A digital phantom measurement adsorption method and system based on local coordinate reconstruction

Abstract

The present disclosure relates to the technical field of image processing, and particularly relates to a digital mold body measurement adsorption method and system based on local coordinate reconstruction, the method comprising: determining a local processing window according to a measurement click coordinate; obtaining an angle point set in the local processing window; arranging the angle point set in ascending order of Euclidean distance from the measurement click coordinate, and taking the first angle point belonging to a solid pixel block as a nearest angle point; determining a target pixel block according to the nearest angle point; obtaining equivalent pixel blocks adjacent or indirectly adjacent to the target pixel block, the equivalent pixel blocks being solid pixel blocks having the same extreme value in the measurement direction and different coordinates in the direction perpendicular to the measurement direction; and taking the geometric center coordinate of the geometric shape formed by the target pixel block and the equivalent pixel blocks as a target anchor point to adsorb the measurement click coordinate. The present disclosure can realize accurate adsorption of digital mold body measurement points and ensure consistency of multiple measurements of the same geometric feature.

Description

Technical Field

[0001] This disclosure relates to the field of image processing technology, and specifically to a digital phantom measurement and adsorption method and system based on local coordinate reconstruction. Background Technology

[0002] A digital phantom is a computer-generated, idealized digital object with known precise geometric dimensions. Its function is similar to a "standard ruler" in metrology, aiming to provide an objective performance evaluation benchmark for image processing software, measurement software, or medical imaging equipment, particularly for verifying their geometric measurement accuracy and algorithm reliability. In practice, digital phantoms are often generated from standard scale diagrams by CAD software and rendered into pixelated images to simulate real imaging environments, thereby verifying the software's measurement capabilities.

[0003] Surveyors typically measure the angle of the hypotenuse by clicking on the endpoints of the model. However, when the digital model is magnified, the edges of its hypotenuse appear pixelated due to image resolution limitations. This results in the endpoint of the model being composed of multiple pixel blocks in the image, leading to a lack of a unique reference for endpoint positioning. When a user clicks on the same theoretical endpoint multiple times, the measurement point often falls on different pixel blocks.

[0004] This problem is particularly prominent in the verification of fundus OCT software with high precision requirements. Traditional methods cannot force user measurement points to be bound to a consistent physical representation point when dealing with non-horizontal / non-vertical edges. When the user clicks on an endpoint or performs an angle measurement, the landing point tends to drift between adjacent pixel blocks, resulting in a 5%-10% angle or distance deviation in multiple measurements of the same geometric feature, which seriously affects the accuracy of oblique line angle and endpoint measurements. Summary of the Invention

[0005] To address the problems in related technologies, embodiments of this disclosure provide a digital phantom measurement and adsorption method and system based on local coordinate reconstruction.

[0006] In a first aspect, embodiments of this disclosure provide a digital phantom measurement adsorption method based on local coordinate reconstruction, comprising:

[0007] In response to a measurement click operation on a specified end of a digital model, the measurement click coordinates are obtained; based on the measurement click coordinates, a local processing window is determined; each pixel block in the local processing window is analyzed as either a solid pixel block or a background pixel block; Multiple corner points of each pixel block in the local processing window are obtained to obtain a set of corner points in the local processing window; in the set of corner points, they are arranged in ascending order according to their Euclidean distance from the measured click coordinates, and the first corner point belonging to the entity pixel block is taken as the nearest corner point; Determining a target pixel block based on the nearest corner point includes: when the nearest corner point is the corner point of a single entity pixel block, taking the entity pixel block as the target pixel block; when the nearest corner point is a corner point shared by multiple entity pixel blocks, taking the entity pixel block whose pixel coordinates are extreme values ​​in the measurement direction according to the measurement direction corresponding to the specified end as the target pixel block. Obtain equivalent pixel blocks that are adjacent to or indirectly adjacent to the target pixel block. The equivalent pixel blocks are entity pixel blocks that have the same extreme value as the target pixel block in the measurement direction but have different coordinates in the direction perpendicular to the measurement direction. The geometric center coordinates of the geometric shape formed by the target pixel block and the equivalent pixel block are used as the target anchor point, and the measurement click coordinates are snapped to the target anchor point.

[0008] According to embodiments of this disclosure, determining the local processing window based on the measured click coordinates includes: The local processing window is determined by using the measured click coordinates as the center and a preset size as the window size.

