Method for automatic adjustment of image starting depth for ultrahigh frequency ultrasound systems

Abstract

This invention relates to a method for automatically adjusting the initial depth of an image in an ultra-high frequency ultrasound system, comprising the following steps: Step 1: During image scanning, checking image stability; Step 2: Detecting the position on the skin surface; Step 3: Cropping the image. This invention provides image integrity, facilitating observation.

Description

Technical Field

[0001] This invention relates to the field of ultrasound system imaging, and more particularly to a method for automatically adjusting the initial depth of an image in an ultra-high frequency ultrasound system. Background Technology

[0002] Compared to conventional ultrasound imaging, high-frequency ultrasound systems offer extremely high image resolution and are primarily used in dermatology, preclinical experiments on small animals (rats, mice, rabbits, zebrafish), and ophthalmology. For these anatomical structures, during scanning, the probe plane is generally kept as parallel as possible to the skin surface, close to the skin but not pressed tightly, with acoustic conductive gel in between to avoid affecting skin tissue imaging or compressing internal organs. The displayed image will include the probe dead zone (approximately 1 mm) and the effective image area (1–3 mm) of the acoustic conductive gel layer. Within a fixed image display window, the display of the probe dead zone and acoustic conductive gel layer will reduce the effective image area, failing to fully utilize the advantages of ultra-high image resolution. Furthermore, the display of invalid image information will cause unnecessary attention for the user.

[0003] Ultra-high frequency medical ultrasound systems offer extremely high image resolution; for example, a 50MHz probe can achieve a resolution of 0.03mm. This provides dermatology with a powerful imaging diagnostic tool. However, image noise in the probe-tissue contact area is difficult to remove, including both the system's imaging dead zones and noise from the contact area itself. Since skin is surface tissue, excessive noise or pressure in the contact area can affect the doctor's interpretation of tissue lesions. A common solution is to apply a thick layer of acoustic conductive adhesive to the skin surface, avoiding pressing the probe firmly into the skin. This isolates the probe surface from the skin, preventing pressure from affecting image quality. However, this approach reduces the image display area, preventing full utilization of the high-resolution image, and the starting position of tissue imaging is not at zero depth, which can complicate image interpretation for the doctor.

[0004] Existing ultrasound systems display images with a depth scale, typically starting from a fixed depth position (usually 0 cm / mm), and the starting position of the image display cannot be adjusted. A certain product has a parameter and knob for manually setting the starting depth (Depth Offset), but this requires manual operation. Summary of the Invention

[0005] To address the aforementioned technical problems, the purpose of this invention is to provide a method for automatically adjusting the initial depth of an image in an ultra-high frequency ultrasound system.

[0006] To achieve the above objectives, the present invention adopts the following technical solution:

[0007] A method for automatically adjusting the initial depth of an image in an ultra-high frequency ultrasound system includes the following steps:

[0008] Step 1: Check if the image is stable during the image scanning process;

[0009] The image scanning process is as follows:

[0010] a. Select the region of interest. Select the region with characteristic features on the image as the data for continuity check and / or select the image region according to the configuration as the data for continuity check (e.g., image region: from 25% on the left to 75% on the right, 0% on the top to 50% on the bottom).

[0011] b. Calculate the average value. Calculate the average value of each pixel and record the average value of each column of pixels. Each average value corresponds to a feature of a column.

[0012] c. Calculate the variance: Calculate the variance of all the obtained averages. The variance is the feature value of the image.

[0013] d. Compare variances. After variance calculation, each image will generate a feature value. Comparing image similarity is to compare the degree of closeness of the variances generated by the images. The stability is judged based on the size of the data variances. The degree of closeness of the variances of multiple sets of data reflects the degree of closeness of data fluctuations.

[0014] Step 2: Detect the location on the skin surface. The detection process is as follows:

[0015] 1) Employ a boundary detection algorithm;

[0016] 11) Detection is performed on the image column data based on near-field image features;

[0017] 12) Differential edge detection: The first-order difference in the direction is defined as: f(i, j+1) - f(i, j), where f represents a frame of image, i represents the column number, and j represents the row number;

[0018] Edge points are detected by calculating the extreme values ​​at locations where gray values ​​change significantly using the first derivative of the image gray level. These edge points are represented by edge intensity values, and an edge image is obtained by setting a threshold.

