Ear parameter acquisition method and device

Abstract

The application discloses an ear parameter acquisition method and device, and relates to the technical field of image processing. The method can acquire a three-dimensional head image of a scanning object, and then output ear parameters of the ear of the scanning object based on ear tissues included in the ear of the scanning object in the three-dimensional head image. Compared with the way of detecting the ear by using tools to obtain the ear parameters, the method provided by the application can effectively improve the ear parameter acquisition efficiency and improve the ear parameter acquisition flexibility.

Description

Technical Field

[0001] This application relates to the field of image processing technology, and in particular to a method and apparatus for acquiring ear parameters. Background Technology

[0002] Ear diseases (such as ear deformities) can affect people's health and quality of life, making their detection and treatment crucial. The prerequisite for detecting ear diseases is obtaining ear parameters.

[0003] In related technologies, doctors can manually examine a patient's ear using tools to obtain ear parameters. However, the efficiency of obtaining ear parameters in these technologies is relatively low. Summary of the Invention

[0004] This application provides a method and apparatus for acquiring ear parameters, which can solve the problem of low efficiency in acquiring ear parameters in related technologies. The technical solution is as follows:

[0005] On the one hand, a method for obtaining ear parameters is provided, the method comprising:

[0006] Acquire a three-dimensional head image of the scanned object, the scanned object having ears;

[0007] Based on the ear tissue included in the ear in the three-dimensional head image, output the ear parameters of the ear;

[0008] The ear parameters include the ear tissues included in the ear of the scanned object.

[0009] Optionally, based on the ear tissue included in the three-dimensional head image, ear parameters of the ear are output, including:

[0010] Based on the three-dimensional head image, a target ear image of the scanned object is obtained, and the target ear image is labeled with the ear tissues included in the ear of the scanned object;

[0011] Based on the target ear image, the ear parameters of the ear are output.

[0012] Optionally, the ear includes: the inner ear, the middle ear, and the outer ear; based on the three-dimensional head image, obtaining a target ear image of the scanned object includes:

[0013] Based on the three-dimensional head image, a first ear image, a first inner ear image, and a first middle ear image of the scanned object are obtained, wherein the first ear image is at least labeled with the ear tissues included in the outer ear, the first inner ear image is labeled with the ear tissues included in the inner ear, and the first middle ear image is labeled with the ear tissues included in the middle ear.

[0014] A target ear image is obtained based on the first ear image, the first inner ear image, and the first middle ear image.

[0015] Optionally, based on the three-dimensional head image, obtaining a first ear image, a first inner ear image, and a first middle ear image of the scanned object includes:

[0016] Based on the three-dimensional head image, a second inner ear sub-image and a second middle ear sub-image of the scanned object are obtained. The second inner ear sub-image does not label the ear tissues included in the inner ear, and the second middle ear sub-image does not label the ear tissues included in the middle ear.

[0017] The second inner ear image, the second middle ear image, and the outer ear image are stitched together to obtain the second ear image;

[0018] The first ear image is obtained based on the second ear image;

[0019] Based on the second inner ear sub-image, obtain the first inner ear sub-image;

[0020] Based on the second middle ear image, the first middle ear image is obtained.

[0021] Optionally, based on the second inner ear image, obtaining the first inner ear image includes:

[0022] The second inner ear sub-image is input into the inner ear segmentation model to obtain the first inner ear sub-image output by the inner ear segmentation model.

[0023] Optionally, based on the second middle ear image, obtaining the first middle ear image includes:

[0024] The second middle ear sub-image is input into the middle ear segmentation model to obtain the first middle ear sub-image output by the middle ear segmentation model.

[0025] Optionally, obtaining the first ear image based on the second ear image includes:

[0026] The second ear image is input into the ear segmentation model to obtain the first ear image output by the ear segmentation model.

[0027] Optionally, based on the three-dimensional head image, obtaining a second inner ear image and a second middle ear image of the scanned object includes:

[0028] The positions of the inner ear key points and the middle ear key points in the three-dimensional head image were determined.

[0029] Based on the location of the key points in the inner ear, the three-dimensional head image is sampled to obtain a second inner ear sub-image of the scanned object;

[0030] Based on the location of the key points in the middle ear, the three-dimensional head image is sampled to obtain a second middle ear sub-image of the scanned object.

[0031] On the other hand, an ear parameter acquisition device is provided, the device comprising:

[0032] The acquisition module is used to acquire a three-dimensional head image of the scanned object, which has ears;

[0033] The output module is used to output ear parameters of the ear based on the ear tissue included in the ear in the three-dimensional head image;

[0034] The ear parameters include the ear tissues included in the ear of the scanned object.

[0035] Optionally, the device further includes:

[0036] An ear diagnosis module is used to determine the diagnostic result of the ear based on the ear parameters.

[0037] In another aspect, a computer-readable storage medium is provided having a computer program stored thereon, which, when executed by a processor, implements the method for acquiring ear parameters as described above.

[0038] In another aspect, a computer program product is provided, the computer program product comprising a computer program or computer instructions, wherein when the computer program or computer instructions are executed by a processor, the method for obtaining ear parameters as described above is implemented.

[0039] The beneficial effects of the technical solution provided in this application include at least the following:

[0040] This application provides a method and apparatus for acquiring ear parameters. The method can acquire a three-dimensional head image of a scanned object, and then output ear parameters based on the ear tissue included in the ear of the scanned object in the three-dimensional head image. Compared with the method of manually detecting the ear with tools to obtain ear parameters, the method provided in this application can effectively improve the efficiency and flexibility of acquiring ear parameters.