[0009] According to embodiments of this disclosure, after determining the target pixel block based on the nearest corner point, the method further includes: Centered on the target pixel block, the recognition extension area is determined according to the preset pixel length and pixel width; Obtain the pixel coordinates of each entity pixel block in the recognition extended region in the measurement direction to obtain the pixel coordinate set of the recognition extended region; Determine whether the pixel coordinates of the target pixel block in the measurement direction are extreme values ​​in the set of pixel coordinates; If so, then maintain the target pixel block; If not, then redetermine the nearest corner point.

[0010] According to embodiments of this disclosure, the method further includes: resolving each pixel block in the local processing window into a physical pixel block or a background pixel block using an attribute classification function.

[0011] According to embodiments of this disclosure, determining the target pixel block based on the nearest corner point further includes: When the nearest corner point is a corner point shared by multiple entity pixel blocks, if the number of entity pixel blocks whose pixel coordinates are extreme values ​​in the measurement direction exceeds one, then one entity pixel block is randomly selected from the entity pixel blocks whose pixel coordinates are extreme values ​​in the measurement direction as the target pixel block.

[0012] Secondly, embodiments of this disclosure provide a digital phantom measurement adsorption system, comprising: The corner mapping module is configured to respond to a measurement click operation on a specified end of a digital model, obtain the measurement click coordinates; determine a local processing window based on the measurement click coordinates; parse each pixel block in the local processing window as either a solid pixel block or a background pixel block; obtain multiple corner points of each pixel block in the local processing window to obtain a set of corner points in the local processing window; in the set of corner points, arrange them in ascending order according to their Euclidean distance from the measurement click coordinates, and take the first corner point belonging to a solid pixel block as the nearest corner point; A pixel block recognition module is configured to determine a target pixel block based on the nearest corner point, including: when the nearest corner point is the corner point of a single entity pixel block, taking the entity pixel block as the target pixel block; when the nearest corner point is a corner point shared by multiple entity pixel blocks, taking the entity pixel block whose pixel coordinates are extreme values ​​in the measurement direction as the target pixel block according to the measurement direction corresponding to the specified end. The center-of-gravity stacking step module is configured to acquire equivalent pixel blocks that are adjacent to or indirectly adjacent to the target pixel block. The equivalent pixel blocks are entity pixel blocks that have the same extreme value as the target pixel block in the measurement direction but have different coordinates in the direction perpendicular to the measurement direction. The geometric center coordinates of the geometric shape formed by the target pixel block and the equivalent pixel blocks are used as the target anchor point. The coordinate snapping module is configured to snap the measured click coordinates to the target anchor point.

[0013] According to embodiments of this disclosure, the system further includes: a verification module; The verification module is configured to: determine an extended recognition region centered on the target pixel block, according to a preset pixel length and pixel width; obtain the pixel coordinates of each entity pixel block in the extended recognition region in the measurement direction, thereby obtaining a set of pixel coordinates of the extended recognition region; determine whether the pixel coordinates of the target pixel block in the measurement direction are extreme values ​​in the set of pixel coordinates; if yes, maintain the target pixel block; if no, re-determine the nearest corner point.

[0014] According to embodiments of this disclosure, the pixel block recognition module is further configured to: When the nearest corner point is a corner point shared by multiple entity pixel blocks, if the number of entity pixel blocks whose pixel coordinates are extreme values ​​in the measurement direction exceeds one, then one entity pixel block is randomly selected from the entity pixel blocks whose pixel coordinates are extreme values ​​in the measurement direction as the target pixel block.

[0015] Thirdly, embodiments of this disclosure provide a computer-readable storage medium having computer instructions stored thereon that, when executed by a processor, implement the method as described in any of the first aspects.

[0016] Fourthly, embodiments of this disclosure provide a computer program product including computer instructions that, when executed by a processor, implement the method as described in any of the first aspects.

[0017] This disclosure obtains measurement click coordinates in response to a measurement click operation on a specified end of a digital model; determines a local processing window based on the measurement click coordinates; parses each pixel block in the local processing window as either a solid pixel block or a background pixel block; acquires multiple corner points of each pixel block in the local processing window to obtain a set of corner points in the local processing window; arranges the corner points in the set in ascending order according to their Euclidean distance from the measurement click coordinates, and takes the first corner point belonging to a solid pixel block as the nearest corner point; determines a target pixel block based on the nearest corner point; acquires equivalent pixel blocks that are adjacent or indirectly adjacent to the target pixel block, wherein the equivalent pixel blocks are solid pixel blocks that have the same extreme value as the target pixel block in the measurement direction but have different coordinates in a direction perpendicular to the measurement direction; and uses the geometric center coordinates of the geometric shape formed by the target pixel block and the equivalent pixel blocks as a target anchor point, and snaps the measurement click coordinates to the target anchor point.

