CN112396667B - Method for matching electrode positions of retina stimulator - Google Patents

Abstract

The present disclosure relates to a method for matching electrode positions of a retinal stimulator. The retinal stimulator includes a camera device installed outside the eye and a stimulating electrode array implanted in the retina, and is characterized in that it includes the following steps: (a) using the camera device Acquire an initial image with a predetermined number of pixels; (b) collect a fundus photo containing the stimulation electrode array, and obtain the configuration position of the stimulation electrode array on the retina based on the fundus photo; (c) select the initial image and the stimulation electrode array according to the configuration position a corresponding target area; and (d) processing the target area so that the target pixel number of the target area matches the number of electrodes of the stimulation electrode array. Thereby, the position of the output image can be adjusted without changing the hardware.

Description

Matching method of electrode position of retinal stimulator

technical field

The present disclosure particularly relates to a method for matching electrode positions of a retinal stimulator.

Background technique

Retinal diseases such as RP (retinitis pigmentosa), AMD (age-related macular degeneration), etc. are important blinding diseases, and patients suffer from reduced vision or blindness due to obstruction of photoreceptor pathways. With the research and development of technology, the use of retinal stimulators and other technical means to repair the above-mentioned retinal diseases has emerged. Existing retinal stimulators generally include a camera device, an image processing device, and an implant (also referred to as an "implant device") placed in the patient's eyeball outside the patient's body. Wherein, an external camera device captures an external image to obtain an image signal, and an image processing device processes the image signal and sends the processed image signal (also called "visual signal") to the implant. The implant further converts these image signals into electrical stimulation signals to stimulate ganglion cells, or bipolar cells, in the retina, thereby producing light perception in the patient.

However, since the state of the surviving retinal cells of each patient is not consistent, the surgeon needs to choose the most suitable position to place the stimulation electrode array according to the actual situation, so it is possible to set the position of the stimulation electrode array of the implanted device in the patient's eyeball. Deviations such as tilting of the stimulation electrode array with respect to the eye plane can occur. In this case, the correction needs to be performed individually for each patient so that the patient can perceive the normal image perspective.

The existing correction method is usually realized by adjusting the camera module. Specifically, the camera module of the camera device usually does not fix the camera when it leaves the factory. After the clinical operation is completed, the camera device shoots an external T-shaped pattern during the boot-up adaptation process, and then the medical staff rotates the camera module according to the actual patient experience. When the patient can feel the T-shaped pattern, the medical staff then glues and fixes the camera module. However, due to the constant movement of human eyeballs in daily use, the stimulation electrode arrays tend to move slowly after implantation, resulting in skewed output images. Adjust again, causing a bad experience for the patient.

SUMMARY OF THE INVENTION

The present disclosure has been made in view of the above-mentioned situation, and an object thereof is to provide a matching method of the electrode position of a retinal stimulator capable of suppressing repeated modification of the hardware and adjusting the output image position after the electrode is displaced.

To this end, the present disclosure provides a method for matching electrode positions of a retinal stimulator, the retinal stimulator comprising a camera device installed outside the eye and a stimulating electrode array implanted in the retina, characterized in that it includes the following steps: (a) using the camera to acquire an initial image with a predetermined number of pixels; (b) acquiring a fundus photograph containing the stimulating electrode array, and obtaining the arrangement position of the stimulating electrode array on the retina based on the fundus photograph; ( c) selecting a target area corresponding to the stimulation electrode array on the initial image according to the configuration position; and (d) processing the target area so that the target pixel number of the target area is the same as the stimulation electrode array The number of electrodes of the electrode array is matched.

In the present disclosure, a camera device is used to obtain an initial image, and a fundus photo containing the stimulation electrode array is collected, and the configuration position of the stimulation electrode array on the retina can be obtained according to the fundus photo, so as to select the target area corresponding to the initial image, and to assign the target area to the target area. Processing is performed to match the target number of pixels in the target area with the number of electrodes of the stimulating electrode array. Thereby, the position of the output image can be adjusted without adjusting the position of the stimulation electrode array.

In the method for matching electrode positions according to the present disclosure, optionally, before step (b), the method further includes: performing grayscale processing on the initial image to obtain a grayscale image, and performing binary grayscale processing on the grayscale image. processing to obtain a binary image. In this case, even when the number of electrodes is small and the ability to receive information is limited, the image processing can be optimized to retain as much useful image information as possible, such as the contours of objects or obstacles.

In the method for matching electrode positions according to the present disclosure, optionally, before performing the binarization processing, the grayscale image is further subjected to compression processing. In this case, the redundant information of the image can be reduced, and the number of pixels of the image can be reduced, so that useful information of the image can be extracted in the subsequent steps.