[0041] Additional aspects and advantages of this application will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of this application. Attached Figure Description

[0042] Figure 1This is a flowchart of a method for obtaining ear parameters provided in an embodiment of this application;

[0043] Figure 2 This is a flowchart of another method for obtaining ear parameters provided in an embodiment of this application;

[0044] Figure 3 This is a flowchart of a method for obtaining a target ear image of a scanned object based on a three-dimensional head image, provided in an embodiment of this application.

[0045] Figure 4 This is a schematic diagram of the structure of an ear parameter acquisition device provided in an embodiment of this application;

[0046] Figure 5 This is a schematic diagram of another ear parameter acquisition device provided in an embodiment of this application;

[0047] Figure 6 This is a schematic diagram of the structure of a parameter acquisition device provided in an embodiment of this application. Detailed Implementation

[0048] The embodiments of this application are described in detail below. Examples of these embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and intended to explain this application, and should not be construed as limiting this application.

[0049] This application provides a method for acquiring ear parameters, which is applied to an ear parameter acquisition device. Optionally, the ear parameter acquisition device (hereinafter referred to as the parameter acquisition device) can be a medical imaging device, a mobile terminal, or a fixed terminal, etc. The medical imaging device can be a computed tomography (CT) device or a magnetic resonance imaging (MRI) device. See also Figure 1 The method includes:

[0050] Step 101: Obtain the 3D head image of the scanned object.

[0051] When it is necessary to obtain the ear parameters of a scanned object, the head of the object can be scanned using a CT scanner to obtain a three-dimensional head image. The scanned object can be a human body, an animal body, or a phantom. The scanned object has an ear, which includes multiple ear regions, each containing ear tissue. These multiple ear regions are the outer ear, middle ear, and inner ear.

[0052] Step 102: Based on the ear tissue included in the 3D head image, output the ear parameters of the ear.

[0053] The ear parameters include: multiple ear tissues included in the ear of the scanned object. For example, the ear parameters may include: multiple ear tissues included in the ear, tissue parameters (such as diameter, height, and length) of a first ear tissue among the multiple ear tissues, and the connection status of at least two second ear tissues among the multiple ear tissues. The connection status includes one of being connected or not connected.

[0054] In this embodiment, the parameter acquisition device pre-stores a parameter acquisition model. The parameter acquisition device can input the 3D head image into the parameter acquisition model to obtain the ear parameters of the scanned object output by the parameter acquisition model. It is understood that before inputting the 3D head image into the parameter acquisition model, the parameter acquisition device can train the model based on multiple auxiliary training data to obtain the parameter acquisition model. Each auxiliary training data may include: a sample head image, and ear parameters of the sample ear obtained based on the sample head image.

[0055] Alternatively, the parameter acquisition device can identify the ear tissue included in the scanned object's ear from a 3D head image. Then, based on this ear tissue, the device can output ear parameters.

[0056] Alternatively, the ear tissues included in the ear can be represented by a target ear image. In this case, the parameter acquisition device can first acquire a target ear image of the scanned object based on a 3D head image. This target ear image is labeled with the ear tissues included in the scanned object's ear. Then, the parameter acquisition device can output the ear parameters of the ear based on the target ear image.

[0057] In summary, this application provides a method for obtaining ear parameters. This method acquires a three-dimensional head image of a scanned object and then outputs ear parameters based on the ear tissue included in the ear portion of the scanned object within the three-dimensional head image. Compared to manually detecting the ear using tools to obtain ear parameters, the method provided in this application effectively improves the efficiency and flexibility of ear parameter acquisition.

[0058] It should be understood that the scanned object generally has two ears. For each ear, the parameter acquisition device can use the method provided in the embodiments of this application to acquire the ear parameters of that ear.

[0059] This application embodiment uses an example of a parameter acquisition device first acquiring a target ear image based on a 3D head image, and then outputting ear parameters based on the target ear image, to exemplify the ear parameter acquisition method provided in this application embodiment. See also Figure 2 The method may include:

[0060] Step 201: Obtain the 3D head image of the scanned object.

[0061] When it is necessary to obtain the ear parameters of the object being scanned, the head of the object can be scanned using medical imaging equipment to obtain a three-dimensional head image of the object. The object being scanned can be a human body, an animal body, or a phantom.

[0062] Optionally, the medical imaging device can be a photon-counting CT scanner. Compared to ordinary CT scanners, photon-counting CT scanners have a slice thickness of 0.1 to 0.3 millimeters (mm), thus offering higher spatial resolution and better image quality. Therefore, photon-counting CT scanners can acquire clearer images of the minute anatomical structures within the outer, middle, and inner ear, resulting in more comprehensive and accurate ear parameters. The slice thickness of a photon-counting CT scanner refers to the thickness of the image slice acquired in each scan. In other words, it is the thickness of the image acquired in each scan.

[0063] Step 202: Based on the 3D head image, obtain the target ear image of the scanned object.

[0064] The target ear image is labeled with the various ear tissues included in the scanned object's ear. That is, the ear tissues included in each ear region of the scanned object's outer ear, middle ear, and inner ear.

[0065] It should be understood that a normal (i.e., non-malformed) ear includes the auricle and external auditory canal. The middle ear includes the tympanic membrane, middle ear cavity, ossicles, and eustachian tubes, with the ossicles including the malleus, incus, and stapes. The inner ear includes the internal auditory canal, facial nerve, auditory nerve, cochlea, vestibule, vestibular aqueduct, and semicircular canals, including the lateral semicircular canal, anterior semicircular canal (also called superior semicircular canal), and posterior semicircular canal. The ear of the scanned object in this application embodiment may be normal or may suffer from ear diseases (such as malformations), meaning it may not include certain ear tissues in the aforementioned ear regions.

