments are classified according to the upper and lower boundaries of the needle body to determine the upper and lower boundary coordinates; the left and right boundary point coordinates are determined in the upper and lower boundaries; and a rectangular region similar to the needle body region is established according to the four boundary points.

[0101] It should be noted that the line segments screened out in the previous step are the boundaries of the needle body, so the screened out line segments need to be integrated to form the needle body region. The needle body line segments are classified according to the upper and lower boundaries, and the line segments with overlapping parts in the horizontal direction of the upper and lower boundaries are determined to belong to the same needle body region. If there are line segments that do not overlap with other line segments, such line segments are separately divided into a needle body region. After obtaining the needle body region to which each line segment belongs, the leftmost and rightmost boundary points in the upper and lower boundaries of the region, i.e. the minimum and maximum coordinates in the horizontal direction, are calculated, so that the positions of the four vertices of a rectangular region similar to the needle body can be obtained.

[0102] As described in the following steps, the rectangular region is fused and template filled, as shown in Figure 5

[0103] ​​It should be noted that the fusion template is used for weighted superposition of the deflected image and the non-deflected image, and the value of the fusion template represents the weighting proportion of the deflected image. The position of the rectangular region enclosed in the above step is considered as the puncture needle position, and the weight value coefficient of the deflected image at this position is the largest, which is usually set to 1. In order to facilitate calculation, the value of the Mask can be quantized and converted into an integer shape.

[0104] In a specific implementation, the value of the straight line position Mask is set to 128.

[0105] The fusion template is subjected to spatial filtering processing according to the following steps.

[0106] It should be noted that if the deflected and non-deflected images are directly subjected to weighted superposition by using the Mask, the puncture needle position in the image after superposition will be more conspicuous, and the fusion effect is poor. On the other hand, when the position of the needle body template detected in the continuous frames has a slight change, the image after fusion will have a significant flicker phenomenon. Therefore, the Mask needs to be subjected to spatial filtering processing.

[0107] In a specific implementation, 5*5 mean filtering

[0108]

[0109] Wherein m and n are the coordinates of the Mask template, and the filtered needle body image is as shown in Figure 6 .

[0110] As described in the above step S130, the specific process of the step S130 of "performing connected domain analysis processing on the needle body region to determine a single connected domain needle body region template" can be further illustrated in combination with the following description.

[0111] It should be noted that for the position of the needle body region existing only one, the connected domain processing is still fully connected. For the needle body region existing multiple interruptions, first, the interrupted needle body region is smoothed, and then the smoothed interrupted needle body region is connected, at this time, one or several connected domains are obtained, and finally, the connected domain screening processing is performed. Because the real needle body exists only one, the final needle body part can be obtained after screening, as shown in Figure 7 .

[0112] The interrupted needle body region is smoothed, and then the interrupted needle body region is connected to establish several connected domains, according to the following steps.

[0113] It should be noted that the purpose of smoothing is to make the connected domain connection smooth and stable. After smoothing, the template is subjected to connected domain processing. For a position where only one needle region exists, the connected domain processing is still fully connected. For a position where multiple interrupted needle regions exist, the interrupted needle region parts are first smoothed, and then the smoothed interrupted needle regions are connected. At this time, one or several connected domains are obtained, and finally, the connected domain screening processing is performed. Because there is only one real needle, the final needle part can be obtained after screening.

[0114] The continuous connected domain ratio of each connected domain in the several connected domains is calculated as described in the following steps, and the connected domain with the highest confidence coefficient is determined.

[0115] It should be noted that the continuous connected domain ratio of each connected domain in the several connected domains is calculated by the formula

[0116]

[0117] The continuous connected domain ratio of each connected domain in the several connected domains is calculated, wherein,

[0118] ConnectLabel_n_p_size represents the number of pixels of the continuous connected domain in the connected domain n,

[0119] ConnectLabel_n_size represents the total number of pixels in the connected domain n;

[0120] The connected domain with the maximum Pn value is determined as the connected domain with the highest confidence coefficient.

[0121] As described in the following steps, the weight in other connected domains except the connected domain with the highest confidence coefficient is decayed.

