Parameter measurement system and method based on external auditory canal three-dimensional reconstruction

Abstract

The invention discloses a parameter measurement system and method based on external auditory canal three-dimensional reconstruction, and relates to the technical field of parameter measurement, and the system comprises a scanning module which is used for obtaining a temporal bone scanning image; the boundary extraction module is used for performing external auditory canal boundary extraction on the temporal bone scanning image to obtain external auditory canal boundary features; the model building module is used for building an external auditory canal three-dimensional model according to a moving cube algorithm based on external auditory canal boundary features; the interception module is used for performing dynamic interception according to the external auditory canal three-dimensional model to obtain an external auditory canal continuous cross section; and the map construction module is used for carrying out multi-dimensional measurement analysis and constructing an external auditory canal parameter mapping map. The technical problems that in the prior art, external auditory canal morphological analysis is low in precision and lacks continuity and three-dimensional structure information are solved, and the technical effect of high-precision, continuous and visual external auditory canal three-dimensional parameter measurement and mapping is achieved by introducing threshold value self-adaptive segmentation, moving cube three-dimensional modeling and multi-dimensional parameter analysis.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of parameter measurement, in particular to a parameter measurement system and method based on three-dimensional reconstruction of an external auditory canal. BACKGROUND

[0002] External auditory canal morphology measurement is of great significance in accurately describing individual structural characteristics. Traditional methods are mostly based on two-dimensional images for observation, which is difficult to reflect the three-dimensional spatial morphology of the external auditory canal. In the image processing process, the boundary extraction accuracy is not high, which affects the construction quality of the subsequent three-dimensional model. The constructed structural information is scattered, and the cross-sectional data is discontinuously distributed, which cannot form a complete three-dimensional morphology expression, limiting the comprehensive quantification and parameter analysis of the morphological characteristics. SUMMARY

[0003] The present application provides a parameter measurement system and method based on three-dimensional reconstruction of an external auditory canal, which is used to solve the technical problems of low accuracy, lack of continuity and three-dimensional structural information in the prior art.

[0004] In view of the above problems, the present application provides a parameter measurement system and method based on three-dimensional reconstruction of an external auditory canal.

[0005] In a first aspect of the present application, a parameter measurement system based on three-dimensional reconstruction of an external auditory canal is provided, which comprises: a scanning module for acquiring a temporal bone scan image; a boundary extraction module for extracting the boundary of the external auditory canal according to a threshold adaptive segmentation algorithm on the temporal bone scan image to obtain the boundary features of the external auditory canal; a model establishment module for constructing a three-dimensional model of the external auditory canal based on the boundary features of the external auditory canal according to a moving cube algorithm; a cutting module for dynamically cutting according to the three-dimensional model of the external auditory canal to obtain continuous cross sections of the external auditory canal; and a atlas construction module for constructing a parameter mapping atlas of the external auditory canal according to multi-dimensional measurement analysis of the continuous cross sections of the external auditory canal.

[0006] In a second aspect of the present application, a parameter measurement method based on three-dimensional reconstruction of an external auditory canal is provided, which comprises: acquiring a temporal bone scan image; extracting the boundary of the external auditory canal according to a threshold adaptive segmentation algorithm on the temporal bone scan image to obtain the boundary features of the external auditory canal; constructing a three-dimensional model of the external auditory canal based on the boundary features of the external auditory canal according to a moving cube algorithm; dynamically cutting according to the three-dimensional model of the external auditory canal to obtain continuous cross sections of the external auditory canal; and constructing a parameter mapping atlas of the external auditory canal according to multi-dimensional measurement analysis of the continuous cross sections of the external auditory canal.