[0066] Optionally, the target ear image may also be labeled with various ear regions of the scanned object's ear. That is, the target ear image may be labeled with various ear regions of the ear, as well as the ear tissue included in each ear region.

[0067] In this embodiment, the parameter acquisition device can annotate each ear region and each ear tissue in the target ear image using methods such as multi-color drawing, label setting, text addition, and transparency adjustment, so that the target ear image can characterize the ear tissues included in the ear and the location of each ear tissue. For example, the parameter acquisition device can use different colors to annotate each ear region and each ear tissue.

[0068] In one alternative implementation, the parameter acquisition device may pre-store an image acquisition model. The parameter acquisition device can input the 3D head image into the image acquisition model to obtain a target ear image output by the image acquisition model.

[0069] Understandably, the parameter acquisition device can acquire multiple first training data sets, each of which may include: a sample head image and a target sample ear image obtained based on the sample head image. The target sample ear image at least annotates all the ear tissues included in the scanned object's ear. For example, the target sample ear image annotates all the ear regions and ear tissues included in the ear. The parameter acquisition device can then train a model using this first training data to obtain an image acquisition model.

[0070] In another alternative implementation, see [link to implementation details]. Figure 3 The process of the parameter acquisition device performing step 202 may include:

[0071] Step 2021: Based on the three-dimensional head image, obtain the first ear image, the first inner ear image, and the first middle ear image of the scanned object.

[0072] The first ear image at least labels the ear tissues included in the outer ear of the scanned object. The first inner ear sub-image labels the ear tissues included in the inner ear of the scanned object, and the first middle ear sub-image labels the ear tissues included in the middle ear of the scanned object.

[0073] Understandably, since the ear tissues included in the outer ear are relatively simple, the ear tissues included in the outer ear of the scanned object can be directly marked in the first ear image. Optionally, the first ear image may also be marked with each ear region included in the scanned object's ear. That is, the first ear image is marked with each ear region included in the ear, and the ear tissues included in each ear region.

[0074] Step 2022: Obtain the target ear image based on the first ear image, the first inner ear image, and the first middle ear image.

[0075] The parameter acquisition device can extract annotation information from the first ear image, the first inner ear image, and the first middle ear image, and then fuse these images to obtain a fused image. The parameter acquisition device can then annotate the fused image based on the annotation information to obtain the target ear image.

[0076] The annotation information includes: the names of each ear region and each ear tissue, and their positions in the three-dimensional coordinate system of the three-dimensional head image. This three-dimensional coordinate system can be established using the head of the scanned object as an example. For instance, the origin of this three-dimensional coordinate system can be any point on the head, the X-axis can be the front-back direction of the head, the Y-axis can be the left-right direction of the head, and the Z-axis can be perpendicular to both the X and Y axes. The position of the ear region (or ear tissue) can include: the position of each point constituting the ear region (or ear tissue) in the three-dimensional coordinate system.

[0077] In this embodiment of the application, the process of the parameter acquisition device performing step 2021 may include:

[0078] Step S1: Based on the three-dimensional head image, obtain the second inner ear image and the second middle ear image of the scanned object.

[0079] The second inner ear sub-image does not label the individual ear tissues included in the inner ear of the scanned object. The second middle ear sub-image does not label the individual ear tissues included in the middle ear of the scanned object.

[0080] As an alternative example, the parameter acquisition device can determine the positions of inner ear keypoints and middle ear keypoints in a three-dimensional head image. Then, the device can sample the three-dimensional head image based on the positions of the inner ear keypoints to obtain a second inner ear sub-image of the scanned object, and can sample the three-dimensional head image based on the positions of the middle ear keypoints to obtain a second middle ear sub-image of the scanned object.

[0081] The location of each keypoint in the 3D head image refers to its coordinates in the 3D coordinate system of the head image. Optionally, the inner ear keypoint may include the center point of the cochlea. The middle ear keypoint may include the center point of the ossicles.

[0082] In this embodiment of the application, the process of the parameter acquisition device acquiring the second inner ear image and the second middle ear image is illustrated by taking the sampling of a three-dimensional head image based on the center point of the cochlea as an example:

[0083] The parameter acquisition device can determine a region of interest (ROI) image of the inner ear from a three-dimensional head image based on the location of the cochlear center point. This ROI image can refer to an image containing the inner ear region centered on the inner ear center point (such as the cochlear center point). Then, the parameter acquisition device can sample the ROI image with the cochlear center point as the sampling starting point and a preset sampling step size, thereby obtaining a second inner ear sub-image.

[0084] The sampling step size refers to the distance between adjacent sampling points when sampling the image. The size of this sampling step size determines the resolution of the acquired second inner ear image. For example, the sampling step size can be smaller than the slice thickness of the medical imaging equipment. This ensures a high resolution of the acquired second inner ear image.

[0085] Optionally, the parameter acquisition device can extract features from the three-dimensional head image to obtain relevant features of the inner ear (or middle ear), and predict the location of key points of the inner ear (or middle ear) in the three-dimensional head image based on these relevant features through a regression network.

[0086] Alternatively, the parameter acquisition device responds to the annotation operation of inner ear keypoints to determine the position of those keypoints in the 3D head image. Furthermore, the parameter acquisition device can also respond to the annotation operation of middle ear keypoints to determine the position of those keypoints in the 3D head image.

[0087] As another alternative example, the parameter acquisition device pre-stores an object detection and segmentation model. The parameter acquisition device can input the 3D head image into the object detection and segmentation model to obtain the second inner ear image and the second middle ear image output by the object detection and segmentation model.