[0122] It should be noted that in normal cases, only one puncture needle penetrates into the imaging area, so the needle body connected domain can only have one. When the number of detected connected domains is greater than 1, each connected domain is analyzed, and the weight of the connected domain with a lower confidence coefficient is decayed. Because the position of the needle body in the imaging area is usually continuously changed, the connected domain with the maximum Pn value is determined as the connected domain with the highest confidence coefficient according to the prior knowledge of the previous frame. In addition, the other connected domains are more likely to be artifacts, and the weight in the connected domain is decayed.

[0123]

[0124] Decay coef is a pre-set decay coefficient.

[0125] After the screening of the connected domain and the decay of the artifact are performed, the mask template of the single connected domain needle body part is obtained.

[0126] As described above in step S140, the specific process of "performing frame correlation processing on the needle region template of the single connected domain and the last frame template to generate a stable needle template image" in step S140 can be further described in conjunction with the following description.

[0127] It should be noted that since the needle will inevitably vibrate and the like when puncturing, if the template of the needle region is directly overlaid on the deflected needle image and then fused with the non-deflected image, the fused needle will also flicker with the vibration of the template. In order to avoid this phenomenon, before weighted fusion, the template after the connected domain processing and the template result of the last frame are subjected to frame correlation processing, as shown in Figure 8 .

[0128] As described above in step S150, the specific process of "performing image fusion on the stable needle template image of the needle and the non-deflected needle image to generate an image with a clear stable needle" in step S150 can be further described in conjunction with the following description.

[0129] It should be noted that the image fusion of the stable needle template image of the needle and the non-deflected needle image is performed by generating a to-be-stacked template through frame processing, stacking the to-be-stacked template on the deflected needle image to generate a stacked deflected needle image, fusing the stacked deflected needle image with the non-deflected image to generate a target image.

[0130] In a specific implementation, the non-deflected image as shown in Figure 9 is fused with the deflected image as shown in Figure 10 to generate a fused target image as shown in Figure 11 .

[0131] Referring to Figure 12 , an embodiment of the present application provides a device for suppressing and enhancing artifacts of a puncture image, comprising:

[0132] A prior estimation module 210 is configured to perform prior estimation on the angle and position of the needle according to the deflection scanning angle, and delete straight lines outside the estimated range, artifacts appearing in the tissue, and needle path artifacts left around the needle entry;

[0133] A needle region establishing module 220 is configured to connect and template fill the needle line segments to establish a needle region;

[0134] A connected domain analysis module 230 is configured to perform connected domain analysis processing on the needle region to determine a single connected domain needle region template;

[0135] The frame correlation processing module 240 is configured to perform frame correlation processing on the single connected region needle region template and a last frame template to generate a stable needle template image.

[0136] The image generation module 250 is configured to perform image fusion on the stable needle template image and a non-deflection needle image to generate an image with a clear stable needle.

[0137] In an embodiment, the prior estimation module 210 comprises:

[0138] The image establishment module is configured to generate a non-deflection needle image and a large-angle deflection needle image by sequentially transmitting an ultrasonic wave with a first non-deflection angle and an ultrasonic wave with a first preset deflection angle through the probe.

[0139] The coordinate conversion module is configured to transform the large-angle deflection needle image according to a coordinate conversion manner to determine a needle image coordinate when the large-angle deflection needle image is not deflected,

[0140] The image conversion module is configured to generate a coordinate-converted needle image according to the large-angle deflection needle image and the needle image coordinate when the large-angle deflection needle image is not deflected.

[0141] The noise suppression module is configured to perform noise suppression on the coordinate-converted needle image to generate a noise-suppressed needle image.

[0142] The binarization module is configured to process the noise-suppressed needle image according to an edge detection algorithm to generate a binarized needle edge image.

[0143] The edge detection module is configured to perform line segment detection on the needle edge image to obtain a needle edge line segment.

[0144] The angle limiting module is configured to perform angle limiting on the needle edge line segment to remove a line segment with a large deviation.

[0145] In an embodiment, the large-angle deflection needle image is transformed according to a coordinate conversion manner to determine a needle image position when the large-angle deflection needle image is not deflected, and a coordinate-converted needle image is generated, wherein a coordinate conversion formula is:

[0146]

[0147] wherein the large-angle deflection needle image coordinate is (il, ip), the coordinate-converted needle image coordinate is (l, p), θ is a preset deflection angle, Pointspace is a point spacing, and Linespace is a line spacing.