[0018] When measuring the ends of a digital phantom, this disclosure does not limit itself to the pixel block closest to the measurement point, but expands the point map of the pixel block and automatically snaps the endpoint coordinates based on the expanded geometric center, thereby providing targeted interactive correction for the measurement of the digital phantom endpoints and ensuring the consistency of the measurement points.

[0019] This disclosure enables precise adsorption of measurement points on digital phantoms, ensuring consistency in multiple measurements of the same geometric feature. It is applicable to image measurement verification platforms, medical imaging software quality control systems, and precision measurement scenarios for CAD rendered images. For example, when using verified image measurement software to measure OCT images (which typically have multiple line segments marked on them), it enables precise measurement of line segments on the image.

[0020] It should be understood that the above general description and the following detailed description are exemplary and explanatory only, and are not intended to limit this disclosure. Attached Figure Description

[0021] Other features, objects, and advantages of this disclosure will become more apparent from the following detailed description of non-limiting embodiments, taken in conjunction with the accompanying drawings. In the drawings: Figure 1This diagram illustrates a digital phantom used in the digital phantom measurement adsorption method according to an embodiment of the present disclosure. Figure 2 Show Figure 1 The example shown is a magnified illustration of the digital phantom. Figure 3 A flowchart is shown for a digital phantom measurement adsorption method based on local coordinate reconstruction according to an embodiment of the present disclosure; Figure 4 This diagram illustrates geometric endpoints and common edge corners in a digital phantom used in an embodiment of this disclosure. Figure 5 A schematic diagram showing the determination of a target anchor point using a digital phantom measurement adsorption method according to an embodiment of the present disclosure is shown. Figure 6 A schematic diagram of a dummy endpoint in a digital phantom used in an embodiment of this disclosure is shown; Figure 7 A complete flowchart of a digital phantom measurement adsorption method according to an embodiment of the present disclosure is shown; Figure 8 A structural block diagram of a digital phantom measurement adsorption system according to an embodiment of the present disclosure is shown. Detailed Implementation

[0022] In the following, exemplary embodiments of the present disclosure will be described in detail with reference to the accompanying drawings to enable those skilled in the art to readily implement them. Furthermore, for clarity, portions unrelated to the description of exemplary embodiments have been omitted from the drawings.

[0023] In this disclosure, it should be understood that terms such as “comprising” or “having” are intended to indicate the presence of features, figures, steps, behaviors, components, parts or combinations thereof disclosed in this specification, and are not intended to exclude the possibility of the presence or addition of one or more other features, figures, steps, behaviors, components, parts or combinations thereof.

[0024] It should also be noted that, unless otherwise specified, the embodiments and features described in this disclosure can be combined with each other. This disclosure will now be described in detail with reference to the accompanying drawings and embodiments.

[0025] As mentioned earlier, traditional methods cannot force user measurement points to a consistent physical representation point when dealing with non-horizontal / non-vertical edges. When a user clicks on an endpoint or performs an angle measurement, the landing point tends to drift between adjacent pixel blocks, resulting in a 5-10% angle or distance deviation in multiple measurements of the same geometric feature, which seriously affects the accuracy of oblique line angle and endpoint measurements.

[0026] While existing bilinear interpolation edge smoothing techniques can reduce visual jaggedness by linearly compensating the original pixels and thus smooth the transition edges, they do not lock the true geometric boundaries at the coordinate level and still cannot guarantee the consistency of click points during measurement interactions.

[0027] This disclosure provides a digital phantom measurement and adsorption method based on local coordinate reconstruction, comprising: obtaining measurement click coordinates in response to a measurement click operation on a specified end of the digital phantom; determining a local processing window based on the measurement click coordinates; resolving each pixel block in the local processing window to be either a solid pixel block or a background pixel block; obtaining multiple corner points of each pixel block in the local processing window to obtain a set of corner points in the local processing window; sorting the corner point set in ascending order according to their Euclidean distance from the measurement click coordinates, and taking the first corner point belonging to a solid pixel block as the nearest corner point; determining a target pixel block based on the nearest corner point, including: determining the target pixel block based on the nearest corner point as the corner of a solid pixel block. When a point is selected, the physical pixel block is taken as the target pixel block. When the nearest corner point is a corner point shared by multiple physical pixel blocks, the physical pixel block with an extreme pixel coordinate in the measurement direction is taken as the target pixel block according to the measurement direction corresponding to the specified end. Equivalent pixel blocks that are adjacent to or indirectly adjacent to the target pixel block are obtained. The equivalent pixel blocks are physical pixel blocks that have the same extreme value in the measurement direction as the target pixel block but have different coordinates in the direction perpendicular to the measurement direction. The geometric center coordinates of the geometric shape formed by the target pixel block and the equivalent pixel blocks are taken as the target anchor point, and the measurement click coordinates are snapped to the target anchor point.