[0088] It should be understood that before inputting the 3D head image into the object detection and segmentation model, the parameter acquisition device can acquire multiple second training data sets. Each second training data set includes: a sample head image, a first inner ear sample sub-image cropped from the sample head image, and a first middle ear sample sub-image cropped from the sample head image. The parameter acquisition device can then train the model using these multiple second training data sets to obtain the object detection and segmentation model. Note that the first inner ear sample sub-image does not label the inner ear tissues, and the first middle ear sample sub-image does not label the middle ear tissues.

[0089] Step S2: The second inner ear image, the second middle ear image, and the outer ear image are stitched together to obtain the second ear image.

[0090] The parameter acquisition device can stitch together the second inner ear sub-image, the second middle ear sub-image, and the outer ear sub-image according to the relative positions of the outer ear, middle ear, and inner ear to obtain a second ear image. That is, the second ear image can include: the second inner ear sub-image, the second middle ear sub-image, and the outer ear sub-image. The outer ear sub-image does not label the ear tissues included in the outer ear of the scanned object.

[0091] In this embodiment of the application, before executing step 2022, the parameter acquisition device can acquire the outer ear image through a pre-stored object detection and segmentation model. That is, after the parameter acquisition device inputs the 3D head image of the scanned object into the object detection and segmentation model, the object detection and segmentation model can also output the outer ear image of the scanned object. At this time, each of the second training data mentioned above can also include: a sample outer ear image cropped from the sample head image.

[0092] Step S3: Obtain the first ear image based on the second ear image.

[0093] The first ear image includes a second inner ear image, a second middle ear image, and an outer ear image. Each ear region is marked in the first ear image.

[0094] As an optional embodiment, the parameter acquisition device may pre-store an ear segmentation model. The parameter acquisition device can input a second ear image into the ear segmentation model to obtain a first ear image output by the ear segmentation model.

[0095] In this embodiment of the application, the parameter acquisition device can acquire multiple third training data and perform model training on the multiple third training data to obtain an ear segmentation model. Each third training data may include: a first ear sample image without labeled outer ear tissue, and a second ear sample image with labeled ear tissue.

[0096] Optionally, the second ear sample image may also be labeled with various ear regions.

[0097] As another alternative embodiment, the parameter acquisition device may, in response to a labeling operation of the ear tissues included in the outer ear in the second ear image, at least label the ear tissues included in the outer ear in the second ear image, thereby obtaining a first ear image.

[0098] Step S4: Obtain the first inner ear image based on the second inner ear image.

[0099] Optionally, the parameter acquisition device also stores an inner ear segmentation model. The parameter acquisition device can input the second inner ear sub-image into the inner ear segmentation model to obtain the first inner ear sub-image output by the inner ear segmentation model.

[0100] It should be understood that the parameter acquisition device can acquire multiple fourth training data sets and use these fourth training data sets to train the model to obtain an inner ear segmentation model. Each fourth training data set includes: a first inner ear sample sub-image and a second inner ear sample sub-image showing the various ear tissues labeled within the inner ear.

[0101] Step S5: Obtain the first middle ear image based on the second middle ear image.

[0102] Optionally, the parameter acquisition device also stores a middle ear segmentation model. The parameter acquisition device can input the second inner ear sub-image into the middle ear segmentation model to obtain the first inner ear sub-image output by the middle ear segmentation model.

[0103] It should be understood that the parameter acquisition device can acquire multiple fifth training data sets and use these fifth training data sets to train the model to obtain a middle ear segmentation model. Each fifth training data set includes: a first middle ear sample sub-image and a second middle ear sample sub-image labeled with various ear tissues of the middle ear.

[0104] In this embodiment, before training the ear segmentation model, inner ear segmentation model, and middle ear segmentation model, the parameter acquisition device can acquire a large number of first ear sample images, first inner ear sample sub-images, and first middle ear sample sub-images, and preprocess the acquired sample images (i.e., first ear sample images, first inner ear sample sub-images, and first middle ear sample sub-images). Then, in response to the annotation operation for each preprocessed sample image, the parameter acquisition device can acquire the annotated sample images.

[0105] Specifically, the external auditory canal and auricle (such as the external auditory canal, auricle, and various ear regions) can be labeled in the first ear sample image to obtain the second ear sample image. The internal auditory canal, facial nerve, auditory nerve, cochlea, vestibule, vestibular aqueduct, lateral semicircular canals, anterior semicircular canals, and posterior semicircular canals can be labeled in the first inner ear sample sub-image to obtain the second inner ear sample sub-image. The tympanic membrane, middle ear cavity, and eustachian tube can be labeled in the first middle ear sample sub-image, and the ossicles are labeled within the middle ear cavity to obtain the second middle ear sample sub-image.

[0106] The preprocessing of the sample images may include at least one of the following: removing sample images with low clarity, removing sample images other than ears, removing artifacts from the sample images, and adjusting the window width and window level of the sample images.

[0107] Each sample image is a three-dimensional image, which can be reconstructed from a two-dimensional image obtained by scanning the sample object. Each two-dimensional image includes at least 512*512 pixels, and the slice thickness during scanning of the sample object is less than or equal to 0.3mm. This ensures that the acquired sample images are of high quality and can clearly display the various ear tissues.

[0108] Understandably, annotation work can be done by doctors or experts with professional knowledge and experience, which can ensure the accuracy and consistency of annotation, thereby ensuring the high reliability of the trained ear segmentation model, inner ear segmentation model and middle ear segmentation model.

[0109] Step 203: Based on the target ear image, output the ear parameters of the scanned object.