[0148] In an embodiment, the angle limiting of the needle edge line segments, removing the line segments with large deviation, further comprises:

[0149] The angle of the corresponding straight line is calculated by the formula

[0150] The angle of the corresponding straight line is calculated by the formula space is the distance between image data points, Line space is the distance between input image lines, in mm.

[0151] In an embodiment, the needle region establishing module 220 comprises:

[0152] A line segment classification module is configured to classify the needle line segments according to the upper and lower boundaries of the needle, and determine the coordinates of the upper and lower boundaries.

[0153] A boundary point confirmation module is configured to determine the coordinates of the left and right boundary points in the upper and lower boundaries.

[0154] A region determination module is configured to establish a rectangular region similar to the needle region according to the four boundary points.

[0155] A fusion template filling module is configured to perform fusion template filling in the rectangular region.

[0156] A spatial filtering module is configured to perform spatial filtering processing on the fusion template.

[0157] In an embodiment, the connected domain analysis module 230 comprises:

[0158] A connected domain establishing module is configured to connect the interrupted needle regions after smoothing, and establish a plurality of connected domains.

[0159] A connected domain ratio calculation module is configured to calculate the continuous connected domain ratio of each connected domain in the plurality of connected domains, and determine the connected domain with the highest confidence coefficient.

[0160] A weight decay module is configured to decay the weights in the connected domains other than the connected domain with the highest confidence coefficient.

[0161] In an embodiment, the calculation of the continuous connected domain ratio of each connected domain in the plurality of connected domains, and the determination of the connected domain with the highest confidence coefficient, comprises:

[0162] The continuous connected domain ratio of each connected domain in the plurality of connected domains is calculated by the formula

[0163]

[0164] calculating a continuous connected domain ratio of each connected domain in the several connected domains, wherein,

[0165] representing the number of pixels of the continuous connected domain in the connected domain n,

[0166] representing the total number of pixels in the connected domain n;

[0167] determining the connected domain with the maximum value of Pn as the connected domain with the highest confidence coefficient.

[0168] Referring to Figure 13 , a computer device of a puncture image enhancement method for suppressing artifacts is shown, which can specifically include the following:

[0169] The computer device 12 is in the form of a general-purpose computing device, and the components of the computer device 12 can include but are not limited to one or more processors or processing units 16, system memory 28, and a bus 18 connecting different system components, including the system memory 28 and the processing unit 16.

[0170] The bus 18 represents one or more of several types of buses 18, including a memory bus 18 or memory controller, a peripheral bus 18, a graphics acceleration port, a processor or local bus 18 using any of a variety of bus 18 architectures including an industry standard architecture (ISA) bus 18, a microchannel architecture (MAC) bus 18, an enhanced ISA bus 18, a video electronics standards association (VESA) local bus 18, and a peripheral component interconnect (PCI) bus 18. For example, these architectures include but are not limited to an industry standard architecture (ISA) bus 18, a microchannel architecture (MAC) bus 18, an enhanced ISA bus 18, a video electronics standards association (VESA) local bus 18, and a peripheral component interconnect (PCI) bus 18.

[0171] The computer device 12 typically includes a variety of computer system readable media. These media can be any available media that can be accessed by the computer device 12 and includes both volatile and nonvolatile media, removable and non-removable media.

[0172] The system memory 28 can include computer system readable media in the form of volatile memory, such as random access memory (RAM) 30 and / or cache memory 32. The computer device 12 can further include other removable / non-removable, volatile / non-volatile computer system storage media. By way of example only, a storage system 34 can be provided for reading from and writing to non-removable, non-volatile magnetic media (typically called a "hard drive"). Figure 13A disk drive, a floppy disk drive, a CD-ROM drive, a DVD-ROM drive, or other removable media drive, can be provided in the computing device 12 to read from and / or write to a removable nonvolatile media (such as a floppy disk, a CD-ROM, a DVD-ROM, or other optical media). Such a drive can be connected to the bus 18 by one or more data media interfaces. The memory can include at least one program product having a set (e.g., at least one) of program modules 42 configured to carry out the functions of embodiments of the application.