[0028] This disclosure enables precise attachment of measurement points on digital phantoms, ensuring consistency in multiple measurements of the same geometric feature. It solves the problem of lacking a real-time point correction mechanism for interactive measurements, reducing geometric measurement errors caused by pixel discretization.

[0029] Figure 1 This diagram illustrates a digital phantom used in the digital phantom measurement adsorption method according to an embodiment of the present disclosure.

[0030] In this disclosure, the digital model includes non-horizontal or non-vertical oblique edges, such as triangles with hypotenuses, line segments with set tilt angles, and so on.

[0031] by Figure 1The example shown illustrates this disclosure. The digital phantom is a geometric shape similar to a set square, consisting of a horizontal base and a hypotenuse, with the hypotenuse forming a 30-degree angle with the horizontal base. The hypotenuse comprises multiple diagonal lines, and the base comprises multiple horizontal and vertical line segments. These diagonal lines can serve as the core measurement object of this disclosure, used to verify the phantom's adhesion capability to the endpoints of the digital phantom.

[0032] Figure 2 Show Figure 1 The example shown is a magnified illustration of a digital phantom; as shown Figure 2 As shown, when the digital model is magnified, pixel blocks with an aspect ratio of 2:1 appear in the end region within the red box. This pixel pattern is the root cause of positioning errors when geometrically measuring this endpoint. That is, when performing multiple measurement clicks on the end shown in the red box, the measured click coordinates obtained each time are not necessarily consistent.

[0033] The inventors noticed this problem, especially in the verification of fundus OCT (Optical Coherence Tomography) software, where the high precision required directly affects the reliability of diagnostic conclusions due to the measurement deviation at the endpoints caused by pixel block morphology. Therefore, a method that can uniformly adsorb during endpoint measurements is needed to ensure the accuracy and consistency of measurement results.

[0034] Figure 3 A flowchart illustrating a digital phantom measurement adsorption method based on local coordinate reconstruction according to an embodiment of the present disclosure is shown. Figure 3 As shown, the method includes the following steps S301 to S305.

[0035] In step S301, in response to a measurement click operation on a specified end of the digital model, the measurement click coordinates are obtained; based on the measurement click coordinates, a local processing window is determined; and each pixel block in the local processing window is analyzed as either a solid pixel block or a background pixel block.

[0036] In this disclosure, the designated end is the endpoint of any non-horizontal or non-vertical edge in the digital model. Compared with horizontal or vertical edges, since the designated end is the endpoint of a diagonal line, such a diagonal end will present a stepped jagged edge under the limitation of image resolution, and its end lacks a clear single pixel representation in the image.

[0037] According to embodiments of this disclosure, the measured click coordinates are used as the center, and a preset size is used as the window size to determine the local processing window. The local processing window can be rectangular, square, etc.; the preset size can be set according to user needs, and this disclosure does not impose any restrictions on it.

[0038] Existing image processing technologies mostly employ a global processing model. For example, image scaling requires pixel resampling of the entire image (using algorithms such as bilinear interpolation), which leads to significant computational latency in real-time interactive measurement scenarios. However, in digital phantom verification processes, users frequently need to perform image zooming and endpoint clicks, requiring millisecond-level response times. The global processing model struggles to meet the real-time demands of this dynamic interaction.

[0039] Therefore, this disclosure abandons the global processing approach and only performs fine-grained processing on the user-clicked area, thereby significantly reducing computational latency and effectively improving the real-time performance and smoothness of interactive measurements.

[0040] According to embodiments of this disclosure, the method further includes: resolving each pixel block in the local processing window into a physical pixel block or a background pixel block using an attribute classification function.

[0041] That is, for any pixel block in the local processing window The analysis treats each pixel block as a basic unit with a defined geometric boundary, and then uses an attribute classification function. Each pixel block is marked to determine whether it belongs to a background pixel block or a physical pixel block, where 0 represents a background pixel block and 1 represents a physical pixel block.

[0042] In step S302, multiple corner points of each pixel block in the local processing window are obtained to obtain a set of corner points in the local processing window; in the set of corner points, they are arranged in ascending order according to their Euclidean distance from the measured click coordinates, and the first corner point belonging to the entity pixel block is taken as the nearest corner point.

