Medical Image Protection Method Based on Integer Wavelet Transform and Steganography in the Encryption Domain

Abstract

The present invention proposes a method for protecting medical images based on integer wavelet transform and steganography in the encrypted domain. In order to retain a certain degree of readability while protecting the privacy of medical images, the present invention proposes a method for protecting medical images based on integer wavelet transform and steganography in the encrypted domain. The method of the present invention can not only effectively protect the security of encrypted medical images, but also provide a degraded version of the visual input to assist cloud managers in archiving and managing images. Compared with traditional image encryption, the proposed scheme of the present invention facilitates the management and archiving of images on the cloud and has relatively superior performance.

Description

Technical Field

[0001] The present invention belongs to the field of cloud-based medical image security, and specifically relates to a method for protecting medical images based on integer wavelet transform and encryption domain steganography. Background Art

[0002] With the rapid development of 5G technology, cloud storage has broad application prospects in the field of data sharing due to its economic, efficient and scalable characteristics. Data shows that medical imaging data accounts for as much as 85% to 90% of medical big data. It can be said that the cloud of medical imaging is the key to breaking the medical information island, enabling hospital-doctor-patient links, and realizing remote consultation, remote diagnosis, intelligent auxiliary diagnosis and other link-based medical applications, and helping to achieve hierarchical diagnosis and treatment. At present, governments and medical institutions of various countries are committed to building a safe, efficient and practical medical cloud data management platform to help the digital transformation of the medical industry. However, due to the particularity of medical data, how to balance privacy and practicality has become a huge challenge.

[0003] To protect medical images stored in the cloud, traditional methods use an obfuscation-diffusion architecture to encrypt medical images to protect the content of the image from being destroyed. On this basis, there are also methods that can embed additional data into the encrypted image, such as the patient's personal information and diagnosis records, to promote the improvement of diagnostic efficiency. Although this method provides a high degree of privacy, it still has its limitations. For example, cloud managers cannot organize and manage encrypted images by his / her visual content, and users must download and decrypt encrypted images to access the image content. In other words, this makes the encrypted image lose its usability. As medical data becomes more and more massive, this will bring a great burden to the management and classification of medical images. Therefore, traditional encrypted domain steganography is not a perfect solution for cloud-based medical image management. Summary of the invention

[0004] In order to protect the privacy of medical images while retaining a certain degree of readability, this paper proposes a method for protecting medical images based on integer wavelet transform (IWT) and encrypted domain steganography. Our method can not only effectively protect the security of encrypted medical images, but also provide a degraded visual input to assist cloud managers in archiving and managing images. Experimental results show that compared with traditional image encryption, the scheme proposed in this paper facilitates cloud managers to manage and archive images on the cloud and has superior performance.

[0005] The technical solution steps of the present invention are as follows:

[0006] A medical image protection method based on integer wavelet transform and encryption domain steganography is used to provide privacy protection for medical images stored in the cloud while providing a certain degree of readability. The specific steps are as follows:

[0007] S1: The medical center management terminal performs integer wavelet transform on the acquired medical images;

[0008] S2: The medical center management end performs run-length coding on the medium-high frequency area and high frequency area of ​​the medical image after integer wavelet transform;

[0009] S3: The medical center management end encrypts the travel code, fills the encrypted travel code into the original medium-high frequency area and high-frequency area in the medical image, generates a visualized encrypted medical image, and uploads it to the cloud;

[0010] S4: The doctor at the first visit hospital downloads the visualized encrypted medical image from the cloud by sending a download request, and decrypts, decodes and inverses integer wavelet transforms the downloaded visualized encrypted medical image to obtain the original medical image for medical diagnosis and thus generating a diagnosis record;

[0011] S5: The doctor at the first visit hospital encrypts the diagnosis record and embeds it into the downloaded visualized encrypted medical image, generates a visualized encrypted medical image carrying the diagnosis record, and uploads it to the cloud;

[0012] S6: The pharmacist at the first visit hospital downloads the visualized encrypted medical image of the payload diagnosis record from the cloud by sending a download request, and decrypts the diagnosis record according to his authority, so as to provide drugs to the patient according to the diagnosis record;

[0013] S7: The doctor at the secondary visit hospital downloads the visualized encrypted medical image of the payload diagnosis record from the cloud by sending a download request, and decrypts, decodes, and inverses integer wavelet transforms according to his authority to obtain the original medical image and perform a secondary diagnosis.