[0110] The ear parameters may include at least the multiple ear tissues included in the ear of the scanned object. For example, the ear parameters may also include at least one of the following: the multiple ear tissues included in the ear of the scanned object, the tissue parameters (such as diameter, height, and length) of a first ear tissue among the multiple ear tissues, and the connection states of at least two second ear tissues among the multiple ear tissues. The connection states include one of being connected and not connected.

[0111] The first ear tissue may include at least one of the following: external ear, middle ear cavity, malleus, incus, stapes, internal auditory canal, cochlea, vestibular aqueduct, semicircular canals, facial nerve, and auditory nerve. The tissue parameters of the external ear may include the diameter of the external auditory canal. The tissue parameters of the middle ear cavity may include the average density, volume, maximum diameter, and minimum diameter. The average density of the middle ear cavity refers to the average grayscale value of all pixels in the sub-image of the middle ear cavity included in the target ear image. The tissue parameters of each bone tissue in the malleus, incus, and stapes may include the long axis, volume, maximum diameter, minimum diameter, and average density of that bone tissue. The tissue parameters of the internal auditory canal may include the diameter of the internal auditory canal. The tissue parameters of the cochlea may include the vertical height, horizontal width, length, number of coils, diameter (e.g., effective diameter, maximum diameter, and minimum diameter), area, and grayscale value of the cochlea. The cochlea is a spiral structure; the length of the cochlea refers to the length of the path that unfolds sequentially from the center of the cochlea outwards. The number of coils refers to the number of layers in this spiral structure. The grayscale value of the cochlea refers to the average grayscale value of all pixels in the sub-image of the cochlea included in the target ear image. The tissue parameters of the vestibular aqueduct can include its length, diameter (e.g., effective diameter, maximum diameter, and minimum diameter), area, and grayscale value. The tissue parameters of the semicircular canals can include the length, height, diameter (e.g., effective diameter, maximum diameter, and minimum diameter), area, and grayscale value of each of the lateral, anterior, and posterior semicircular canals. The tissue parameters of the facial nerve can include its central line, diameter, area, and grayscale value. The tissue parameters of the auditory nerve can include its central line, diameter, area, and grayscale value. The grayscale value of each ear tissue in the vestibular aqueduct, semicircular canals, facial nerve, and auditory nerve refers to the average grayscale value of all pixels in the sub-image of that ear tissue included in the target ear image.

[0112] The second ear tissue may include: the tympanic membrane, malleus, incus, and stapes. Ear parameters may include: the connection status of the tympanic membrane with other tissues. These other tissues are the ear tissues other than the tympanic membrane among multiple ear tissues. The connection status of the malleus and incus, and the connection status of the incus and stapes.

[0113] Understandably, for the first ear tissue, the parameter acquisition device can determine the image region where the ear tissue is located in the target ear image based on the location of the ear tissue, and then obtain the tissue parameters of the first ear tissue based on the image region.

[0114] For example, a parameter acquisition device can identify the central line of the external auditory canal in the image region where the external ear is located in a target ear image, and then obtain the diameter of the external auditory canal lumen based on this central line. The central line of the external auditory canal is the central line between the center of the external auditory canal opening and the center of the tympanic membrane in the middle ear.

[0115] The parameter acquisition device can identify the centerline of the middle ear cavity in the image region containing the middle ear in a target ear image, and determine the tissue parameters of the middle ear cavity based on this centerline. Furthermore, the device can acquire the tissue parameters of each bone tissue in the labeled malleus, incus, and stapes. During this process, the device can also identify the centerline of the eustachian tube in the target ear image.

[0116] The parameter acquisition device can identify the center and central line of the cochlea, the central line of the vestibular aqueduct, the central line of the lateral semicircular canals, the central line of the anterior semicircular canals, and the central line of the posterior semicircular canals within the image region containing the inner ear in a target ear image. Then, based on the center and central line of the cochlea, the device can calculate the tissue parameters of the cochlea; based on the central line of the vestibular aqueduct, it can calculate the tissue parameters of the vestibular aqueduct; and based on the central lines of each of the lateral, anterior, and posterior semicircular canals, it can calculate the corresponding tissue parameters of the semicircular canals.

[0117] Optionally, after acquiring the target ear image and ear parameters, the parameter acquisition device can also display the target ear image and ear parameters, so that clinicians can have a deeper and more intuitive understanding of the anatomical structure of the ear and the extent, morphology and adjacent relationships of lesions, thereby facilitating diagnosis and the development of the correct surgical plan.

[0118] It is understood that the order of steps in the method for obtaining ear parameters provided in this application embodiment can be appropriately adjusted, and steps can be added or removed as appropriate. For example, step 202 can be deleted as needed. Any variations that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the protection scope of this application, and therefore will not be elaborated further.

[0119] In summary, this application provides a method for obtaining ear parameters. This method acquires a three-dimensional head image of a scanned object and then outputs ear parameters based on the ear tissue included in the ear portion of the scanned object within the three-dimensional head image. Compared to manually detecting the ear using tools to obtain ear parameters, the method provided in this application effectively improves the efficiency and flexibility of ear parameter acquisition.

[0120] This application provides an ear parameter acquisition device, which can be applied to parameter acquisition equipment. See also... Figure 4 The device 300 includes:

[0121] The acquisition module 301 is used to acquire a three-dimensional head image of the scanned object, which has ears.

[0122] Output module 302 is used to output ear parameters of the ear based on the ear tissue included in the ear in the three-dimensional head image;

[0123] The ear parameters include the ear tissues included in the scanned object's ear.

