A method and device for measuring breast tumor volume using reflection, sound velocity, and attenuation parameters

Abstract

The present invention provides a method and device for measuring breast tumor volume by using reflection, sound velocity and attenuation parameters. The scheme comprises the following steps: emitting ultrasonic waves to breast tissue to obtain reflected wave signals and transmitted wave signals for different directions of breast tissue; obtaining three kinds of medical image data based on ultrasonic reflection, sound velocity and attenuation imaging; segmenting and classifying the obtained medical image data to obtain binary data corresponding to the medical image data; obtaining surface positioning anchor points of breast tissue according to the binary data; triangulating the surface positioning anchor points to form a plurality of triangular facets, and splicing the plurality of triangular facets to form a closed spatial polyhedron; performing smoothing operation on the spatial polyhedron; performing polyhedron volume calculation based on the spatial polyhedron after the smoothing operation to obtain the tumor volume in the breast tissue; the method has the advantages of obtaining all-round, three-dimensional and stereoscopic ultrasonic information and more accurately calculating the breast tumor volume.

Description

Technical Field

[0001] The present invention relates to the field of breast tumor detection, and in particular to a method and device for measuring breast tumor volume using reflection, sound velocity and attenuation parameters. Background Art

[0002] Breast cancer is the leading cause of cancer death worldwide. According to data from the International Agency for Research on Cancer of the World Health Organization in 2020, breast cancer surpassed lung cancer to become the leading cause of cancer death worldwide with 2.26 million new cases. In China, breast cancer is the number one killer of women's health. Moreover, compared with Europe and the United States, due to the lack of early screening methods, cancer cells often spread when the cancer is discovered.

[0003] Existing methods for breast cancer examination generally include mammography, traditional ultrasound examination, magnetic resonance imaging, modified ultrasound examination, etc.

[0004] Among them, mammography is generally regarded as the gold standard in breast imaging examination. However, the mammography examination process requires compression of the breast, which is not very specific, especially in the assessment of suspicious breast calcifications in dense breasts, with a false negative rate as high as 76%. Compared to Western women, Eastern women have relatively denser breasts and experience a lower age of onset for breast cancer. Therefore, mammography is not suitable as an early screening method for breast examinations in Asian women. Traditional ultrasound examinations can only provide images of a single cross-section of breast tissue. Clinically, doctors need to mentally construct the three-dimensional structure of breast tissue based on real-time two-dimensional images, which is highly subjective, lacks repeatability and traceability, and can easily produce inaccurate estimates of the location, shape, and size of tumors. Although MRI has the advantage of sensitivity, it is time-consuming and expensive, making it unsuitable as an early screening method. Modified ultrasound examination equipment, such as GE's ABUS and Siemens' ABVS, can obtain three-dimensional images, but they only collect reflected wave signals to form grayscale images, resulting in a relatively simple presentation of breast tissue and failing to clearly show the obvious difference between lesion locations and normal breast tissue. Furthermore, the aforementioned breast cancer examination methods, due to the lack of precision in the data obtained, cannot accurately calculate the size of tumors within breast tissue. Summary of the Invention

[0005] The purpose of this invention is to provide a method and apparatus for accurately calculating the volume of breast tumors using reflection, sound velocity, and attenuation parameters.

[0006] To address the aforementioned technical problems, this invention provides a method for measuring breast tumor volume using reflection, sound velocity, and attenuation parameters, comprising the following steps:

[0007] Step 1: Emit ultrasound waves to the breast tissue and obtain reflected and transmitted wave signals from different directions of the breast tissue, where different directions cover the full range of angles of the breast tissue.

[0008] Step 2: Perform ultrasound reflection, sound velocity, and attenuation imaging using reflected and transmitted wave signals to obtain three types of medical image data based on ultrasound reflection, sound velocity, and attenuation imaging.

[0009] Step 3: Segment and classify the obtained medical image data to obtain the corresponding binarized data;

[0010] Step 4: Obtain surface localization anchor points of tumors in breast tissue based on binarized data;

[0011] Step 5: Triangulate the surface positioning anchor points to form multiple triangular facets, and then combine the multiple triangular facets to form a closed spatial polyhedron.

[0012] Step 6: Perform a smoothing operation on the spatial polyhedron;

[0013] Step 7: Calculate the volume of the polyhedron based on the smoothed spatial polyhedron to obtain the tumor volume in the breast tissue.

[0014] Furthermore, in step 4, the MarchingCube algorithm is used in conjunction with binarized data to obtain the surface localization anchor points of tumors in breast tissue.