[0043] A corner expansion operation is performed on all pixel blocks in the local processing window, that is, the coordinates of the four corner points of each pixel block are extracted and mapped to logical points to form a corner point set. : .

[0044] A local high-density sub-pixel set is constructed by using a corner point set method to improve the resolution of jagged edges near the specified end in geometric analysis.

[0045] Furthermore, after obtaining the set of corner points, they are sorted in ascending order according to their Euclidean distance from the measured click coordinates, and the first corner point belonging to the entity pixel block is taken as the nearest corner point.

[0046] The following specific example illustrates the calculation of the nearest corner point: For the aforementioned local processing area, target anchor point (nearest corner point) locking is performed, specifically as follows: Define the objective functionJ The coordinates of the candidate points are: The measured click coordinates are objective function J The Euclidean distance between the candidate point coordinates and the measured click coordinates; Set of corner points All corner points in the middle according to J Arrange the values ​​in ascending order to obtain the corner queue Q; A greedy strategy of first-to-middle termination is adopted, sequentially checking all corner points in the corner point queue Q, while simultaneously executing the decision condition. That is, the selected corner point must belong to the entity pixel block; once a corner point that meets the judgment condition is found, the corner point is taken as the nearest corner point.

[0047] In step S303, determining the target pixel block based on the nearest corner point includes: when the nearest corner point is the corner point of a single entity pixel block, the entity pixel block is taken as the target pixel block; when the nearest corner point is a corner point shared by multiple entity pixel blocks, the entity pixel block whose pixel coordinates are extreme values ​​in the measurement direction is taken as the target pixel block according to the measurement direction corresponding to the specified end.

[0048] Since the local processing area is the region near the specified end, the nearest corner point in this region can be either a geometric endpoint or a normal edge corner point.

[0049] Figure 4 This diagram illustrates geometric endpoints and common edge corners in a digital phantom used in an embodiment of the present disclosure.

[0050] like Figure 4 As shown, for the local processing area of ​​the digital model: the geometric endpoint is a fully exposed protruding tip in the pixel grid, which belongs to only one entity pixel block, as shown by the red corner point in the figure; the ordinary edge corner point, the corresponding pixel edge must extend horizontally or vertically on the boundary line of the digital model, so that the ordinary edge corner point is shared by multiple entity pixel blocks, as shown by the blue corner point in the figure.

[0051] For geometric endpoints, their physical pixel blocks are used as target pixel blocks.

[0052] For ordinary edge corners, it is necessary to determine the pixel coordinates of multiple entity pixel blocks sharing the ordinary edge corner in the measurement direction according to the measurement direction corresponding to the specified end, and take the entity pixel block with the extreme value (maximum or minimum value) of the pixel coordinates in the measurement direction as the target pixel block.

[0053] The following uses the specified ends as the top, bottom, leftmost, and rightmost points as examples to illustrate the measurement direction and pixel coordinate extreme values ​​of this disclosure: When the measurement task to be performed by the measurement personnel is to measure the top of the digital model, the measurement direction corresponding to the specified end is the upper side of the vertical y-axis, and the extreme value of the pixel coordinate corresponding to the measurement direction is the minimum value of the y-axis.

[0054] When the measurement task to be performed by the measurement personnel is to measure the bottom of the digital model, the measurement direction corresponding to the specified end is the lower side of the vertical direction y, and the extreme value of the pixel coordinate corresponding to the measurement direction is the maximum value of the y-axis.

[0055] When the measurement task to be performed by the measurement personnel is to measure the leftmost side of the digital phantom, the measurement direction corresponding to the specified end is the left side of the horizontal x-axis, and the extreme value of the pixel coordinate corresponding to the measurement direction is the minimum value of the x-axis.

[0056] When the measurement task to be performed by the measurement personnel is to measure the rightmost side of the digital phantom, the measurement direction corresponding to the specified end is the right side of the horizontal x-axis, and the extreme value of the pixel coordinate corresponding to the measurement direction is the maximum value of the x-axis.

[0057] It is known that the coordinates of a pixel block can be its row and column numbers, or the center point of the pixel block, but are not limited to these.

[0058] In this disclosure, the target pixel block is determined from among multiple entity pixel blocks to which a common edge corner point belongs, based on the extreme values ​​of the pixel coordinates corresponding to the measurement direction.

[0059] According to an embodiment of this disclosure, when the nearest corner point is a corner point shared by multiple entity pixel blocks, if the number of entity pixel blocks whose pixel coordinates are extreme values ​​in the measurement direction exceeds one, one entity pixel block is randomly selected from the entity pixel blocks whose pixel coordinates are extreme values ​​in the measurement direction as the target pixel block.