[0007] One or more technical solutions provided in the present application have at least the following technical effects or advantages: The application obtains a temporal bone scan image; extracts an external auditory canal boundary from the temporal bone scan image according to a threshold adaptive segmentation algorithm to obtain an external auditory canal boundary feature; constructs an external auditory canal three-dimensional model based on the external auditory canal boundary feature according to a moving cube algorithm; dynamically intercepts according to the external auditory canal three-dimensional model to obtain an external auditory canal continuous cross section; and performs multi-dimensional measurement analysis according to the external auditory canal continuous cross section to construct an external auditory canal parameter mapping atlas. The application solves the technical problems of low external auditory canal shape analysis precision, lack of continuity and three-dimensional structure information in the prior art, and achieves the technical effects of high-precision, continuous and visual external auditory canal three-dimensional parameter measurement and mapping by introducing threshold adaptive segmentation, moving cube three-dimensional modeling and multi-dimensional parameter analysis. BRIEF DESCRIPTION OF DRAWINGS

[0008] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings needed in the embodiment description will be briefly introduced. Obviously, the drawings in the following description are only some embodiments of the present application, and other drawings can be obtained by those skilled in the art without creative labor.

[0009] Figure 1 The structure schematic diagram of the parameter measurement system based on external auditory canal three-dimensional reconstruction provided by the present application is shown in the figure. Figure 2 The flowchart of the parameter measurement method based on external auditory canal three-dimensional reconstruction provided by the present application is shown in the figure.

[0010] The figure legend is as follows: scanning module 11, boundary extraction module 12, model establishment module 13, intercepting module 14, atlas construction module 15. DETAILED DESCRIPTION

[0011] The present application provides a parameter measurement system and method based on external auditory canal three-dimensional reconstruction, which solves the technical problems of low external auditory canal shape analysis precision, lack of continuity and three-dimensional structure information in the prior art, and achieves the technical effects of high-precision, continuous and visual external auditory canal three-dimensional parameter measurement and mapping by introducing threshold adaptive segmentation, moving cube three-dimensional modeling and multi-dimensional parameter analysis.

[0012] The technical solutions in the embodiments of the present application will be described clearly and completely in combination with the drawings in the embodiments of the present application. Obviously, the described embodiments are only some embodiments of the present application, not all embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor are within the scope of protection of the present application.

[0013] It should be noted that any variation of the terms "comprising" and "having" is intended to cover non-exclusive inclusion, for example, a process, method, system, product, or server that includes a series of steps or units is not necessarily limited to those steps or units that are explicitly listed, but may include other steps or modules that are not explicitly listed or that are inherent to such processes, methods, products, or devices.

[0014] Example 1, as Figure 1 As shown, this application embodiment provides a parameter measurement system based on three-dimensional reconstruction of the external auditory canal, the system comprising: Scanning module 11 is used to acquire temporal bone scan images.

[0015] In this embodiment, the scanning module 11 acquires a temporal bone scan image by first performing a high-resolution thin-slice scan of the user's temporal bone region using a thin-slice scanning unit to obtain a temporal bone CT image. Then, the preprocessing unit performs image enhancement, noise suppression, and other processing on the CT image to generate the temporal bone scan image.

[0016] Furthermore, in the system provided in the application embodiment, the scanning module 11 further includes: A thin-slice scanning unit is used to perform a thin-slice scan on the user's temporal bone region to obtain a temporal bone CT image; a preprocessing unit is used to preprocess the temporal bone CT image to obtain the temporal bone scan image.

[0017] In this embodiment of the application, the thin-slice scanning unit first performs a high-resolution thin-slice scan on the user's temporal bone region. Using CT imaging technology with a slice thickness of less than 0.5 mm, it acquires continuous tomographic images of the temporal bone structure layer by layer to obtain a temporal bone CT image including structures such as the external auditory canal.

[0018] The preprocessing unit then preprocesses the temporal bone CT image, performing operations such as image denoising, grayscale correction, edge enhancement, and spatial registration to obtain the temporal bone scan image.

[0019] The boundary extraction module 12 is used to extract the external auditory canal boundary from the temporal bone scan image according to the threshold adaptive segmentation algorithm, and obtain the external auditory canal boundary features.

[0020] In this embodiment, when the boundary extraction module 12 extracts the external auditory canal boundary from the temporal bone scan image using a threshold adaptive segmentation algorithm, it first divides the temporal bone scan image into multiple local window images. Then, threshold adaptive segmentation is applied to each local window image to generate a corresponding local binary image. Based on these local binary images, connected component analysis is performed to identify the region where the external auditory canal is located. Next, edge detection is performed within this region to extract the external auditory canal boundary contour. Finally, morphological optimization processing is used to correct and smooth the boundary contour, resulting in the external auditory canal boundary features.