In the method for matching electrode positions according to the present disclosure, optionally, the number of pixels in the target area is not less than the number of electrodes in the stimulation electrode array. Thereby, the visible range of the patient can be increased.

In the method for matching electrode positions according to the present disclosure, optionally, in step (d), the target area is compressed so that the target pixel number of the target area is equal to the number of electrodes of the stimulation electrode array. match. As a result, the patient can be better aided in recognizing the image.

In the method for matching electrode positions according to the present disclosure, optionally, in step (d), a plurality of sub-regions having a number of pixels matching the number of electrodes of the stimulating electrode array are selected from the target region. As a result, the patient can be better aided in recognizing the image.

In the method for matching electrode positions according to the present disclosure, optionally, the method further includes periodically collecting a fundus photograph including the stimulation electrode array, and when the configuration position of the stimulation electrode array on the retina changes, obtaining the stimulation again The configuration position of the electrode array in the retina. In this case, after the position of the stimulation electrode array is changed, the patient can see the image from the normal viewing angle without changing the hardware.

In the method for matching electrode positions according to the present disclosure, optionally, the configuration position is an inclination angle of the stimulation electrode array relative to the horizontal plane when the eye is looking straight ahead. Thus, the corresponding target area on the initial image can be selected according to the inclination angle of the stimulation electrode array.

In the method for matching electrode positions according to the present disclosure, optionally, the predetermined number of pixels is greater than the target number of pixels. Thereby, the visible range of the patient can be increased.

In the method for matching electrode positions according to the present disclosure, optionally, the stimulation electrode array is arranged on the retina. Thus, the retina can be stimulated to generate light perception by stimulating the electrodes on the electrode array.

According to the matching method involved in the present disclosure, a patient can see an image of a normal viewing angle without changing the hardware.

Description of drawings

FIG. 1 is a schematic diagram showing the structure of a retinal stimulator according to an example of the present disclosure.

FIG. 2 is a schematic flowchart illustrating a method of matching electrode positions according to an example of the present disclosure.

FIG. 3 is a schematic diagram illustrating a preprocessing flow of an initial image involved in an example of the present disclosure.

FIG. 4 is a schematic diagram showing a procedure in a compression process involved in an example of the present disclosure.

FIG. 5 is a schematic diagram showing the arrangement position of the stimulation electrode array in the fundus photograph according to the example of the present disclosure.

FIG. 6 is a schematic diagram showing a target area of a stimulation electrode array involved in an example of the present disclosure in a dot matrix corresponding to an initial image.

Detailed ways

Hereinafter, preferred embodiments of the present disclosure will be described in detail with reference to the accompanying drawings. In the following description, the same reference numerals are assigned to the same components, and overlapping descriptions are omitted. In addition, the drawings are only schematic diagrams, and the ratios of the dimensions of the members, the shapes of the members, and the like may be different from the actual ones.

In addition, the subheadings and the like mentioned in the following description of the present disclosure are not intended to limit the content or scope of the present disclosure, but only serve as a reminder for reading. Such subheadings can neither be understood to be used to divide the content of the article, nor should the content under the subheadings be limited to the scope of the subheadings.

The present disclosure provides a method for matching electrode positions of a retinal stimulator. In the present disclosure, the target area corresponding to the stimulation electrode array can be corrected many times after the clinical operation, thereby improving the phenomenon of image skew due to the relative displacement of the electrodes. The present disclosure will be described in detail below with reference to the accompanying drawings.

FIG. 1 is a schematic diagram showing the structure of a retinal stimulator according to an example of the present disclosure. For example, the retinal stimulator 1 involved in the present disclosure may be particularly suitable for patients with blindness caused by retinopathy but with intact visual pathways such as bipolar cells and ganglion cells. In the present disclosure, the retinal stimulator 1 is also sometimes referred to as "artificial retina", "artificial retina", "artificial retinal system", "artificial retinal system" and the like.

In some examples, as shown in FIG. 1 , retinal stimulator 1 may include implant device 10 , camera device 20 and image processing device 30 . Implant device 10 may receive visual signals and generate electrical stimulation signals based on the visual signals to induce light perception in the patient. Wherein, the visual signal may be collected by the camera device 20 and processed and obtained by the image processing device 30 .