[0060] In step S304, equivalent pixel blocks that are adjacent to or indirectly adjacent to the target pixel block are obtained. The equivalent pixel blocks are entity pixel blocks that have the same extreme value as the target pixel block in the measurement direction but have different coordinates in the direction perpendicular to the measurement direction.

[0061] For example, if the measurement direction is the upper side of the vertical direction y, after determining the target pixel block, the pixel block that has the same y-axis coordinate value but a different x-axis coordinate value as the target pixel block is considered among the entity pixel blocks that are adjacent or indirectly adjacent to the target pixel block (adjacent through one or more entity pixel blocks).

[0062] In step S305, the geometric center coordinates of the geometric shape formed by the target pixel block and the equivalent pixel block are used as the target anchor point, and the measurement click coordinates are snapped to the target anchor point.

[0063] Figure 5 This diagram illustrates the determination of target anchor points using a digital phantom measurement and adsorption method according to an embodiment of the present disclosure; as shown. Figure 5 As shown, the target pixel block has an equivalent pixel block, such that the target pixel block and the corresponding equivalent pixel block form a rectangle. The geometric center coordinates of this rectangle are the target anchor point, as shown by the blue dot in the figure.

[0064] This disclosure provides a targeted interactive correction scheme for digital phantom endpoint measurement. This scheme can aggregate multiple measurements of the same endpoint to the same target anchor point, thereby ensuring high consistency of measurement points and significantly improving the geometric measurement accuracy of image measurement software when processing oblique line edges. Image measurement software validated by this disclosed scheme can accurately measure OCT images containing multiple line segment markers.

[0065] In a special case where the angle of the diagonal edge is 45 degrees, false endpoints may occur. Figure 6 This diagram illustrates a dummy endpoint in a digital phantom used in an embodiment of the present disclosure.

[0066] like Figure 6 As shown, the digital model is a diagonal line segment with an angle of 45 degrees. Figure 6 The two red corner points shown are both geometric endpoints, each belonging to only one entity pixel block. However, the lower red corner point is clearly not an endpoint of the line segment. To avoid misidentifying false endpoints as geometric endpoints, this disclosure, after determining the target pixel block based on the nearest corner point, further includes: determining an identification extension region centered on the target pixel block according to a preset pixel length and pixel width; obtaining the pixel coordinates of each entity pixel block in the identification extension region in the measurement direction to obtain the pixel coordinate set of the identification extension region; determining whether the pixel coordinates of the target pixel block in the measurement direction are extreme values ​​in the pixel coordinate set; if yes, maintaining the target pixel block; if no, re-determining the nearest corner point.

[0067] Assuming the target pixel block is the center, and the distance is 5... The size of the 5-area region is used to determine the recognition extension area. Assuming that the measurement direction is the upper side of the vertical y-direction, the pixel coordinates of each entity pixel block in the recognition extension area in the vertical y-direction are obtained to obtain the pixel coordinate set. It is then determined whether the pixel coordinate value of the target pixel block is an extreme value in the pixel coordinate set. If not, the nearest corner point needs to be re-determined.

[0068] Figure 7 A complete flowchart of a digital phantom measurement adsorption method according to an embodiment of the present disclosure is shown.

[0069] like Figure 7 As shown, for a digital phantom loaded in the image measurement software, the measurement task is to measure the top of the digital phantom. The measurement operator obtains the measurement click coordinates by manually clicking near the endpoint (measuring the click point). Based on these coordinates, the red point is determined as the nearest corner point, and the pixel block shown in the orange area is then identified as the target pixel block. Using this target pixel block as the center, a range of 5... The pixel region of 5 is used as the recognition extension region, and the vertical pixel coordinate value of the target pixel block is determined to be the extreme value; the target pixel block has an equivalent pixel block, and the two together form the rectangle shown in the green area in the figure. The geometric center of the rectangle is used as the final target anchor point.

[0070] Finally, the measurement click coordinates at the gray pixel block were snapped to the target anchor point, realizing the automatic snapping of endpoint measurements in the digital model.

[0071] Figure 8 A structural block diagram of a digital phantom measurement adsorption system according to an embodiment of the present disclosure is shown.

[0072] like Figure 8 As shown, the digital phantom measurement and adsorption system 800 includes a corner mapping module 810, a pixel block recognition module 820, a centroid superposition step size module 830, and a coordinate adsorption module 840.