[0021] Further, the system provided by the application embodiment further comprises: The temporal bone scan image is divided into a plurality of local window images; threshold adaptive segmentation is performed according to the plurality of local window images to construct a plurality of local binary images; connected domain analysis is performed according to the plurality of local binary images to determine an external auditory canal region; edge detection is performed according to the external auditory canal region to extract an external auditory canal boundary contour; and morphological optimization processing is performed on the external auditory canal boundary contour to obtain the external auditory canal boundary feature.

[0022] In the application embodiment, when the boundary extraction module 12 processes the temporal bone scan image by using the threshold adaptive segmentation algorithm, the whole temporal bone scan image is first divided into a plurality of local window images by using a sliding window method. For example, the image is segmented according to a fixed region of 32*32 pixels, so that each window has local independence in gray scale calculation.

[0023] After the plurality of local window images are obtained, threshold adaptive segmentation is performed on each window image. Specifically, a local threshold is automatically determined by calculating the average gray value and the gray fluctuation degree of the pixels in each window, and the pixels are divided into foreground and background by using, for example, the Niblack algorithm. Through this process, a plurality of local binary images are constructed.

[0024] Next, connected domain analysis is performed on the local binary images, and 8-adjacent pixel connection is used to identify the pixel sets that are associated with each other. According to the size, shape compactness degree and spatial position in the image, each connected region is screened to identify the region having the structure characteristics of the external auditory canal. For example, the external auditory canal usually presents an elongated and continuous closed channel structure in the image, and the region to which the external auditory canal belongs is determined in combination with these morphological characteristics.

[0025] After the region identification is completed, edge detection is performed on the determined external auditory canal region. The Canny edge detection algorithm is used to perform smoothing processing on the image by using a Gaussian filter to remove high-frequency noise. Subsequently, the gray change amplitude of the image is calculated to locate the edges at the gray mutation positions. Non-maximum suppression processing is then performed to accurately locate the edge positions. Finally, the effective edges are selected according to the gray gradient amplitude to obtain the external auditory canal contour line with clear boundaries and strong continuity.

[0026] Finally, the extracted boundary contour is corrected and smoothed by morphological optimization processing. The processing includes erosion operation for removing noise points on the edge, dilation operation for completing the boundary defects, and closing operation for connecting the broken contours and eliminating the internal small holes. Through the above operations, the external auditory canal boundary feature with complete structure, continuous boundary and accurate morphology is finally obtained.

[0027] The model establishing module 13 is configured to construct a three-dimensional model of the ear canal according to a marching cubes algorithm based on the ear canal boundary features.

[0028] In the embodiments of the present application, when constructing the three-dimensional model of the ear canal, the model establishing module 13 first integrates the extracted ear canal boundary feature data into a three-dimensional spatial coordinate system to construct a three-dimensional data structure composed of a plurality of cubic units. Each cubic unit corresponds to a pixel block with a spatial position in the original image, and is marked with different values according to whether it belongs to the ear canal boundary region, thereby forming a three-dimensional binary image data set.

[0029] On this basis, the entire three-dimensional data is divided into a plurality of cubic units of equal size, and each cubic unit is composed of eight adjacent data points as vertices. Then each cubic unit is traversed in turn, and whether there is a structural boundary inside the cubic unit is identified by judging the value combination of the eight vertices.

[0030] For the identified boundary region, according to the definition of the marching cubes algorithm, the geometric structure corresponding to the current vertex state is searched in the preset combination correspondence, and a plurality of triangular facets are drawn in the cubic unit. These triangular facets represent the boundary surface at this position and have a clear geometric position and direction. By processing all cubic units one by one, the triangular facets formed in each cubic unit are continuously connected, and finally a three-dimensional surface model of the ear canal is constructed.