[0015] Furthermore, in step 5, the Delaunay triangulation algorithm is used to triangulate the surface positioning anchor points of the tumor in the breast tissue.

[0016] Furthermore, after obtaining the spatial polyhedron in step 5, a mesh subdivision algorithm is used to optimize the face mesh of the spatial polyhedron.

[0017] Furthermore, in step 6, the spatial polyhedron is smoothed as a whole using a three-dimensional polyhedron patch smoothing algorithm.

[0018] Furthermore, in step 7, the volume of the spatial polyhedron is calculated using a three-dimensional polyhedron volume calculation algorithm.

[0019] Furthermore, the three-dimensional polyhedron patch smoothing algorithm is a Laplacian smoothing algorithm, a Curvature smoothing algorithm, a Taubin algorithm, or a hybrid algorithm derived from the Laplacian smoothing algorithm, the Curvature smoothing algorithm, and the Taubin algorithm.

[0020] The present invention also discloses an apparatus for measuring breast tumor volume using reflection, sound velocity, and attenuation parameters, comprising a signal generator, a signal receiver, and at least one ultrasound probe; the ultrasound probe is connected to the signal generator and the signal receiver respectively.

[0021] Furthermore, it also includes a data acquisition module connected to the signal receiver; the signal receiver transmits the received ultrasonic signal to the data acquisition module.

[0022] Furthermore, the signal generator is used to emit ultrasound waves onto breast tissue.

[0023] The advantage of the present invention is that after the signal generator emits ultrasonic waves to the human breast tissue, the signal receiver will collect the reflected wave signal and the transmitted wave signal of the ultrasonic wave, and perform ultrasonic reflection imaging through the reflected wave signal and the transmitted wave signal, thereby obtaining comprehensive, three-dimensional, and stereoscopic medical image data. Subsequently, the medical image data is processed and a spatial polyhedron is finally obtained. The volume of the spatial polyhedron is then calculated to obtain the tumor volume in the breast tissue. Since the information obtained during the information collection is sufficiently comprehensive, the breast tumor volume data obtained when calculating the volume of the breast tissue tumor is also more comprehensive. Attached Figure Description

[0024] Figure 1 This is a schematic diagram of the structure of the device of the present invention. DETAILED DESCRIPTION

[0025] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention are within the scope of protection of the present invention.

[0026] Those skilled in the art should understand that, in the disclosure of the present invention, the terms "longitudinal", "transverse", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside" and the like to indicate orientations or positional relationships are based on the orientations or positional relationships shown in the accompanying drawings, which are only for the convenience of describing the present invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation. Therefore, the above terms should not be understood as limiting the present invention.

[0027] It is to be understood that the term "one" should be understood as "at least one" or "one or more", that is, in one embodiment, the number of an element may be one, while in another embodiment, the number of the elements may be multiple, and the term "one" should not be understood as a limitation on the quantity.

[0028] like Figure 1 The present invention provides a method for measuring breast tumor volume using reflection, sound velocity, and attenuation parameters, comprising the following steps:

[0029] Step 1: Emit ultrasound waves to the breast tissue and obtain reflected and transmitted wave signals from different directions of the breast tissue, where different directions cover the full range of angles of the breast tissue.

[0030] Step 2: Perform ultrasound reflection, sound velocity, and attenuation imaging using reflected and transmitted wave signals to obtain three types of medical image data based on ultrasound reflection, sound velocity, and attenuation imaging.

[0031] Step 3: Segment and classify the obtained medical image data to obtain the corresponding binarized data;

[0032] Step 4: Obtain surface localization anchor points of tumors in breast tissue based on binarized data;

[0033] Step 5: Triangulate the surface positioning anchor points to form multiple triangular facets, and then combine the multiple triangular facets to form a closed spatial polyhedron.

[0034] Step 6: Perform a smoothing operation on the spatial polyhedron;

[0035] Step 7: Calculate the volume of the polyhedron based on the smoothed spatial polyhedron to obtain the tumor volume in the breast tissue.

[0036] Specifically, after the signal generator emits ultrasound waves into the human breast tissue, the signal receiver collects the reflected and transmitted ultrasound signals. Ultrasound reflection imaging is then performed using these signals to obtain comprehensive, three-dimensional, and stereoscopic medical imaging data. This data is then processed to obtain a spatial polyhedron, which is used to calculate the volume of the tumor within the breast tissue. Because the information collected is comprehensive enough, richer attribute elements can be referenced, allowing for better differentiation of tumor boundaries and the construction of a more realistic tumor surface. This results in more accurate calculations of the breast tumor volume.