[0073] The corner mapping module 810 is configured to, in response to a measurement click operation on a specified end of a digital model, obtain measurement click coordinates; determine a local processing window based on the measurement click coordinates; parse each pixel block in the local processing window as either a solid pixel block or a background pixel block; obtain multiple corner points of each pixel block in the local processing window to obtain a set of corner points in the local processing window; in the set of corner points, arrange them in ascending order according to their Euclidean distance from the measurement click coordinates, and take the first corner point belonging to a solid pixel block as the nearest corner point.

[0074] The pixel block recognition module 820 is configured to determine a target pixel block based on the nearest corner point, including: when the nearest corner point is the corner point of a single entity pixel block, taking the entity pixel block as the target pixel block; when the nearest corner point is a corner point shared by multiple entity pixel blocks, taking the entity pixel block whose pixel coordinates are extreme values ​​in the measurement direction according to the measurement direction corresponding to the specified end as the target pixel block.

[0075] The centroid superposition step module 830 is configured to acquire equivalent pixel blocks that are adjacent to or indirectly adjacent to the target pixel block. The equivalent pixel blocks are entity pixel blocks that have the same extreme value as the target pixel block in the measurement direction but have different coordinates in the direction perpendicular to the measurement direction. The geometric center coordinates of the geometric shape formed by the target pixel block and the equivalent pixel blocks are used as the target anchor point.

[0076] The coordinate snapping module 840 is configured to snap the measured click coordinates to the target anchor point.

[0077] According to an embodiment of this disclosure, the system further includes: a verification module; the verification module is configured to: determine an identification extension region centered on the target pixel block, according to a preset pixel length and pixel width; obtain the pixel coordinates of each entity pixel block in the identification extension region in the measurement direction, thereby obtaining a set of pixel coordinates of the identification extension region; determine whether the pixel coordinates of the target pixel block in the measurement direction are extreme values ​​in the set of pixel coordinates; if yes, maintain the target pixel block; if no, re-determine the nearest corner point.

[0078] According to an embodiment of this disclosure, the pixel block identification module 820 is further configured to: when the nearest corner point is a corner point shared by multiple entity pixel blocks, if the number of entity pixel blocks whose pixel coordinates are extreme values ​​in the measurement direction exceeds one, select one entity pixel block from the entity pixel blocks whose pixel coordinates are extreme values ​​in the measurement direction as the target pixel block.

[0079] In particular, according to embodiments of this disclosure, the methods described above can be implemented as computer software programs. For example, embodiments of this disclosure include a computer program product comprising a computer program tangibly embodied on a machine-readable medium, the computer program containing program code for performing the methods described above. In such embodiments, the computer program can be downloaded and installed from a network via a communication component, and / or installed from a removable medium.

[0080] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of this disclosure. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, may be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.

[0081] The units or modules described in the embodiments of this disclosure can be implemented in software or programmable hardware. The described units or modules can also be located in a processor, and the names of these units or modules do not necessarily constitute a limitation on the unit or module itself.

[0082] In another aspect, this disclosure also provides a computer-readable storage medium, which may be a computer-readable storage medium included in the electronic device or computer system described above; or it may be a standalone computer-readable storage medium not assembled into a device. The computer-readable storage medium stores one or more programs, which are used by one or more processors to perform the methods described in this disclosure.

[0083] The above description is merely a preferred embodiment of this disclosure and an explanation of the technical principles employed. Those skilled in the art should understand that the scope of the invention involved in this disclosure is not limited to technical solutions formed by specific combinations of the above-described technical features, but should also cover other technical solutions formed by arbitrary combinations of the above-described technical features or their equivalents without departing from the inventive concept. For example, technical solutions formed by substituting the above-described features with (but not limited to) technical features disclosed in this disclosure that have similar functions.

Claims

1. A digital phantom measurement and adsorption method based on local coordinate reconstruction, characterized in that, include: In response to a measurement click operation on a specified end of a digital model, the measurement click coordinates are obtained; based on the measurement click coordinates, a local processing window is determined; each pixel block in the local processing window is analyzed as either a solid pixel block or a background pixel block; Multiple corner points of each pixel block in the local processing window are obtained to obtain a set of corner points in the local processing window; in the set of corner points, they are arranged in ascending order according to their Euclidean distance from the measured click coordinates, and the first corner point belonging to the entity pixel block is taken as the nearest corner point; Determining a target pixel block based on the nearest corner point includes: when the nearest corner point is the corner point of a single entity pixel block, taking the entity pixel block as the target pixel block; when the nearest corner point is a corner point shared by multiple entity pixel blocks, taking the entity pixel block whose pixel coordinates are extreme values ​​in the measurement direction according to the measurement direction corresponding to the specified end as the target pixel block. Obtain equivalent pixel blocks that are adjacent to or indirectly adjacent to the target pixel block. The equivalent pixel blocks are entity pixel blocks that have the same extreme value as the target pixel block in the measurement direction but have different coordinates in the direction perpendicular to the measurement direction. The geometric center coordinates of the geometric shape formed by the target pixel block and the equivalent pixel block are used as the target anchor point, and the measurement click coordinates are snapped to the target anchor point.