[0019] 2) Mark the continuous tissue boundaries;

[0020] 3) Find the highest point of the boundary and the shortest distance from the probe surface;

[0021] 4) Using the shortest distance as the offset, proceed to step 3;

[0022] Step 3: Crop the image;

[0023] 1) Display the cropped image in the window at its maximum scale;

[0024] 2) Draw a ruler based on the position of the starting image.

[0025] Preferably, in the method for automatically adjusting the initial depth of an image in an ultra-high frequency ultrasound system, step 1 involves a continuity check of consecutive image frames.

[0026] Preferably, in the method for automatically adjusting the initial depth of an image in an ultra-high frequency ultrasound system, the smaller the variance difference in step 1, the more similar the images are.

[0027] Preferably, in the method for automatically adjusting the initial depth of an image in an ultra-high frequency ultrasound system, the edge image is detected using a vertical edge detection method.

[0028] Preferably, the method for automatically adjusting the image starting depth of an ultra-high frequency ultrasound system includes a button for turning the automatic adjustment of the image starting depth on or off.

[0029] By means of the above-described solution, the present invention has at least the following advantages:

[0030] This invention enables automatic adjustment of the image starting position, which can fully utilize the display area to take advantage of high-resolution images, while removing non-tissue areas from the probe surface to the skin surface, thus ensuring complete image presentation and avoiding confusion for doctors in interpreting images.

[0031] The above description is merely an overview of the technical solution of the present invention. In order to better understand the technical means of the present invention and to implement it in accordance with the contents of the specification, the preferred embodiments of the present invention are described in detail below with reference to the accompanying drawings. Attached Figure Description

[0032] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the embodiments will be briefly introduced below. It should be understood that the following drawings only show some embodiments of the present invention and should not be regarded as a limitation on the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0033] Figure 1 This is a flowchart illustrating the present invention;

[0034] Figure 2 This is a schematic diagram of the existing original image of the present invention;

[0035] Figure 3 This is a schematic diagram of the present invention, showing only the effective area of ​​the image;

[0036] Figure 4 This is a schematic diagram of the image before processing according to the present invention;

[0037] Figure 5 This is a schematic diagram of the processed image according to the present invention. Detailed Implementation

[0038] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. The components of the embodiments of this application described and shown in the accompanying drawings can generally be arranged and designed in various different configurations.

[0039] Therefore, the following detailed description of the embodiments of this application provided in the accompanying drawings is not intended to limit the scope of the claimed application, but merely to illustrate selected embodiments of the application. All other embodiments obtained by those skilled in the art based on the embodiments of this application without inventive effort are within the scope of protection of this application.

[0040] Example

[0041] like Figures 1 to 5 As shown, a method for automatically adjusting the image initiation depth in an ultra-high frequency ultrasound system.

[0042] Includes the following steps:

[0043] Step 1: Check if the image is stable during the image scanning process;

[0044] The image scanning process is as follows:

[0045] a. Select the region of interest. Select the region with characteristic features on the image as the data for continuity check, or select the image region according to the configuration (e.g., image region: from 25% on the left to 75% on the right, and from 0% on the top to 50% on the bottom).

[0046] b. Calculate the average value. Calculate the average value of each pixel and record the average value of each column of pixels. Each average value corresponds to a feature of a column.

[0047] c. Calculate the variance: Calculate the variance of all the obtained averages. The variance is the feature value of the image.

[0048] d. Compare variances. After variance calculation, each image will generate a feature value. Comparing image similarity is to compare the degree of closeness of the variances generated by the images. The stability is judged based on the size of the data variances. The degree of closeness of the variances of multiple sets of data reflects the degree of closeness of data fluctuations.

[0049] Step 2: Detect the location on the skin surface. The detection process is as follows:

[0050] 1) Employ a boundary detection algorithm;

[0051] 11) Detection is performed on the image column data based on near-field image features;

[0052] 12) Differential edge detection: The first-order difference in the direction is defined as: f(i, j+1) - f(i, j), where f represents a frame of image, i represents the column number, and j represents the row number;

[0053] Edge points are detected by calculating the extreme values ​​at locations where gray values ​​change significantly using the first derivative of the image gray level. These edge points are represented by edge intensity values, and an edge image is obtained by setting a threshold.