[0031] The intercepting module 14 is configured to dynamically intercept the three-dimensional model of the ear canal to obtain a continuous cross section of the ear canal.

[0032] In the embodiments of the present application, when dynamically intercepting the three-dimensional model of the ear canal, the intercepting module 14 first performs smoothing processing on the three-dimensional model of the ear canal to generate an optimized model of the ear canal with more stable structure. Then, the model center axis of the optimized model of the ear canal is used to accurately describe the spatial trend of the ear canal. On this basis, a plurality of cross sections perpendicular to the axis direction are dynamically generated by performing equal-interval cutting operation along the center axis according to a predetermined intercepting step, and finally a continuous cross section of the ear canal with spatial continuity and structural integrity is obtained.

[0033] Further, in the system provided by the embodiments of the present application, the intercepting module 14 further comprises: a smoothing processing unit configured to perform smoothing processing on the three-dimensional model of the ear canal to obtain an optimized model of the ear canal; an axis determining unit configured to determine a model center axis of the optimized model of the ear canal; and a dynamic intercepting unit configured to dynamically intercept the optimized model of the ear canal based on the model center axis according to a predetermined intercepting step to obtain the continuous cross section of the ear canal.

[0034] In the embodiment of the present application, when the dynamic intercepting is performed according to the three-dimensional model of the external auditory canal, first, the three-dimensional model of the external auditory canal is smoothed by the smoothing unit. The position of each vertex in the three-dimensional model of the external auditory canal is iteratively optimized by using a geometric algorithm such as Laplacian smoothing, the relative position of the vertex and adjacent vertices is calculated, and the vertex coordinate value is adjusted, so as to eliminate edge sawtooth, local mutation and high-frequency noise generated in the modeling process, and an optimized model of the external auditory canal is obtained.

[0035] Then, the axis determination unit determines the axis of the external auditory canal based on the optimized model of the external auditory canal, generates a plurality of initial cross sections along the axial direction of the external auditory canal, extracts the contour barycenter in each cross section, connects all the barycenter points in spatial order, and fits a three-dimensional spatial curve as the model center axis.

[0036] After the center axis is established, the cross section acquisition stage is entered. A plurality of cut points are generated by the dynamic intercepting unit based on the model center axis and according to a predetermined intercepting step (for example, every 0.5 mm). A plane perpendicular to the direction of the center axis is established at each cut point, and the intersection operation of the plane and the optimized model of the external auditory canal is performed, so as to obtain a closed cross section contour. By repeating this operation along the axis in sequence, a series of uniformly distributed and sequentially continuous continuous cross sections of the external auditory canal are gradually acquired.

[0037] The atlas construction module 15 is configured to perform multi-dimensional measurement analysis on the continuous cross sections of the external auditory canal, and construct an external auditory canal parameter mapping atlas.

[0038] In the embodiment of the present application, when the atlas construction module 15 performs multi-dimensional measurement analysis on the continuous cross sections of the external auditory canal, first, the volume parameter analysis is performed on the continuous cross sections of the external auditory canal, and a first parameter measurement result reflecting the local structure volume change is obtained. Then, the morphological parameter analysis is performed according to the morphological factors such as the segmented diameter extreme value and the average cross section area, and a second parameter measurement result is obtained. Then, the spatial geometric parameter analysis is performed in combination with the spatial geometric factors such as the local curvature radius, the three-dimensional bending angle and the center path length, and a third parameter measurement result is obtained. Finally, the above three types of measurement results are integrated to generate the external auditory canal parameter mapping atlas.

[0039] Further, in the system provided by the embodiment of the present application, the atlas construction module 15 further comprises: The volume parameter analysis unit is configured to analyze volume parameters according to the continuous cross sections of the external auditory canal, and obtain a first parameter measurement result; the shape parameter analysis unit is configured to analyze shape parameters of the continuous cross sections of the external auditory canal according to shape factors, and obtain a second parameter measurement result; the geometric parameter analysis unit is configured to analyze spatial geometric parameters of the continuous cross sections of the external auditory canal according to spatial geometric factors, and obtain a third parameter measurement result; and the integration unit is configured to generate the external auditory canal parameter mapping atlas according to the first parameter measurement result, the second parameter measurement result and the third parameter measurement result.