In some examples, implant device 10 may include stimulation electrode array 11 (see Figure 5). The stimulation electrode array 11 may include a predetermined number of stimulation electrodes (sometimes referred to as "electrodes"). (Refer to Figure 5). The stimulation electrodes can generate electrical stimulation signals based on visual signals. Specifically, the implanted device 10 can receive visual signals, and the stimulation electrodes can convert the received visual signals into bidirectional pulsed current signals as electrical stimulation signals, so as to emit bidirectional pulsed currents to ganglion cells or bipolar cells of the retina signal to generate light perception. Additionally, the implant device 10 may be implanted in a human body such as the eyeball.

In some examples, the visual signal received by the implant device 10 may be acquired and processed by the camera device 20 and the image processing device 30 .

In some examples, camera 20 may be used to capture images and convert the captured images into visual signals. For example, camera 20 may capture images of the environment in which the patient is located.

In some examples, the camera 20 may be a device having a camera function, such as a video camera, a camera, and the like. For ease of use, smaller cameras can be designed (eg embedded into) glasses.

In other examples, the patient may also capture images by wearing lightweight camera-enabled glasses as the camera device 20 . The camera 20 can also be implemented with Google Glass or the like. In addition, the camera device 20 may be mounted on smart wearable devices such as smart glasses, smart headsets, and smart bracelets.

In some examples, image processing device 30 may receive visual signals generated by camera device 20 . The image processing device 30 may process the visual signal and send it to the implant device 10 via the transmit antenna.

In some examples, the image processing device 30 may be connected to the camera device 20 . The connection between the imaging device 20 and the image processing device 30 may be a wired connection or a wireless connection. The wired connection may be a data line connection, and the wireless connection may be a Bluetooth connection, a WiFi connection, an infrared connection, an NFC connection, or a radio frequency connection, and the like.

In some examples, the camera device 20 and the image processing device 30 may be configured outside the patient's body. For example, the patient may wear the camera device 20 on glasses. The patient may also wear the camera device 20 on a wearable accessory such as a headgear, hair band, or brooch. In addition, the patient can wear the image processing device 30 on the waist, and the patient can also wear the image processing device 30 on parts such as arms and legs. Examples of the present disclosure are not limited thereto, for example, the patient may also place the image processing apparatus 30 in, for example, a handbag or a backpack that is carried around.

Hereinafter, the process of the matching method of the electrode positions of the retinal stimulator 1 will be described in detail with reference to the accompanying drawings. The matching method of the electrode positions of the retinal stimulator 1 involved in the present disclosure may be simply referred to as the matching method of the electrode positions. FIG. 2 is a schematic flowchart illustrating a method of matching electrode positions according to an example of the present disclosure. FIG. 3 is a schematic diagram illustrating a preprocessing flow of an initial image involved in an example of the present disclosure.

In this embodiment, as shown in FIG. 2 , the method for matching the electrode positions of the retinal stimulator 1 includes the following steps: (a) using the camera 20 to acquire an initial image with a predetermined number of pixels (step S10 ); (b) Collect a fundus photo containing the stimulation electrode array 11, and obtain the configuration position of the stimulation electrode array 11 on the retina based on the fundus photo (step S20); (c) select a target area M corresponding to the stimulation electrode array 11 on the initial image according to the configuration position (step S30 ); and (d) processing the target area M so that the target pixel number of the target area M matches the number of electrodes of the stimulation electrode array 11 (step S40 ).

In the method for matching the electrode positions of the retinal stimulator 1 according to the present embodiment, without changing the hardware (for example, readjusting the camera module), if the stimulation electrode array 11 is skewed after the clinical operation, many The target area M corresponding to the stimulation electrode array 11 is corrected, so that the patient can see an image with a normal viewing angle.

In step S10 , an initial image with a predetermined number of pixels may be acquired by using the camera 20 . As mentioned above, the imaging device 20 may be a camera.

In some examples, the initial image is, for example, the external environment in which the patient is located, such as a life scene, a traffic scene, and the like. The desired initial image can be captured by photographing the external environment by the camera device 20 . In other examples, the camera 20 may capture an initial image every preset time T.

In this embodiment, the predetermined number of pixels of the initial image may be, for example, 300,000, 1,000,000, 2,000,000, 5,000,000, 12,000,000, etc., but this embodiment is not limited thereto. In some examples, the number of electrodes of stimulation electrode array 11 may be 16, 20, 32, 60, 128, 256, 1200, and so on. In this case, the predetermined number of pixels of the initial image may be greater than the number of electrodes of the stimulation electrode array 11 .

In some examples, the initial image may be an image captured by the camera 20 without any processing. Usually, the initial image obtained by photographing the surrounding environment by the camera 20 is a color image. That is, the original image captured by the camera 20 without any processing may be a color image. In some examples, the color images may be HSI images. Color images can also be RGB images. However, the example of the present disclosure is not limited thereto, and the initial image captured by the camera 20 may be a grayscale image or a binary image, or the like.