[0124] Figure 5 This is a schematic diagram of another ear parameter acquisition device provided in an embodiment of this application. See also... Figure 5 The device may also include:

[0125] The ear diagnostic module 303 is used to determine the diagnostic results of the ear based on the ear parameters of the scanned object. The diagnostic results include at least one of the following: external auditory canal malformation, tympanic membrane malformation, ossicular malformation, inflammation or tumor in the middle ear cavity, internal auditory canal malformation, cochlear malformation, vestibular aqueduct malformation, and semicircular canal malformation.

[0126] Optionally, the ear parameters may include: multiple ear tissues included in the ear of the scanned object, the tissue parameters of a first ear tissue among the multiple ear tissues, and the connection status of at least two second ear tissues among the multiple ear tissues.

[0127] In this embodiment of the application, when the ear parameter includes the diameter of the external auditory canal, the ear diagnosis module 303 can be used to determine an external auditory canal malformation if the diameter of the external auditory canal is determined to be less than a first diameter threshold.

[0128] Specifically, external auditory canal malformations include: external auditory canal atresia and external auditory canal stenosis. If the ear diagnosis module 303 determines that the lumen diameter of the external auditory canal is less than a first diameter threshold and greater than an auxiliary diameter threshold, then external auditory canal stenosis of the ear can be determined. If the ear diagnosis module 303 determines that the lumen diameter is less than or equal to the auxiliary diameter threshold, then external auditory canal atresia of the ear can be determined.

[0129] The first diameter threshold is greater than the auxiliary diameter threshold, and both the first diameter threshold and the auxiliary diameter threshold can be pre-stored by the ear diagnostic module 303. For example, the first diameter threshold can be 4 mm, and the auxiliary diameter threshold can be 0.

[0130] When the ear parameters include the connection status of the tympanic membrane with other tissues, the ear diagnostic module 303 can be used to determine tympanic membrane deformity if the connection status is determined to be connection.

[0131] When the ear parameters include: the ear tissues included in the middle ear of the scanned object, the connection state of the malleus and incus, the connection state of the incus and stapes, and the connection state of each bone tissue in the malleus, incus, and stapes to the cavity wall of the middle ear, the ear diagnostic module 303 can be used for:

[0132] If it is determined that the ossicles of the scanned object do not include at least one of the malleus, incus, and stapes, and / or, the malleus and incus are not connected, and / or, the incus and stapes are not connected, and / or, at least one of the bone tissues of the malleus, incus, and stapes is connected to the wall of the middle ear cavity, then an ossicular deformity of the ear is determined.

[0133] When the ear parameter includes the average density of the middle ear cavity, the ear diagnostic module 303 can be used to determine the presence of inflammation or a tumor in the middle ear cavity if the average density of the middle ear cavity is determined to be higher than a density threshold. This density threshold may be pre-stored by the ear diagnostic module.

[0134] When the ear parameter includes the diameter of the internal auditory canal, the ear diagnostic module 303 can be used to determine an internal auditory canal malformation if the diameter of the internal auditory canal is determined to be less than a second diameter threshold or greater than a third diameter threshold. The third diameter threshold is greater than the second diameter threshold, and both can be pre-stored by the ear diagnostic module. For example, the third diameter threshold can be 8 mm, and the second diameter threshold can be 3 mm.

[0135] When the ear parameters include the tissue parameters of the inner ear and the cochlea, the ear diagnostic module 303 can be used to determine cochlear malformation if it is determined that the inner ear does not include the cochlea, and / or, the height of the cochlea is less than a height threshold, and / or, the length of the cochlea is less than a length threshold, and / or, the number of turns of the cochlea is less than a number of turns threshold.

[0136] The height threshold, length threshold, and number of rotations threshold can all be pre-stored in the ear diagnostic module 303. For example, the height threshold can be 5mm, the length threshold can be 31mm, and the number of rotations threshold can be 3 rotations.

[0137] When the ear parameters include the diameter of the vestibular aqueduct, the ear diagnostic module 303 can be used to determine vestibular aqueduct malformation if it is determined that the diameters of both the middle and distal segments of the vestibular aqueduct are greater than a fourth diameter threshold. Specifically, the scanned subject's ear suffers from large vestibular aqueduct syndrome.

[0138] When the ear parameters include the ear tissues included in the inner ear, and the diameters of each of the semicircular canals in the lateral, anterior, and posterior semicircular canals, the ear diagnostic module 303 can be used to: determine a semicircular canal malformation if it is determined that the inner ear does not include at least one of the semicircular canals, anterior, and posterior semicircular canals, and / or, the diameter of any semicircular canal is less than a fifth diameter threshold, and / or, the diameter of any semicircular canal is greater than a sixth diameter threshold.

[0139] Specifically, semicircular canal malformations include: absence of semicircular canals, hypoplasia of semicircular canals, or enlargement of semicircular canals. If the ear diagnostic module 303 determines that the inner ear does not include the external semicircular canals, and / or the anterior semicircular canals, and / or the posterior semicircular canals, then the absence of semicircular canals can be determined. If the ear diagnostic module 303 determines that the diameter of any semicircular canal is less than the fifth diameter threshold, then the hypoplasia of that semicircular canal can be determined. If the ear diagnostic module 303 determines that the diameter of any semicircular canal is greater than the sixth diameter threshold, then the enlargement of that semicircular canal can be determined.

[0140] The fifth diameter threshold can be less than or equal to the first value, which can be less than or equal to 2 / 3 of the diameter of a normally developing semicircular canal. The fifth diameter threshold can be greater than or equal to the second value, which can be greater than or equal to 1.5 times the diameter of a normally developing semicircular canal.