[0037] In step 1, at least one signal generator emits ultrasound waves to the patient's breast tissue, and simultaneously, at least one signal receiver receives the reflected and transmitted ultrasound waves. In this embodiment, a large number of ultrasound probes are used to perform a comprehensive, three-dimensional, and stereoscopic scan of the human breast tissue. Due to the large number of ultrasound probes, this method can emit ultrasound signals to the patient's breast tissue from multiple directions, and then obtain the reflected and transmitted ultrasound waves from multiple directions through the signal receiver, making the breast tissue data obtained by this method more comprehensive.

[0038] In this method, after acquiring the reflected and transmitted ultrasonic waves, the signal receiver uses an algebraic reconstruction algorithm to reconstruct the sound velocity and attenuation images of the ultrasonic waves. Then, it uses synthetic aperture focusing technology to reconstruct the reflected ultrasonic waves. Simultaneously, the sound velocity, attenuation, and reflection images contain information about the sound velocity, attenuation, and reflection of the ultrasonic waves. This ensures that the medical image data obtained through ultrasound reflection imaging includes sound velocity, attenuation, and reflection information. Compared to existing technologies that only provide reflection information, this method provides more comprehensive data. Furthermore, because ultrasonic waves... The speed at which sound propagates within an object is related to the elastic modulus (stiffness) and density of the material. Therefore, the numerical values ​​of each data point in the sound velocity image can, to some extent, represent the elastic modulus and density properties of the breast tissue at the data point location. Similarly, the attenuation rate of ultrasound is related to the density of the material. Therefore, the numerical values ​​of each data point in the attenuation image can, to some extent, represent the density properties of the breast tissue at the data point location. This allows the proposed solution to obtain trimodal medical imaging data that can display multiple properties within the breast tissue. Among these, the reflection data mainly corresponds to the morphology of the breast tissue, the sound velocity data corresponds to the stiffness and density of the breast tissue, and the attenuation data corresponds to the density of the breast tissue.

[0039] Specifically, in step 3, when segmenting the obtained medical image data, segmentation can be performed by setting an empirical threshold or by using existing classic algorithms such as the Otsu method to adaptively adjust the threshold.

[0040] Furthermore, the trimodal data is actually the feedback values ​​of three different features of the same spatial region obtained during a single ultrasound acquisition process, referred to as volume data. This spatial region is represented as a cubic spatial matrix in the final data, where each point in the matrix has its own spatial coordinates and corresponding reflection, sound velocity, and attenuation attribute values. Secondly, in step 3, segmentation and classification are mainly based on the three attribute values ​​of reflection, sound velocity, and attenuation to classify the points in these spatial matrices and distinguish whether they belong to tumor tissue. A binary volume data is generated for each "yes" or "no" result. Preferably, in step 4, the MarchingCube algorithm is used in conjunction with the binary data to obtain the surface localization anchor points of the tumor in the breast tissue.

[0041] Specifically, based on the binarized data after the three-dimensional volume data is binarized, the MarchingCube algorithm is used to determine the cut surfaces and cut points of the tumor tissue edge in each voxel unit (a minimum cube unit formed by 8 adjacent volume data points in the up, down, left, and right directions) in the imaging space. Then, interpolation calculations are performed based on the attribute values ​​of reflection, sound velocity, and attenuation. The cut surfaces and cut points are comprehensively optimized using the interpolation calculation results and empirical coefficients obtained from a large number of experiments, and the surface positioning anchor points of the tumor tissue generated by the MarchingCube algorithm are adjusted.

[0042] The interpolation calculation here is mainly based on the attribute values ​​(reflection, sound velocity, and attenuation imaging values) of each point in the volume data and the spatial coordinates.

[0043] Specifically, during the interpolation calculation, if the reflectance image values ​​corresponding to two adjacent points P1 and P2 on the volume data are V1 and V2 respectively, and the target threshold for segmentation is V', then the default interpolation point calculation formula for finding the segmentation point P' between P1 and P2 is generally considered to be as follows:

[0044]

[0045] In addition to the segmentation value, consider the sound velocity values ​​S1 and S2 and the attenuation values ​​A1 and A2 corresponding to two points P1 and P2, and incorporate them into the difference calculation in a weighted manner. The properties of the material's elastic modulus and density can be referenced to more accurately fit the actual boundary points. The specific formula is as follows (where C1 and C2 are constants in the difference formula):

[0046]

[0047] It is worth mentioning that the "empirical coefficients obtained from numerous experiments" mentioned above specifically refer to the constants of the difference formula used for calculating the boundary anchor points related to tumor tissue, based on experimental results. Comprehensive optimization refers to using the above formula to obtain better interpolation between voxels, find more accurate tangent points, and ultimately generate a boundary surface that better fits the tumor.