2. The digital phantom measurement adsorption method according to claim 1, characterized in that, The step of determining the local processing window based on the measured click coordinates includes: The local processing window is determined by using the measured click coordinates as the center and a preset size as the window size.

3. The digital phantom measurement adsorption method according to claim 1, characterized in that, After determining the target pixel block based on the nearest corner point, the method further includes: Centered on the target pixel block, the recognition extension area is determined according to the preset pixel length and pixel width; Obtain the pixel coordinates of each entity pixel block in the recognition extended region in the measurement direction to obtain the pixel coordinate set of the recognition extended region; Determine whether the pixel coordinates of the target pixel block in the measurement direction are extreme values ​​in the set of pixel coordinates; If so, then maintain the target pixel block; If not, then redetermine the nearest corner point.

4. The digital phantom measurement adsorption method according to claim 1, characterized in that, The method further includes: resolving each pixel block in the local processing window into a physical pixel block or a background pixel block using an attribute classification function.

5. The digital phantom measurement adsorption method according to claim 1, characterized in that, The step of determining the target pixel block based on the nearest corner point further includes: When the nearest corner point is a corner point shared by multiple entity pixel blocks, if the number of entity pixel blocks whose pixel coordinates are extreme values ​​in the measurement direction exceeds one, then one entity pixel block is randomly selected from the entity pixel blocks whose pixel coordinates are extreme values ​​in the measurement direction as the target pixel block.

6. A digital phantom measurement adsorption system, characterized in that, include: The corner mapping module is configured to respond to a measurement click operation on a specified end of a digital model, obtain the measurement click coordinates; determine a local processing window based on the measurement click coordinates; parse each pixel block in the local processing window as either a solid pixel block or a background pixel block; obtain multiple corner points of each pixel block in the local processing window to obtain a set of corner points in the local processing window; in the set of corner points, arrange them in ascending order according to their Euclidean distance from the measurement click coordinates, and take the first corner point belonging to a solid pixel block as the nearest corner point; A pixel block recognition module is configured to determine a target pixel block based on the nearest corner point, including: when the nearest corner point is the corner point of a single entity pixel block, taking the entity pixel block as the target pixel block; when the nearest corner point is a corner point shared by multiple entity pixel blocks, taking the entity pixel block whose pixel coordinates are extreme values ​​in the measurement direction as the target pixel block according to the measurement direction corresponding to the specified end. The center-of-gravity stacking step module is configured to acquire equivalent pixel blocks that are adjacent to or indirectly adjacent to the target pixel block. The equivalent pixel blocks are entity pixel blocks that have the same extreme value as the target pixel block in the measurement direction but have different coordinates in the direction perpendicular to the measurement direction. The geometric center coordinates of the geometric shape formed by the target pixel block and the equivalent pixel blocks are used as the target anchor point. The coordinate snapping module is configured to snap the measured click coordinates to the target anchor point.

7. The digital phantom measurement adsorption system according to claim 6, characterized in that, The system also includes: a verification module; The verification module is configured to: determine an extended recognition region centered on the target pixel block, according to a preset pixel length and pixel width; obtain the pixel coordinates of each entity pixel block in the extended recognition region in the measurement direction, thereby obtaining a set of pixel coordinates of the extended recognition region; determine whether the pixel coordinates of the target pixel block in the measurement direction are extreme values ​​in the set of pixel coordinates; if yes, maintain the target pixel block; if no, re-determine the nearest corner point.

8. The digital phantom measurement adsorption system according to claim 6, characterized in that, The pixel block recognition module is also configured as follows: When the nearest corner point is a corner point shared by multiple entity pixel blocks, if the number of entity pixel blocks whose pixel coordinates are extreme values ​​in the measurement direction exceeds one, then one entity pixel block is randomly selected from the entity pixel blocks whose pixel coordinates are extreme values ​​in the measurement direction as the target pixel block.

9. A computer-readable storage medium storing computer instructions thereon, characterized in that, When the computer instructions are executed by the processor, they implement the method of any one of claims 1 to 5.

10. A computer program product, characterized in that, It includes computer instructions that, when executed by a processor, implement the method of any one of claims 1 to 5.

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