Generally speaking, the presence of objects or obstacles in the initial image is the information that the patient is mainly interested in, especially identifying the outlines of objects or obstacles can facilitate the actions of blind or low-vision patients. On the one hand, not all information such as color features in the color image can be used to reflect the morphological features of the object in the original image, so even if some of the above information in the color image is removed, the outline of the object or obstacle can be better preserved. On the other hand, the number of electrodes of the stimulation electrode array 11 in the implanted device 10 of the retinal stimulator 1 is still relatively small, such as 60, 100, 150 or 256 electrodes.

In general, it is difficult for a relatively small number of electrodes to fully transmit all the information of the initial image, and it is often difficult to transmit information such as the contours of objects or obstacles in the initial image. In such a case, if the information with a large number of pixels in the initial image is directly corresponding to the extremely limited number of stimulation electrodes in the implanted device 10 of the retinal stimulator 1, the number of stimulation electrodes cannot fully reflect the information of the pixels in the initial image. Therefore, it is easy to cause serious distortion of the image. Based on this, by performing grayscale processing and binarization processing on the initial image, the present disclosure can optimize the processing of the initial image even when the number of stimulation electrodes is small and the ability to receive information is limited. Image useful information such as outlines of objects or obstacles.

In some examples, in step S10, the initial image may be preprocessed. As shown in FIG. 3 , a grayscale image may be obtained by performing grayscale processing on the initial image (step S11 ). In addition, a binary image can also be obtained by performing a binarization process on the grayscale image (step S12). In addition, the grayscale image may also be compressed (step S13). In some examples, the preprocessing of the initial image may be implemented by the image processing device 30 .

In some examples, the grayscale image may be a special color image with three components of R, G, and B having the same size (ie, the value of R=G=B), and has less information than ordinary color images. Each pixel of a grayscale image has a corresponding grayscale value. In some examples, each grayscale value may be represented by, for example, an 8-bit binary number, that is, the grayscale value of the grayscale image ranges from 0-255. In other examples, each gray value can also be represented by, for example, a 16-bit binary number, and in addition, it can also be represented by, for example, a 24-bit or more binary number.

In some examples, the grayscale processing in step S11 mainly processes the color information of the initial image, and does not change the initial image information other than the color information. For example, grayscale processing can help to highlight useful image information in the initial image during subsequent processing, such as morphological feature information of objects or obstacles in the initial image.

In some examples, the grayscale processing method may be a component method, that is, the value of any one of the three components of R, G, and B may be selected as the grayscale value. For example, for a pixel in the initial image, if R=70, G=110, B=150, for example, 70 can be selected as the gray value of the pixel, that is, set R=G=B=70 as the pixel The gray value of the pixel; for example, 110 can also be selected as the gray value of the pixel, or 150 can be selected as the gray value of the pixel. In this case, a grayscale image can be obtained by sequentially processing each pixel in the original image.

In addition, in some examples, the grayscale processing method may also be a maximum value method, that is, the maximum value among the three components of R, G, and B may be selected as the grayscale value. For example, for a pixel in the initial image, if R=70, G=110, and B=150, for example, 150 can be selected as the grayscale value of the pixel. In this case, a grayscale image can be obtained by sequentially processing each pixel in the original image.

In addition, in some examples, the grayscale processing method may also be an average value method, that is, the average value of the three components of R, G, and B may be selected as the grayscale value. For example, for a pixel in the initial image, if R=70, G=110, B=150, then the average of the three values of R, G, and B is 110, and 110 can be selected as the gray value of the pixel . In this case, a grayscale image can be obtained by sequentially processing each pixel in the original image.

In addition, in some examples, the grayscale processing method may also be a weighting method, that is, the three components of R, G, and B may be weighted and calculated according to different weighting coefficients to obtain grayscale values. For example, for a pixel in the initial image, if R=70, G=110, B=150, the weighting coefficient of R can be set to 0.3, the weighting coefficient of G is 0.5, and the weighting coefficient of B is 0.2, then the The grayscale value of the pixel is 0.3*70+0.5*110+0.2*150=106. In this case, a grayscale image can be obtained by sequentially processing each pixel in the original image.

In the above example, the grayscale processing can reduce the amount of data (or information) of the initial image, facilitate subsequent processing of the image, and help to highlight useful image information in the initial image during subsequent processing. The useful information of the image can be, for example, contour information of objects or obstacles.