[0054] 2) Mark the continuous tissue boundaries;

[0055] 3) Find the highest point of the boundary and the shortest distance from the probe surface;

[0056] 4) Using the shortest distance as the offset, proceed to step 3;

[0057] Step 3: Crop the image;

[0058] 1) Display the cropped image in the window at its maximum scale;

[0059] 2) Draw a ruler based on the starting image position.

[0060] In this invention, the region of interest is selected by the operator or the image region configured by the operator (e.g., image region: from 25% on the left to 75% on the right, and from 0% on the top to 50% on the bottom). The calculation of the average and variance are formulas known to those skilled in the art and will not be elaborated upon.

[0061] In step 1 of this invention, a continuity check of consecutive image frames is used.

[0062] In this invention, the smaller the variance difference in step 1, the more similar the images are.

[0063] In this invention, the edge image is detected using a vertical edge detection method.

[0064] The system in this invention is equipped with a button to turn on or off automatic adjustment of the image starting depth.

[0065] It should be noted that similar labels and letters in the following figures indicate similar items. Therefore, once an item is defined in one figure, it does not need to be further defined and explained in subsequent figures.

[0066] In the description of this application, it should be noted that the terms "vertical," "horizontal," "inner," and "outer," etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings, or the orientation or positional relationship commonly used when the product is in use. They are used only for the convenience of describing this application and for simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on this application. Furthermore, the terms "first," "second," etc., are used only to distinguish descriptions and should not be construed as indicating or implying relative importance.

[0067] Furthermore, terms such as "horizontal" and "vertical" do not imply that components must be absolutely horizontal or vertical, but rather that they can be slightly tilted. For example, "horizontal" simply means that its direction is more horizontal than "vertical," and does not mean that the structure must be completely horizontal, but can be slightly tilted.

[0068] In the description of this application, it should also be noted that, unless otherwise expressly specified and limited, the terms "set up," "install," "connect," and "link" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; and they can refer to the internal connection of two components. Those skilled in the art can understand the specific meaning of the above terms in this application based on the specific circumstances.

[0069] The above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the technical principles of the present invention, and these improvements and modifications should also be considered within the scope of protection of the present invention.

Claims

1. A method for automatically adjusting the image initiation depth in an ultra-high frequency ultrasound system. Its features are, Includes the following steps: Step 1: Check if the image is stable during the image scanning process; The image scanning process is as follows: a. Select the region of interest, and select regions with characteristic features on the image as data for continuity checks and / or use the configured image regions as data for continuity checks; b. Calculate the average value. Calculate the average value of each pixel and record the average value of each column of pixels. Each average value corresponds to a feature of a column. c. Calculate the variance: Calculate the variance of all the obtained averages. The variance is the feature value of the image. d. Compare variances. After variance calculation, each image will generate a feature value. Comparing image similarity is to compare the closeness of the variances generated by the images. The stability is judged based on the size of the data variances. The closeness of the variances of multiple sets of data reflects the closeness of data fluctuations. Step 2: Detect the location on the skin surface. The detection process is as follows: 1) Employ a boundary detection algorithm; 11) Detection is performed on the image column data based on near-field image features; 12) Differential edge detection: The first-order difference in the direction is defined as: f(i, j+1) - f(i, j), where f represents a frame of image, i represents the column number, and j represents the row number; Edge points are detected by calculating the extreme values ​​at locations where gray values ​​change significantly using the first derivative of the image gray level. These edge points are represented by edge intensity values, and an edge image is obtained by setting a threshold. 2) Mark the continuous tissue boundaries; 3) Find the highest point of the boundary and the shortest distance from the probe surface; 4) Using the shortest distance as the offset, proceed to step 3; Step 3: Crop the image; 1) Display the cropped image in the window at its maximum scale; 2) Draw a ruler based on the position of the starting image.

2. The method for automatically adjusting the image initiation depth of an ultra-high frequency ultrasound system according to claim 1, characterized in that: Step 1 uses a continuity check of consecutive image frames.

3. The method for automatically adjusting the image initiation depth of an ultra-high frequency ultrasound system according to claim 1, characterized in that: The smaller the variance difference in step 1, the more similar the images are.

4. The method for automatically adjusting the image initiation depth of an ultra-high frequency ultrasound system according to claim 1, characterized in that: The edge image was detected using the vertical edge detection method.

5. The method for automatically adjusting the image initiation depth of an ultra-high frequency ultrasound system according to any one of claims 1 to 4, characterized in that: The system has a button to turn automatic adjustment of image starting depth on or off.

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