[0173] The program / utility 40, having a set (at least one) of program modules 42, can be stored in memory, for example, RAM, ROM, EEPROM, flash or other non-volatile memory. Each of the operating system, one or more application programs, other program modules 42, and program data, or some combination thereof, can include an implementation of a networking environment. The program modules 42 generally carry out the functions and / or methodologies of embodiments of the application as described herein.

[0174] The computer device 12 can also communicate with one or more external devices 14 such as a keyboard, a pointing device, a display 24, a camera, etc.; one or more devices that enable a health care professional to interact with the computer device 12; and / or one or more devices that enable the computer device 12 to communicate with one or more other computer devices. Such communication can be via an input / output (I / O) interface 22. Still yet, the computer device 12 can communicate with one or more networks such as a local area network (LAN), a general wide area network (WAN), and / or a public network (e.g., the Internet) via a network adapter 20. As depicted, the network adapter 20 communicates with the other components of the computer device 12 via the bus 18. It should be appreciated that the network adapter 20 and / or the bus 18 can be implemented using one or more types of technology. Figure 13 Other hardware and / or software modules that can be used in conjunction with the computer device 12 include, but are not limited to, microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data archival storage systems 34, etc.

[0175] The processing unit 16 executes the various functions and data processing operations of the embodiments of the application by running programs stored in the system memory 28.

[0176] In other words, the processing unit 16, when executing the programs, performs a method of suppressing and enhancing artifacts in a puncture image.

[0177] In the embodiments of the present application, the present application further provides a computer readable storage medium, which stores a computer program, and the computer program is executed by a processor to implement the method for suppressing and enhancing artifacts of a puncture image according to any one of the embodiments of the present application.

[0178] That is, the computer program is executed by the processor to implement the method for suppressing and enhancing artifacts of a puncture image.

[0179] Any combination of one or more computer readable medium can be employed. The computer readable medium can be a computer readable signal medium or a computer readable storage medium. A computer readable storage medium can be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. More specific examples (a non-exhaustive list) of the computer readable storage medium include an electrical connection having one or more wires, a portable computer diskette, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In this document, the computer readable storage medium can be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device.

[0180] A computer readable signal medium can include a propagated data signal with computer readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated signal can take any of a variety of forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A computer readable signal medium can be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device.

[0181] Computer program code for carrying out operations of the present application can be written in any combination of one or more programming languages, including an object oriented programming language such as Java, Smalltalk, C++ or the like and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code can execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the latter scenario, the remote computer can be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or the connection can be made to an external computer (for example, through the Internet using an Internet Service Provider). The embodiments of the present application described above are implemented in a manner as follows, and each of the embodiments focuses on the differences from other embodiments. The same or similar parts among the embodiments can be mutually referred to.

[0182] While the preferred embodiments of the application have been described above, additional variations and modifications of the embodiments can occur to those skilled in the art once advised of the basic inventive concepts. Therefore, the appended claims are intended to cover all such additional variations and modifications as fall within the scope of the application.

[0183] Finally, it should be noted that the terms "first", "second", and the like, herein do not denote any order, quantity, combination, or importance, but rather are used to distinguish one element from another, and do not imply singular or plural. Also, the terms "comprises", "comprising", or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but can include other elements not expressly listed or inherent to such process, method, article, or apparatus. An element proceeded by "comprises... a" does not, without more constraints, exclude the presence of additional identical elements in the process, method, article, or apparatus that comprises the element.

[0184] The above provides a method and device for suppressing and enhancing artifacts of a puncture image. The principles and implementation manners of the present application are described by using specific examples. The above description of the embodiments is only used to help understand the method and core idea of the present application. For those skilled in the art, the specific implementation manners and application ranges can be changed according to the idea of the present application. The above description of the present application should not be understood as a limitation.