In addition, for the implanted device 10 of the retinal stimulator 1, since it needs to be implanted into the eyeball, the size of the implanted device 10 is severely limited, and the number of stimulating electrodes in the stimulating electrode array 11 in the implanted device 10 is also relatively large. few. Therefore, by binarizing the grayscale image, a binary image is obtained, so as to effectively transmit the information of the pixel to each stimulation electrode. For example, if the electrical stimulation signal is at a low level, it may correspond to a pixel with a grayscale value of 0, and if the electrical stimulation signal is at a high level, it may correspond to a pixel with a grayscale value of 255. However, the examples of the present disclosure are not limited thereto. For example, if the electrical stimulation signal is at a high level, it may correspond to a pixel with a grayscale value of 0, and if the electrical stimulation signal is at a low level, it may correspond to a pixel with a grayscale value of 255.

In some examples, the binarization process in step S12 may include comparing the grayscale value of each pixel in the grayscale image with the size of a preset grayscale value. The grayscale value in the grayscale image can be set to two types, namely the maximum grayscale value and the minimum grayscale value. After changing the grayscale value, a binary image can be obtained. In some examples, the preset gray value can be set by the relevant personnel or determined by the relevant algorithm of the used software. In this case, a grayscale image can be binarized to obtain a binary image.

In some examples, in the process of preprocessing the initial image, grayscale processing is performed on the initial image to obtain a grayscale image, but the grayscale image still includes a lot of useful information relative to the image such as the outline of an object or an obstacle. Redundant information, for example, spatial redundancy caused by correlation between adjacent pixels in a grayscale image. The number of pixels of a grayscale image can be reduced through compression processing, and the complexity of subsequent image processing (eg, binarization processing) can be reduced, so that useful information of the image can be extracted in subsequent steps.

In some examples, as shown in FIG. 3 , before the binarization process (step S12 ), the grayscale image may also be compressed (step S13 ), that is, the grayscale image is compressed to obtain low-pixel grayscale image, so that the number of pixels in the compressed grayscale image is reduced, so that useful information of the image can be easily extracted in subsequent steps. In some examples, the number of steps of the compression process may be greater than or equal to two steps.

In some examples, the step of compressing (step S13 ) may include: first performing partition processing on the grayscale image to obtain multiple grayscale image regions Y; Y calculates the average gray value of the pixel, and takes the average gray value as the gray value of the gray image area Y; takes each gray image area Y of the gray image as a pixel with an average gray value to obtain Low pixel grayscale image. In this case, by compressing the grayscale image, useful information of the image can be extracted in subsequent steps.

For example, the pixels of the grayscale image are 160*144. In order to facilitate the extraction of useful information of the image in the subsequent steps, the pixels of the grayscale image can be reduced to 20*18 through the compression process described above. FIG. 4 is a schematic diagram showing a procedure in a compression process involved in an example of the present disclosure. As shown in Figure 4, a grayscale image with a pixel size of 160*144 can be divided into 20*18 grayscale image areas Y. Each grayscale image area Y contains 8*8 pixels. Figure 4 shows the 8*8 pixels contained in a grayscale image area y in the grayscale image area y and the grayscale values of each pixel. The average grayscale value of the grayscale image area y can be calculated. The image area y is regarded as a pixel, and the average gray value is regarded as the gray value of the pixel. The grayscale values of other grayscale image regions Y can be obtained like the grayscale image region y, thereby obtaining a low-pixel grayscale image. The low-pixel grayscale image can then be binarized. In some examples, the number of pixels of the compressed low-pixel grayscale image should not be less than the number of stimulation electrodes in the stimulation electrode array 11 .

However, the examples of the present disclosure are not limited thereto, and other compression methods may be used in addition to the above-mentioned compression methods. For example, in some examples, the step of compressing (step S13 ) may include: first performing partition processing on the grayscale image to obtain a plurality of grayscale image areas Y, each grayscale image area Y includes a plurality of pixels; Calculate the average gray value of the pixel in any gray image area Y among the gray image areas Y, and use the average gray value as the gray value of the gray image area Y; The intensity value is compared with the preset average gray value to determine the effective gray image area Y' in the gray image area Y; the effective gray image area Y' is regarded as a pixel with an average gray value, and each pixel Combined sequentially to obtain low-pixel grayscale images. In this case, by performing a first compression process on the grayscale image, useful information of the image can be extracted in subsequent steps.

As mentioned above, compared with the grayscale image before compression, the low-pixel grayscale image after compression processing has a reduced number of pixels, and can correspondingly reduce the number of pixels between adjacent pixels in the grayscale image. Redundancy of image data caused by correlation. Thereby, useful information of the image can be extracted in subsequent steps.