[0040] Further, the system provided by the application embodiment further comprises: The shape factors include a segmented diameter extreme value and an average cross-sectional area.

[0041] Further, the system provided by the application embodiment further comprises: The spatial geometric factors include a local curvature radius, a three-dimensional bending angle and a central path length.

[0042] In the application embodiment, first, when analyzing the structure volume of the external auditory canal, the volume parameter analysis unit performs volume parameter analysis on the continuous cross sections. The spatial structure between two adjacent cross sections is regarded as an irregular cylinder, and the cross section contour integration method is used to calculate the volume. Specifically, the boundary contour on the adjacent cross sections is extracted, a triangular prism unit is constructed by using linear interpolation, and the volume of each small body unit is solved by geometric calculation. All the body units are accumulated to form a segmented volume curve of the external auditory canal along the central axis direction, and a first parameter measurement result is output. The first parameter measurement result includes the local volume value between each pair of adjacent cross sections, the overall cumulative volume, the volume distribution trend along the central axis, the volume change rate per unit length and other data reflecting the volume characteristics of the external auditory canal channel.

[0043] Then, the shape parameter analysis unit analyzes the shape parameters of each external auditory canal cross section according to the shape factors. The shape factors include a segmented diameter extreme value and an average cross-sectional area. To extract the segmented diameter extreme value, the distance between the farthest point pair and the nearest point pair is calculated based on the boundary contour, and is defined as the maximum diameter and the minimum diameter, respectively. For example, the farthest point pair on the closed boundary is efficiently calculated by using the rotating lock algorithm; and the nearest point pair is obtained by boundary scanning. The average cross-sectional area is obtained by summing the areas of the polygons formed by the boundary points, and the Shoelace formula is used to calculate the area of the irregular polygon. The second parameter measurement result is output through the process, reflecting the cross-sectional size change, shape contraction and expansion state of the external auditory canal at different positions. The second parameter measurement result includes the maximum diameter, the minimum diameter, the average cross-sectional area, the cross-sectional perimeter and other measurement data representing the local geometric shape change of each cross section.

[0044] In the spatial geometry analysis stage, the geometry parameter analysis unit analyzes the three-dimensional path and structure of the cross-section sequence according to the spatial geometry factor. The local curvature radius is calculated by fitting the center points of three consecutive cross-sections to establish a local circular arc model, and the radius of the circular arc is taken as the curvature radius value, reflecting the bending degree of the segment; the three-dimensional bending angle is obtained by calculating the included angle between the normal vectors of two adjacent cross-sections, for example, by using the vector dot product formula to solve the angle change, which is used to identify the structure turning and direction changing point. The center path length is accumulated from the starting point of the external auditory canal along the center point sequence by using the path accumulation method to obtain the cumulative length of each cross-section in the spatial channel. The final output parameter measurement third result completely describes the spatial trend characteristics of the external auditory canal structure. The parameter measurement third result includes the local curvature radius of each segment, the three-dimensional bending angle between adjacent cross-sections, the cumulative center path length, and the geometric quantification information of the overall channel extension trajectory.

[0045] Finally, the integration unit jointly processes the parameter measurement first result, the parameter measurement second result, and the parameter measurement third result. The three parameter sequences are aligned in position according to the spatial order of the cross-sections, and a visual technology is used to generate an external auditory canal parameter mapping atlas. Specifically, color gradient coding is used to represent the cross-section parameter values, such as using cold and warm colors to reflect the volume size, using color brightness to represent the cross-sectional area, and using a curve graph to represent the trend of the center path length. The atlas is displayed on the surface of the three-dimensional model or output as a two-dimensional distribution chart, providing an intuitive display of the structure trend.