[0141] Optionally, the output module 302 can be used for:

[0142] Based on the 3D head image, the target ear image of the scanned object is obtained, and the target ear image is labeled with the ear tissues included in the ear of the scanned object;

[0143] Based on the target ear image, output the ear parameters.

[0144] Optionally, the ear includes: the inner ear, the middle ear, and the outer ear. The output module 302 can be used for:

[0145] Based on the three-dimensional head image, the first ear image, the first inner ear image, and the first middle ear image of the scanned object are obtained. The first ear image is marked with at least the ear tissues included in the outer ear, the first inner ear image is marked with the ear tissues included in the inner ear, and the first middle ear image is marked with the ear tissues included in the middle ear.

[0146] The target ear image is obtained based on the first ear image, the first inner ear image, and the first middle ear image.

[0147] Optionally, the output module 302 can be used for:

[0148] Based on the three-dimensional head image, the second inner ear sub-image and the second middle ear sub-image of the scanned object are obtained. The second inner ear sub-image does not label the ear tissues included in the inner ear, and the second middle ear sub-image does not label the ear tissues included in the middle ear.

[0149] The second inner ear image, the second middle ear image, and the outer ear image are stitched together to obtain the second ear image;

[0150] The first ear image is obtained based on the second ear image;

[0151] Based on the second inner ear sub-image, obtain the first inner ear sub-image;

[0152] The first middle ear image is obtained based on the second middle ear image.

[0153] Optionally, the output module 302 can be used for:

[0154] The second inner ear sub-image is input into the inner ear segmentation model to obtain the first inner ear sub-image output by the inner ear segmentation model.

[0155] Optionally, the output module 302 can be used for:

[0156] The second middle ear sub-image is input into the middle ear segmentation model to obtain the first middle ear sub-image output by the middle ear segmentation model.

[0157] Optionally, the output module 302 can be used for:

[0158] The second ear image is input into the ear segmentation model to obtain the first ear image output by the ear segmentation model.

[0159] Optionally, the output module 302 can be used for:

[0160] Determine the locations of key points of the inner ear and key points of the middle ear in the 3D head image;

[0161] Based on the location of key points in the inner ear, the three-dimensional head image is sampled to obtain the second inner ear sub-image of the scanned object;

[0162] Based on the location of key points in the middle ear, the three-dimensional head image is sampled to obtain the second middle ear sub-image of the scanned object.

[0163] As can be seen from the above description, the ear parameter acquisition device provided in this application embodiment can automatically perform ear tissue segmentation, identification, measurement, and ear disease diagnosis, thereby effectively reducing manual operation and improving the efficiency of ear parameter acquisition.

[0164] In summary, this application provides an ear parameter acquisition device. This device can acquire a three-dimensional head image of a scanned object, and then output ear parameters based on the ear tissue included in the ear of the scanned object in the three-dimensional head image. Compared with the method of manually detecting the ear with tools to obtain ear parameters, the device provided in this application can effectively improve the efficiency and flexibility of ear parameter acquisition.

[0165] Figure 6 This is a schematic diagram of the structure of a parameter acquisition device provided in an embodiment of this application. For example... Figure 6As shown, the parameter acquisition device 400 includes a processor 401 and a memory 403. The processor 401 and the memory 403 are connected, for example, via a bus 402. Optionally, the parameter acquisition device 400 may further include a transceiver 404. It should be noted that in practical applications, the transceiver 404 is not limited to one, and the structure of this parameter acquisition device 400 does not constitute a limitation on the embodiments of this application.

[0166] Processor 401 may be a CPU (Central Processing Unit), a general-purpose processor, a DSP (Digital Signal Processor), an ASIC (Application Specific Integrated Circuit), an FPGA (Field Programmable Gate Array), or other programmable logic devices, transistor logic devices, hardware components, or any combination thereof. It can implement or execute the various exemplary logic blocks, modules, and circuits described in conjunction with the disclosure of this application. Processor 401 may also be a combination that implements computational functions, such as including one or more microprocessor combinations, a combination of a DSP and a microprocessor, etc.

[0167] Bus 402 may include a pathway for transmitting information between the aforementioned components. Bus 402 may be a PCI (Peripheral Component Interconnect) bus or an EISA (Extended Industry Standard Architecture) bus, etc. Bus 402 can be divided into address bus, data bus, control bus, etc. For ease of representation, Figure 6 The bus is represented by a single thick line, but this does not mean that there is only one bus or one type of bus.

[0168] The memory 403 stores a computer program corresponding to the ear parameter acquisition method of the above embodiments of this application. This computer program is controlled and executed by the processor 401. The processor 401 executes the computer program stored in the memory 403 to implement the content shown in the foregoing method embodiments.

[0169] This application provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the method for obtaining ear parameters as provided in the above-described method embodiments. For example, Figure 1 or Figure 2 The method shown.

[0170] This application provides a computer program product, which includes a computer program or computer instructions. When executed by a processor, the computer program or computer instructions implement the method for obtaining ear parameters as provided in the above method embodiments. For example, Figure 1 or Figure 2 The method shown.

[0171] It should be noted that the logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as a sequenced list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by, or in conjunction with, an instruction execution system, apparatus, or device (such as a computer-based system, a processor-included system, or other system that can fetch and execute instructions from, an instruction execution system, apparatus, or device). For the purposes of this specification, "computer-readable medium" can be any means that can contain, store, communicate, propagate, or transmit programs for use by, or in conjunction with, an instruction execution system, apparatus, or device. More specific examples (a non-exhaustive list) of computer-readable media include: an electrical connection having one or more wires (electronic device), a portable computer disk drive (magnetic device), random access memory (RAM), read-only memory (ROM), erasable and editable read-only memory (EPROM or flash memory), fiber optic devices, and portable optical disc read-only memory (CDROM). Alternatively, the computer-readable medium may be paper or other suitable media on which the program can be printed, since the program can be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, interpreting, or otherwise processing as necessary, and then stored in a computer memory.