In some examples, both the compression processing and the binarization processing described above may be implemented using image processing algorithms arranged in an FPGA (Field Programmable Gate Array). In the field of image processing, FPGA can have the advantages of high reliability, good flexibility, high throughput, short development cycle and low risk, and can greatly reduce the size and power consumption of the system, and can realize high-speed real-time image compression. In addition, the above-mentioned compression processing and binarization processing can also be implemented using an application specific integrated circuit (ASIC), a software program arranged on a computer, or the like.

FIG. 5 is a schematic diagram showing the arrangement position of the stimulation electrode array 11 in the fundus photograph according to the example of the present disclosure.

In step S20 , as shown in FIG. 5 , a fundus photograph including the stimulation electrode array 11 may be collected, and the configuration position of the stimulation electrode array 11 on the retina may be acquired based on the fundus photograph. In some examples, the stimulation electrode array 11 may be implanted into and attached to the retina by clinical surgery. In general, due to the different states of the surviving retinal cells of each patient, the surgeon will select the most suitable position to place the stimulation electrode array 11 according to the actual situation of the patient during clinical operation, so the configuration positions of the stimulation electrode array 11 for different patients are will be biased. The arrangement position is the inclination angle of the stimulation electrode array 11 with respect to the horizontal plane when the eyes are looking straight ahead. In this case, the inclination angle θ of the stimulation electrode array 11 implanted in the retina of the patient with respect to the horizontal plane L (also referred to as "horizontal plane L") when the eye is looking straight ahead will be different. For example, the inclination angle θ of the stimulation electrode array 11 may be 0°, 10°, 15°, 30°, 60°, 90°, 135°, or the like.

In some examples, after the stimulation electrode array 11 is implanted into the retinal fundus, fundus photographs are taken by a fundus camera (eg, a Topcon TRC-NW400). The acquired fundus photograph includes the stimulation electrode array 11 , especially the arrangement position of the stimulation electrode array 11 on the retina. In this case, the inclination angle θ of the stimulation electrode array 11 with respect to the horizontal plane L can be obtained by analyzing the fundus photograph.

In some examples, a fundus photograph containing the stimulating electrode array 11 may also be periodically collected, so as to periodically know whether the configuration position of the stimulating electrode array 11 on the retina changes. Thus, the arrangement position of the stimulation electrode array on the retina in step S20 can be regularly updated. When the arrangement position of the stimulation electrode array 11 on the retina changes, the arrangement position of the stimulation electrode array 11 on the retina can be acquired again.

Additionally, in some examples, the stimulation electrode array 11 may be disposed on the retina. In other examples, the stimulation electrode array 11 may also be arranged under the retina.

In step S30, the target area corresponding to the stimulation electrode array 11 on the initial image (or the preprocessed initial image) may be selected according to the configuration position in step S20.

FIG. 6 is a schematic diagram showing the target area of the stimulation electrode array 11 involved in the example of the present disclosure in the dot matrix corresponding to the initial image. In some examples, as shown in FIG. 6 , the image processing apparatus 30 may draw a dot matrix X corresponding to the initial image through software, and the dot matrix X may correspond to the pixels of the initial image. For example, one square in lattice X in Figure 6 may represent one pixel of the original image. And select the target area M corresponding to the stimulation electrode array 11 in the dot matrix X of the initial image through the inclination angle θ of the stimulation electrode array 11 .

In some examples, as shown in FIG. 6 , the shape of the target area M may be the same as the shape of the stimulation electrode array 11 , for example, in the case where the shape of the stimulation electrode array 11 is rectangular, the shape of the target area M may be rectangular. In some examples, the inclination angle Δ of the target area M relative to the horizontal plane L in the lattice X may be the same as the inclination angle θ of the stimulation electrode array 11 . In this case, it can be achieved that the target area M corresponds to the stimulation electrode array 11. For example, the corresponding area a and the corresponding area b shown in FIG. 6 may correspond to the stimulation electrodes 111 and 11 in the stimulation electrode array 11 shown in FIG. Stimulation electrodes 112 .

In some examples, the actual range occupied by the selected target area M in the lattice X can be set manually. In some examples, the actual range occupied by the selected target area M in the dot matrix X may be smaller than the number of electrodes of the stimulation electrode array 11, that is, the number of pixels of the target area M is smaller than the number of electrodes of the stimulation electrode array 11 ( not shown). In some examples, the actual range occupied by the selected target area M in the lattice X may not be less than the number of electrodes of the stimulation electrode array 11 (as shown in FIG. 6 ), that is, the number of pixels in the target area M may not be less than the number of electrodes in the stimulation electrode array 11 (as shown in FIG. 6 ). The number of electrodes in the electrode array 11 . For example, the number of electrodes of the stimulation electrode array 11 in the implanted device 10 of the retinal stimulator 1 may be 60, 100, 150, or 256, etc. The number of pixels of the target area M may be less than or not less than 60, 100, 150 or 256, etc.