[0046] In the embodiments of the present application, as described above, the embodiments of the present application have at least the following technical effects: The present application obtains a temporal bone scan image; extracts an external auditory canal boundary from the temporal bone scan image according to a threshold adaptive segmentation algorithm to obtain an external auditory canal boundary feature; constructs an external auditory canal three-dimensional model based on the external auditory canal boundary feature according to a moving cube algorithm; dynamically intercepts the external auditory canal three-dimensional model to obtain continuous cross-sections of the external auditory canal; and performs multi-dimensional measurement analysis on the continuous cross-sections of the external auditory canal to construct an external auditory canal parameter mapping atlas. The present application solves the technical problems of low accuracy, lack of continuity, and three-dimensional structure information in the prior art, and achieves the technical effects of high-precision, continuous, and visual external auditory canal three-dimensional parameter measurement and mapping by introducing threshold adaptive segmentation, moving cube three-dimensional modeling, and multi-dimensional parameter analysis.

[0047] Embodiment two, based on the same inventive concept as the parameter measurement system based on external auditory canal three-dimensional reconstruction in the foregoing embodiments, as shown in Figure 2 The present application provides a parameter measurement method based on external auditory canal three-dimensional reconstruction, which comprises: Obtaining a temporal bone scan image; performing outer ear canal boundary extraction on the temporal bone scan image according to a threshold adaptive segmentation algorithm to obtain outer ear canal boundary features; constructing an outer ear canal three-dimensional model based on the outer ear canal boundary features according to a marching cubes algorithm; performing dynamic interception according to the outer ear canal three-dimensional model to obtain outer ear canal continuous cross sections; and performing multi-dimensional measurement analysis according to the outer ear canal continuous cross sections to construct an outer ear canal parameter mapping atlas.

[0048] Further, the method further comprises: Performing thin layer scanning on a temporal bone region of a user to obtain a temporal bone CT image; and pre-processing the temporal bone CT image to obtain the temporal bone scan image.

[0049] Further, the method further comprises: Dividing the temporal bone scan image into a plurality of local window images; performing threshold adaptive segmentation according to the plurality of local window images to construct a plurality of local binary images; performing connected component analysis according to the plurality of local binary images to determine an outer ear canal region; performing edge detection according to the outer ear canal region to extract an outer ear canal boundary contour; and performing morphological optimization processing on the outer ear canal boundary contour to obtain the outer ear canal boundary features.

[0050] Further, the method further comprises: Performing smoothing processing on the outer ear canal three-dimensional model to obtain an outer ear canal optimized model; determining a model center axis of the outer ear canal optimized model; and performing dynamic interception on the outer ear canal optimized model according to a predetermined interception step length based on the model center axis to obtain the outer ear canal continuous cross sections.

[0051] Further, the method further comprises: Performing volume parameter analysis according to the outer ear canal continuous cross sections to obtain a parameter measurement first result; performing morphological parameter analysis according to a morphological factor on the outer ear canal continuous cross sections to obtain a parameter measurement second result; performing spatial geometric parameter analysis according to a spatial geometric factor on the outer ear canal continuous cross sections to obtain a parameter measurement third result; and generating the outer ear canal parameter mapping atlas according to the parameter measurement first result, the parameter measurement second result, and the parameter measurement third result.

[0052] Further, the method further comprises: The morphological factor comprises a subsection diameter extreme value and an average cross-sectional area.

[0053] Further, the method further comprises: The spatial geometric factor comprises a local curvature radius, a three-dimensional bending angle, and a center path length.

[0054] It should be noted that the above-mentioned embodiment sequence of the present application is only for description, and does not represent the advantages and disadvantages of the embodiments. And the above describes a specific embodiment of the present application. The processes depicted in the drawings do not necessarily require the specific order and continuous order shown to achieve the desired results. In some embodiments, multi-task processing and parallel processing are also possible or can be advantageous.

[0055] The above only describes the preferred embodiments of the present application, and does not limit the present application. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application shall be included in the protection scope of the present application.

[0056] The present application and the drawings are only exemplary descriptions of the present application, and are considered to cover any and all modifications, changes, combinations or equivalents within the scope of the present application. Obviously, those skilled in the art can make various modifications and changes to the present application without departing from the scope of the present application. Thus, if these modifications and changes of the present application belong to the scope of the present application and its equivalent technology, the present application intends to include these modifications and changes.