[0172] It should be understood that various parts of this application can be implemented using hardware, software, firmware, or a combination thereof. In the above embodiments, multiple steps or methods can be implemented using software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, it can be implemented using any one or a combination of the following techniques known in the art: discrete logic circuits having logic gates for implementing logical functions on data signals, application-specific integrated circuits (ASICs) having suitable combinational logic gates, programmable gate arrays (PGAs), field-programmable gate arrays (FPGAs), etc.

[0173] In the description of this specification, the references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of this application. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples.

[0174] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one of that feature. In the description of this application, "multiple" means at least two, such as two, three, etc., unless otherwise explicitly specified.

[0175] In this application, unless otherwise expressly specified and limited, the terms "installation," "connection," "joining," and "fixing," etc., should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral part; 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; they can refer to the internal communication of two components or the interaction between two components, unless otherwise expressly limited. Those skilled in the art can understand the specific meaning of the above terms in this application according to the specific circumstances.

[0176] Although embodiments of this application have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting this application. Those skilled in the art can make changes, modifications, substitutions and variations to the above embodiments within the scope of this application.

Claims

1. A method for obtaining ear parameters, characterized in that, The method includes: Acquire a three-dimensional head image of the scanned object, the scanned object having ears; Based on the three-dimensional head image, a target ear image of the scanned object is obtained, and the target ear image is labeled with the ear tissues included in the ear of the scanned object; Based on the target ear image, ear parameters of the ear are output, including: the ear tissue included in the ear of the scanned object; The ear includes the inner ear, middle ear, and outer ear. Based on the three-dimensional head image, obtaining a target ear image of the scanned object includes: obtaining a second inner ear sub-image and a second middle ear sub-image of the scanned object based on the three-dimensional head image, wherein the second inner ear sub-image does not label the ear tissues included in the inner ear, and the second middle ear sub-image does not label the ear tissues included in the middle ear; stitching the second inner ear sub-image, the second middle ear sub-image, and the outer ear sub-image together to obtain a second ear image; obtaining a first ear image based on the second ear image, wherein the first ear image at least labels the ear tissues included in the outer ear; obtaining a first inner ear sub-image based on the second inner ear sub-image, wherein the first inner ear sub-image labels the ear tissues included in the inner ear; obtaining a first middle ear sub-image based on the second middle ear sub-image, wherein the first middle ear sub-image labels the ear tissues included in the middle ear; and obtaining a target ear image based on the first ear image, the first inner ear sub-image, and the first middle ear sub-image.

2. The method according to claim 1, characterized in that, Based on the second inner ear image, the first inner ear image is obtained, including: The second inner ear sub-image is input into the inner ear segmentation model to obtain the first inner ear sub-image output by the inner ear segmentation model.

3. The method according to claim 1, characterized in that, Based on the second middle ear image, the first middle ear image is obtained, including: The second middle ear sub-image is input into the middle ear segmentation model to obtain the first middle ear sub-image output by the middle ear segmentation model.

4. The method according to claim 1, characterized in that, Obtaining a first ear image based on the second ear image includes: The second ear image is input into the ear segmentation model to obtain the first ear image output by the ear segmentation model.

5. The method according to any one of claims 1 to 4, characterized in that, Based on the three-dimensional head image, the second inner ear image and the second middle ear image of the scanned object are obtained, including: The positions of the inner ear key points and the middle ear key points in the three-dimensional head image were determined. Based on the location of the key points in the inner ear, the three-dimensional head image is sampled to obtain a second inner ear sub-image of the scanned object; Based on the location of the key points in the middle ear, the three-dimensional head image is sampled to obtain a second middle ear sub-image of the scanned object.

6. A device for acquiring ear parameters, characterized in that, The device includes: The acquisition module is used to acquire a three-dimensional head image of the scanned object, which has ears; The output module is used to acquire a target ear image of the scanned object based on the three-dimensional head image, wherein the target ear image is labeled with the ear tissue included in the ear of the scanned object; and to output ear parameters of the ear based on the target ear image, wherein the ear parameters include the ear tissue included in the ear of the scanned object. The ear includes the inner ear, middle ear, and outer ear. The process by which the output module acquires a target ear image of the scanned object based on the three-dimensional head image includes: acquiring a second inner ear sub-image and a second middle ear sub-image of the scanned object based on the three-dimensional head image, wherein the second inner ear sub-image does not label the ear tissues included in the inner ear, and the second middle ear sub-image does not label the ear tissues included in the middle ear; stitching the second inner ear sub-image, the second middle ear sub-image, and the outer ear sub-image together to obtain a second ear image; acquiring a first ear image based on the second ear image, wherein the first ear image at least labels the ear tissues included in the outer ear; acquiring a first inner ear sub-image based on the second inner ear sub-image, wherein the first inner ear sub-image labels the ear tissues included in the inner ear; acquiring a first middle ear sub-image based on the second middle ear sub-image, wherein the first middle ear sub-image labels the ear tissues included in the middle ear; and acquiring a target ear image based on the first ear image, the first inner ear sub-image, and the first middle ear sub-image.

7. The apparatus according to claim 6, characterized in that, The device further includes: An ear diagnosis module is used to determine the diagnostic result of the ear based on the ear parameters.

8. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the method as described in any one of claims 1-5.

9. A computer program product, characterized in that, The computer program product includes a computer program that, when executed by a processor, implements the method as described in any one of claims 1-5.

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