In some examples, since the arrangement position of the stimulation electrode array on the retina in step S20 is regularly updated (the regularly updated arrangement position may not change or may change), therefore, the target area is also regularly updated.

In step S40 , the target area M may be processed so that the target pixel number of the target area M matches the number of electrodes of the stimulation electrode array 11 . In some examples, the predetermined number of pixels of the initial image should be greater than the target number of pixels of the target area M.

In some examples, the number of pixels of the target area M may be less than or equal to the number of electrodes of the stimulation electrode array 11 . In this case, according to the positional correspondence between the target area M and each electrode in the stimulation electrode array 11 (not shown), each pixel of the target area M can completely correspond to the electrodes in the stimulation electrode array 11, Thus, the information corresponding to each pixel is transmitted to each stimulation electrode for stimulation. The information corresponding to each pixel can be determined by the gray value corresponding to each pixel. For example, if the electrical stimulation signal is at a low level, it may correspond to a pixel with a grayscale value of 0, and if the electrical stimulation signal is at a high level, it may correspond to a pixel with a grayscale value of 255. However, the examples of the present disclosure are not limited thereto. For example, if the electrical stimulation signal is at a high level, it may correspond to a pixel with a grayscale value of 0, and if the electrical stimulation signal is at a low level, it may correspond to a pixel with a grayscale value of 255. In this case, it is possible to make the patient feel the image of the normal viewing angle.

In some examples, the number of pixels of the target area M may be greater than the number of electrodes of the stimulation electrode array 11 . In this case, the target area M can be compressed so that the pixels of the target area M have the target number of pixels and match the number of electrodes of the stimulation electrode array 11, and the information corresponding to each pixel of the compressed target area M can be delivered to each stimulation electrode for stimulation.

In step S40, the compression method of the compression process in step S13 may be used. For example, the compression process may include: first performing partition processing on the target area M to obtain a plurality of corresponding areas m (not shown); The average gray value is used as the gray value of the corresponding area m; the processing of the target area M can be completed by taking each corresponding area m of the target area M as a pixel with an average gray value. In some examples, the number of divided corresponding regions m may not be greater than the number of electrodes of the stimulation electrode array 11 . In this case, the pixels corresponding to the compressed target area M can have the target number of pixels, and match the number of electrodes of the stimulation electrode array 11 .

In some examples, the target area M may be divided into a plurality of corresponding areas m as described above in the compression process. Part of the corresponding area m shown in FIG. 6 is, for example, the corresponding area a and the corresponding area b. The average gray value of the pixels in the corresponding area a and the corresponding area b can be obtained respectively, and the respective average gray value is used as the gray value of the corresponding area a and the corresponding area b, respectively, and the corresponding area a and the corresponding area b are respectively As a pixel with its average gray value, the same processing can be performed on other areas (not shown), and then the processing on the target area M can be completed. For example, the compressed pixels of the corresponding area a can be matched with the stimulation electrodes 111 of the stimulation electrode array 11 in FIG. 5 , and can be transmitted through the information corresponding to the compressed pixels of the corresponding area a (ie, the average gray value of the corresponding area a) Go to the stimulation electrode 111 for stimulation; the compressed pixels of the corresponding area b can be matched with, for example, the stimulation electrodes 112 of the stimulation electrode array 11 in FIG. average gray value) to the stimulation electrodes 112 for stimulation. If each corresponding area m stimulates the patient with corresponding information through the corresponding stimulating electrode, the patient can feel the useful information of the image corresponding to the target area M.

For example, in some examples, another compression method of the compression processing in step S10 may be adopted, and the compression processing step may include: firstly performing partition processing on the target area M to obtain a plurality of corresponding areas m, each corresponding area m Including a plurality of pixels; calculating the average gray value of the pixel for any corresponding area m among the plurality of corresponding areas m, and taking the average gray value as the gray value of the corresponding area m; taking the average gray value of each corresponding area m The value is compared with the preset average gray value, and the effective corresponding area m' of the corresponding area m is determined; the effective corresponding area m' is regarded as a pixel with an average gray value, and each pixel is combined in order to complete the target area. Treatment of M. In this case, the pixels corresponding to the divided sub-regions can have the target number of pixels, and match the number of electrodes of the stimulation electrode array 11 .