Claims

1. A method of puncturing image suppression of an enhanced artifact, characterized by, The method comprises the steps of: Priori estimation of needle angle and position according to deflection scanning angle, deletion of straight lines outside the estimation range, and removal of artifacts appearing in the middle of the tissue and needle path artifacts left around the needle insertion site; generation of a non-deflection needle image and a large-angle deflection needle image by sequentially transmitting a non-deflection angle ultrasound wave and a pre-set deflection angle ultrasound wave through the probe; determination of the needle image coordinates when the large-angle deflection needle image is not deflected by transforming the large-angle deflection needle image according to coordinate transformation; and the formula for coordinate transformation is: wherein the large-angle deflection needle image coordinates are (il, ip), the coordinates after coordinate transformation are (l, p) in the non-deflection state, θ is the pre-set deflection angle, Pointspace is the point spacing, and Linespace is the line spacing; Generation of the coordinate-transformed needle image according to the large-angle deflection needle image and the needle image coordinates when the large-angle deflection needle image is not deflected; noise suppression of the coordinate-transformed needle image to generate a noise-suppressed needle image; processing of the noise-suppressed needle image according to an edge detection algorithm to generate a binary needle edge image; line segment detection of the needle edge image to obtain needle edge line segments; angle restriction of the needle edge line segments to remove line segments with large deviations; Calculation of the corresponding straight line angle by the formula wherein the straight line Ln corresponds to the start and end point coordinates of the straight line ((Xns, Yns), (Xne, Yne)), Pointspace is the image data point spacing, and Linespace is the input image line spacing, with the unit of mm; Connection and template filling of the needle line segments to establish a needle region; Connected domain analysis and processing of the needle region to determine a single connected domain needle region template; Frame correlation processing of the single connected domain needle region template and the previous frame template to generate a stable needle template image; Image fusion of the stable needle template image and the non-deflection needle image to generate an image with a clear and stable needle.

2. The method of claim 1, wherein, The connection and template filling of the needle line segments to establish a needle region comprises the steps of: Classification of the needle line segments according to the upper and lower boundaries of the needle to determine the upper and lower boundary coordinates; Determination of the left and right boundary point coordinates in the upper and lower boundaries; Establishment of a rectangular region similar to the needle region according to the four boundary points; Fusion template filling in the rectangular region; Spatial filtering processing of the fusion template.

3. The method of claim 1, wherein, The connected domain analysis and processing of the needle region to determine a single connected domain needle region template comprises the steps of: Smooth the interrupted needle region and connect the interrupted needle region to establish a plurality of connected domains; Calculation of the continuous connected domain ratio of each connected domain in the plurality of connected domains to determine the connected domain with the highest confidence coefficient; Attenuation of the weight values in the other connected domains except the connected domain with the highest confidence coefficient.

4. The method of claim 3, wherein, The calculating the continuous connected domain ratio of each connected domain in the several connected domains, determining the connected domain with the highest confidence coefficient, comprises the steps of: The continuous connected domain ratio of each connected domain in the several connected domains is calculated by the formula ConnectLabel_n_p_size represents the number of pixels of the continuous connected domain in the connected domain n, ConnectLabel_n_size represents the total number of pixels in the connected domain n; The connected domain with the maximum Pn value is determined as the connected domain with the highest confidence coefficient. The device for suppressing and enhancing puncture image pseudo-objects realizes the steps of the method for suppressing and enhancing puncture image pseudo-objects as claimed in any one of claims 1 to 4, comprising:

5. An apparatus for puncturing an image to suppress an enhancement artifact, characterized by, a prior estimation module, configured to perform prior estimation on the needle angle and position according to the deflection scanning angle, and delete straight lines outside the estimated range, pseudo-objects appearing in the tissue, and needle channel pseudo-objects left around the needle entry; a needle body region establishing module, configured to connect and template fill the needle body line segment, and establish a needle body region; a connected domain analysis module, configured to perform connected domain analysis processing on the needle body region, and determine a single connected domain needle body region template; a frame correlation processing module, configured to perform frame correlation processing on the single connected domain needle body region template and a last frame template, and generate a stable needle body template image; an image generation module, configured to perform image fusion on the stable needle body template image and a non-deflection needle body image, and generate an image with a clear stable needle body. The device comprises a processor, a memory, and a computer program stored on the memory and capable of running on the processor, and when the computer program is executed by the processor, the steps of the method for suppressing and enhancing puncture image pseudo-objects as claimed in any one of claims 1 to 4 are realized.

6. An electronic device, characterized by The computer program is stored on the computer readable storage medium, and when the computer program is executed by the processor, the steps of the method for suppressing and enhancing puncture image pseudo-objects as claimed in any one of claims 1 to 4 are realized.

7. A computer readable storage medium, characterized in that, ​

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