Claims

1. A parameter measurement system based on a three-dimensional reconstruction of the external ear canal, characterized in that, The system comprises: a scanning module for acquiring a temporal bone scan image; a boundary extraction module for performing outer ear canal boundary extraction on the temporal bone scan image according to a threshold adaptive segmentation algorithm to obtain outer ear canal boundary features; a model establishment module for establishing an outer ear canal three-dimensional model according to a marching cubes algorithm based on the outer ear canal boundary features; a cutting module for performing dynamic cutting according to the outer ear canal three-dimensional model to obtain outer ear canal continuous cross sections; a graph construction module for performing multi-dimensional measurement analysis on the outer ear canal continuous cross sections to construct an outer ear canal parameter mapping graph.

2. The system for parameter measurement based on three-dimensional reconstruction of the external auditory canal according to claim 1, characterized in that, The scanning module comprises: a thin layer scanning unit for performing thin layer scanning on a temporal bone region of a user to obtain a temporal bone CT image; a preprocessing unit for preprocessing the temporal bone CT image to obtain the temporal bone scan image.

3. The system for parameter measurement based on three-dimensional reconstruction of the external auditory canal according to claim 1, characterized in that, The threshold adaptive segmentation algorithm comprises: dividing the temporal bone scan image into a plurality of local window images; performing threshold adaptive segmentation on the plurality of local window images to construct a plurality of local binary images; performing connected domain analysis on the plurality of local binary images to determine an outer ear canal region; performing edge detection on the outer ear canal region to extract an outer ear canal boundary contour; performing morphological optimization processing on the outer ear canal boundary contour to obtain the outer ear canal boundary features.

4. The system for parameter measurement based on three-dimensional reconstruction of the external auditory canal according to claim 1, characterized in that, The cutting module comprises: a smoothing processing unit for performing smoothing processing on the outer ear canal three-dimensional model to obtain an outer ear canal optimized model; an axis determination unit for determining a model center axis of the outer ear canal optimized model; a dynamic cutting unit for performing dynamic cutting on the outer ear canal optimized model based on the model center axis according to a predetermined cutting step to obtain the outer ear canal continuous cross sections.

5. The system for parameter measurement based on three-dimensional reconstruction of the external auditory canal according to claim 1, wherein, The graph construction module comprises: a volume parameter analysis unit for performing volume parameter analysis on the outer ear canal continuous cross sections to obtain a parameter measurement first result; a morphological parameter analysis unit for performing morphological parameter analysis on the outer ear canal continuous cross sections according to a morphological factor to obtain a parameter measurement second result; a geometric parameter analysis unit for performing spatial geometric parameter analysis on the outer ear canal continuous cross sections according to a spatial geometric factor to obtain a parameter measurement third result; an integration unit for generating the outer ear canal parameter mapping graph according to the parameter measurement first result, the parameter measurement second result, and the parameter measurement third result.

6. The system for parameter measurement based on three-dimensional reconstruction of the external auditory canal according to claim 5, characterized in that, The morphological factor comprises a segmented diameter extreme value and an average cross-sectional area.

7. The system for parameter measurement based on three-dimensional reconstruction of the external auditory canal according to claim 5, characterized in that, The spatial geometric factor comprises a local curvature radius, a three-dimensional bending angle, and a center path length.

8. A method of parameter measurement based on a three-dimensional reconstruction of the external ear canal, characterized in that The method is performed by the outer ear canal three-dimensional reconstruction-based parameter measurement system of any one of claims 1 to 7, comprising: acquiring a temporal bone scan image; performing outer ear canal boundary extraction on the temporal bone scan image according to a threshold adaptive segmentation algorithm to obtain outer ear canal boundary features; establishing an outer ear canal three-dimensional model according to a marching cubes algorithm based on the outer ear canal boundary features; performing dynamic cutting according to the outer ear canal three-dimensional model to obtain outer ear canal continuous cross sections; performing multi-dimensional measurement analysis on the outer ear canal continuous cross sections to construct an outer ear canal parameter mapping graph.

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