However, the examples of the present disclosure are not limited thereto, and other compression methods may be used in addition to the above-mentioned compression methods. The above-mentioned compression method compresses the target area M, so that the patient can feel the useful information of the image corresponding to the target area M.

In some examples, the number of pixels of the target area M may be greater than the number of electrodes of the stimulation electrode array 11 , and a plurality of sub-areas having a number of pixels matching the number of electrodes of the stimulation electrode array 11 may be selected from the target area M. The corresponding pixels in each sub-area can match the number of electrodes of the stimulation electrode array 11, and any sub-area can be selected from the plurality of sub-areas as the target corresponding area to transmit the corresponding information to the corresponding stimulation electrodes respectively. Stimulate.

In some examples, the above-mentioned processing method of the target area M, as shown in FIG. 6 , may divide the target area M into sub-areas Q and other areas except the sub-area Q in the target area M, so that the sub-area Q The number of pixels in each of the other regions can be matched with the number of electrodes in the stimulation electrode array 11 . For example, the corresponding pixels in the sub-region Q and other regions can be the same as the number of electrodes in the stimulation electrode array 11 , so that the pixels in the sub-region Q or other regions can be in one-to-one correspondence with the electrodes in the stimulation electrode array 11 . In this case, the sub-region Q and other regions can be selected as the target corresponding regions in turn, and the information corresponding to each pixel in the respective region can be transmitted to the one-to-one corresponding stimulation electrodes for stimulation, so that the patient can feel the sub-region Q respectively. and corresponding image useful information in other regions.

In some examples, after the stimulation electrode array 11 is implanted in the retina, the constant movement of the eyeball may cause the stimulation electrode array 11 to slowly move and skew the image perceived by the patient. In the present disclosure, the fundus photos containing the stimulation electrode array 11 can be periodically collected, and when the configuration position of the stimulation electrode array 11 in the retina changes, the configuration position of the stimulation electrode array 11 in the retina can be acquired again, and the stimulation electrode array 11 can be re-determined The target area M in the dot matrix X, so as to dynamically adjust the position of the output image (ie, the target area), can make the patient see an image with a normal viewing angle without changing the hardware.

Although the present disclosure has been specifically described above with reference to the accompanying drawings and embodiments, it should be understood that the above description does not limit the present disclosure in any form. Those skilled in the art can make modifications and changes of the present disclosure as required without departing from the essential spirit and scope of the present disclosure, and these modifications and changes all fall within the scope of the present disclosure.

Claims (9)

1. the matching method of the electrode position of a kind of retinal stimulator, described retinal stimulator comprises the camera device that is installed outside eye and the stimulation electrode array that is implanted in retina, it is characterised in that, Include the following steps: (a) using the camera to acquire an initial image with a predetermined number of pixels; (b) using a fundus camera to acquire a fundus photograph containing the stimulating electrode array, and obtaining a configuration position of the stimulating electrode array on the retina based on the fundus photograph, where the configuration position is that the stimulating electrode array is facing forward with respect to the eye the inclination angle of the horizontal plane; (c) selecting a target area corresponding to the stimulation electrode array on the initial image according to the configuration position; and (d) processing the target area to match the target number of pixels of the target area with the number of electrodes of the stimulation electrode array. 2. matching method according to claim 1, is characterized in that: Before step (b), the method further includes performing grayscale processing on the initial image to obtain a grayscale image, and performing binarization processing on the grayscale image to obtain a binary image. 3. matching method according to claim 2, is characterized in that: Before performing the binarization processing, the grayscale image is also subjected to compression processing. 4. matching method according to claim 1, is characterized in that: The number of pixels in the target area is not less than the number of electrodes in the stimulation electrode array. 5. matching method according to claim 1, is characterized in that: In step (d), the target area is compressed so that the target pixel number of the target area matches the number of electrodes of the stimulation electrode array. 6. matching method according to claim 1, is characterized in that: In step (d), a plurality of sub-regions having a number of pixels matching the number of electrodes of the stimulating electrode array are selected from the target region. 7. matching method according to claim 1, is characterized in that: It also includes periodically collecting the fundus photos including the stimulating electrode array, and acquiring the configuration position of the stimulating electrode array on the retina again when the configuration position of the stimulating electrode array on the retina changes. 8. matching method according to claim 1, is characterized in that: The predetermined number of pixels is greater than the target number of pixels. 9. matching method according to claim 1, is characterized in that: The stimulation electrode array is arranged on the retina.

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