[0048] Preferably, in step 5, the surface positioning anchor points of the tumor in the breast tissue are triangulated using a Delaunay triangulation algorithm.

[0049] Specifically, based on the tangent points obtained in step 4, triangulation is performed according to the Delaunay triangulation algorithm, and based on the triangulation results, a basic fitted patch data of the surface of the breast tissue mass is constructed to form a closed spatial polyhedron.

[0050] Among them, the tangent points obtained in step 4 serve as surface positioning anchor points.

[0051] Specifically, the function of combining facet data into a closed spatial polyhedron is a built-in feature of the Delaunay triangulation algorithm. Since the input of the algorithm is a set of random spatial points, the output is a set of triangle vertices after triangulation (each item in the set contains 3 points, forming a triangle). By connecting the relevant triangles according to the original spatial point data and this new output, a surface is constructed when displaying it in 3D, thus forming a closed spatial polyhedron.

[0052] Preferably, after obtaining the spatial polyhedron in step 5, a mesh subdivision algorithm is used to optimize the mesh of the spatial polyhedron.

[0053] Specifically, the Butterfly mesh subdivision algorithm and the Loop mesh subdivision algorithm are used to optimize the patch mesh and increase the number of anchor points in areas with drastic surface unevenness, so as to avoid loss of details during subsequent surface smoothing.

[0054] It is worth mentioning that the grid subdivision algorithm in this case is mainly used to convert large grids into small grids so that certain morphological features will not be distorted due to excessive smoothing in subsequent smoothing operations.

[0055] Preferably, in step 6, the spatial polyhedron is smoothed as a whole using a three-dimensional polyhedron patch smoothing algorithm.

[0056] Specifically, a three-dimensional polyhedron smoothing algorithm is used to smooth the entire polyhedron as a whole, and the smoothing coefficient of the local area is set based on the sound velocity and attenuation volume data to adaptively remove obvious irregular burrs, smooth the polyhedron surface, and make it have a smoother rather than angular surface, thus avoiding calculation distortion.

[0057] Among them, patch smoothing is also known as mesh smoothing. In the embodiments of this scheme, the mesh smoothing algorithm can be selected from: Laplacian smoothing algorithm, Curvature smoothing algorithm and Taubin algorithm, as well as various hybrid algorithms derived from the above three.

[0058] Preferably, in step 7, the volume of the spatial polyhedron is calculated using a three-dimensional polyhedron volume calculation algorithm.

[0059] Specifically, the general idea of ​​the three-dimensional polyhedron volume calculation algorithm is to decompose the polyhedron according to the result of triangulation, connect the surface triangles with a point inside the polyhedron to form a tetrahedron, thereby decomposing the polyhedron into a certain number of tetrahedrons for volume calculation.

[0060] Preferably, the three-dimensional polyhedron patch smoothing algorithm is a Laplacian smoothing algorithm, a Curvature smoothing algorithm, a Taubin algorithm, or a hybrid algorithm derived from the Laplacian smoothing algorithm, the Curvature smoothing algorithm, and the Taubin algorithm.

[0061] The present invention also discloses an apparatus for measuring breast tumor volume using reflection, sound velocity, and attenuation parameters, comprising a signal generator, a signal receiver, and at least one ultrasound probe; the ultrasound probe is connected to the signal generator and the signal receiver respectively.

[0062] Specifically, this device has a built-in ultrasound probe located within the detection area. Since the ultrasound probe is connected to both a signal generator and a signal receiver, the signal generator can emit ultrasound waves to the breast tissue via the probe, and the signal receiver can receive the returned ultrasound signals. The reflected and transmitted wave signals received by the probe and receiver are then used to obtain sound velocity, attenuation, and reflection images. In one embodiment, a 128-probe array is used, with each probe connected to both the signal transmitter and receiver. The 128 probes are evenly distributed along the inner side of the sphere within the detection area, enabling the ultrasound probe to acquire three-dimensional data of the breast. Specifically, as... Figure 1The 128 ultrasound probes are arranged around the inner side of the sphere, allowing the ultrasound probes to emit ultrasound signals from multiple angles. Simultaneously, when collecting sound velocity and reflection information of the ultrasound signals through the probes, the multi-angle arrangement of the probes enables the acquisition of information data from multiple angles of the breast tissue, thus obtaining more comprehensive three-dimensional data of the breast. This increases the comprehensiveness of the information collected by the ultrasound probes and improves the accuracy of subsequent image reconstruction based on this information.

[0063] Preferably, it also includes a data acquisition module connected to the signal receiver; the signal receiver transmits the received ultrasonic signal to the data acquisition module.

[0064] Specifically, the signal receiver collects the reflected wave signal and the transmitted wave signal of the ultrasound, and then transmits the reflected wave signal and the transmitted wave signal to the data acquisition module, which uses the data acquisition module in conjunction with the algebraic reconstruction algorithm and synthetic aperture focusing technology to reconstruct the image.

[0065] Preferably, the signal generator is used to emit ultrasound waves to breast tissue.

[0066] Specifically, by using a signal generator in conjunction with an ultrasound probe to reflect ultrasound waves, the size of tumors in breast tissue can be accurately determined.

[0067] The present invention is not limited to the above-mentioned optimal implementation mode. Anyone can derive other forms of products under the inspiration of the present invention. However, no matter what changes are made in the shape or structure, any technical solution that is the same or similar to that of the present application falls within the scope of protection of the present invention.

Claims

1. A method for measuring breast tumor volume using reflection, sound velocity, and attenuation parameters, characterized in that: The following steps are involved: Step 1, transmitting ultrasound to breast tissue to obtain reflected wave signals and transmitted wave signals at different positions of the breast tissue, wherein the different positions cover all angles of the breast tissue; Step 2: Perform ultrasonic reflection, sound velocity, and attenuation imaging through the reflected wave signal and the transmitted wave signal, and obtain three types of medical imaging data based on ultrasonic reflection, sound velocity, and attenuation imaging; Step 3: segment and classify the obtained medical image data to obtain binary data corresponding to the medical image data; Step 4, obtaining the surface positioning anchor point of the tumor in the breast tissue according to the binary data; Step 5: triangulate the surface anchor points to form multiple triangular facets, and combine the multiple triangular facets to form a closed spatial polyhedron; Step 6: Perform smoothing operation on the spatial polyhedron; Step 7: Calculate the volume of the polyhedron based on the smoothed spatial polyhedron to obtain the tumor volume in the breast tissue; In step 3, the same spatial area obtained during an ultrasonic acquisition process is reflected in the final data as a cubic spatial matrix, in which each point of the matrix has its own spatial coordinates and corresponding reflection attribute value, sound speed attribute value, and attenuation attribute value. The points in these spatial matrices are classified according to the three attribute values ​​of reflection, sound speed, and attenuation to distinguish whether they belong to tumor tissue, and a binary data is generated for "yes" or "no".

2. The method for measuring breast tumor volume using reflection, sound velocity and attenuation parameters according to claim 1, characterized in that: In step 4, the MarchingCube algorithm is used in conjunction with the binarized data to obtain the surface positioning anchor points of the tumor in the breast tissue.

3. The method for measuring breast tumor volume using reflection, sound velocity and attenuation parameters according to claim 1, characterized in that: In step 5, the surface positioning anchor points of the tumor in the breast tissue are triangulated using the Delaunay triangulation algorithm.

4. The method for measuring breast tumor volume using reflection, sound velocity, and attenuation parameters according to claim 1, characterized in that: After the spatial polyhedron is obtained in step 5, a mesh subdivision algorithm is used to optimize the patch mesh of the spatial polyhedron.

5. The method for measuring breast tumor volume using reflection, sound velocity, and attenuation parameters according to claim 1, characterized in that: In step 6, the spatial polyhedron is smoothed as a whole using a three-dimensional polyhedron patch smoothing algorithm.

6. The method for measuring breast tumor volume using reflection, sound velocity, and attenuation parameters according to claim 1, characterized in that: In step 7, the volume of the spatial polyhedron is calculated using a three-dimensional polyhedron volume calculation algorithm.

7. The method for measuring breast tumor volume using reflection, sound velocity, and attenuation parameters according to claim 5, characterized in that: The three-dimensional polyhedron patch smoothing algorithm is a Laplacian smoothing algorithm, a Curvature smoothing algorithm, a Taubin algorithm, or a hybrid algorithm derived from the Laplacian smoothing algorithm, the Curvature smoothing algorithm, and the Taubin algorithm.

8. A device for the method of measuring breast tumor volume using reflection, sound velocity, and attenuation parameters as claimed in any one of claims 1 to 7, comprising a signal generator and a signal receiver, characterized in that: It also includes at least one ultrasonic probe; the ultrasonic probe is connected to the signal generator and the signal receiver respectively.

9. The device according to claim 8, characterized in that: It also includes a data acquisition module connected to the signal receiver; the signal receiver transmits the received reflected wave signal and transmitted wave signal to the data acquisition module.

10. The device according to claim 8, characterized in that: The signal generator is used for transmitting ultrasonic waves to breast tissue.

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