[0014] Preferably, in S1, the method by which the medical center management terminal performs integer wavelet transform on the acquired medical image is as follows:

[0015] The medical center management end iterates K times of Haar wavelet transform on the original medical image to generate an image after K times of Haar wavelet transform. During the iterative process, each Haar wavelet transform will generate corresponding low-frequency areas, horizontal medium-high frequency areas, vertical medium-high frequency areas and high-frequency areas, and the i-th Haar wavelet transform needs to be performed on the low-frequency area generated by the i-1th Haar wavelet transform, i = 2, 3..., K; finally, the low-frequency area generated by the K-th Haar wavelet transform is used as the visualization area of ​​the image.

[0016] Preferably, in S2, the medical center management terminal performs run length coding on the medium-high frequency area and the high frequency area of ​​the medical image converted by integer wavelet transform as follows:

[0017] S21: The medical center management terminal converts the image after K-times Haar wavelet transformation in the original medical image into 8 value bit planes and 1 sign bit plane;

[0018] S22: for each value bit plane, respectively obtain the horizontal medium and high frequency area, the vertical medium and high frequency area and the high frequency area generated in each iteration, and read the bit values ​​from the three areas generated in each iteration in the order of the horizontal medium and high frequency area, the vertical medium and high frequency area and the high frequency area, and concatenate them into a sequence to be encoded, so that each value bit plane generates K sequences to be encoded with inconsistent lengths;

[0019] S23: For each sequence to be encoded, use run-length coding to encode it. If it is encodable, record the run-length coding sequence obtained after encoding and mark the sequence as 1 in the mark sequence. If it is not encodable, record the original sequence to be encoded and mark the sequence as 0 in the mark sequence; finally, an 8×K-bit binary mark sequence is obtained.

[0020] Preferably, in S3, the medical center management terminal encrypts the code, fills the encrypted travel code into the original medium-high and high-frequency areas, generates a visual encrypted medical image, and uploads it to the cloud as follows:

[0021] S31: The medical center management terminal extracts the least significant bits of the first 8×K pixels from the low-frequency area generated by the K-th Haar wavelet transform, and sequentially fills the 8×K-bit binary mark sequence obtained in S23 into it, thereby forming a visualization area of ​​the visualized encrypted medical image;

[0022] S32: The least significant bit of the 8×K pixels extracted in S31, the run-length coding sequence generated in S23, and the sign bit plane generated in S21 are concatenated to generate a concatenated sequence, and the concatenated sequence is encrypted with the image encryption key. The encrypted concatenated sequence is then filled into the horizontal medium and high frequency areas, the vertical medium and high frequency areas, and the high frequency areas generated by each iteration in the order of the bit planes from large to small and K from large to small, and the redundant space is filled with random binary codes, and finally a visual encrypted medical image is generated and uploaded to the cloud.

[0023] Preferably, in S4, the doctor at the first visiting hospital decrypts, decodes and inverses integer wavelet transform the downloaded visualized encrypted medical image, obtains the original medical image and performs medical diagnosis, and generates a diagnosis record as follows:

[0024] S41: The doctor at the first visit hospital downloads the visualized encrypted medical images from the cloud;

[0025] S42: extracting an 8×K-bit binary tag sequence from a visualization area of ​​the visualized encrypted medical image;

[0026] S43: extracting the encrypted concatenated sequence from the middle-high and high-frequency regions of the visualized encrypted medical image, decrypting the concatenated sequence using the image encryption key, extracting the least significant bits of the first 8×K pixels in the original low-frequency region, and restoring the original visualized region;

[0027] S44: using the 8×K-bit binary mark sequence taken out from the visualization area to assist in decoding the encrypted run-length coding sequence in the concatenated sequence;

[0028] S45: Combine the original visualization area and the decoded run-length coding sequence to obtain an image after iterative K-times Haar wavelet transformation and perform inverse Haar wavelet transformation to obtain the original medical image, so as to make a medical diagnosis based on the original medical image and generate a diagnosis record.

[0029] Preferably, in S5, the doctor of the first visiting hospital encrypts the diagnosis record and embeds it into the downloaded encrypted medical image, generates a visual encrypted medical image carrying the diagnosis record, and uploads it to the cloud as follows:

[0030] S51: The doctor at the first visiting hospital encrypts the generated diagnosis record using the data encryption key;

[0031] S52: Embed the encrypted diagnosis record into the redundant space of the visualized encrypted medical image, generate a visualized encrypted medical image carrying the diagnosis record, and upload it to the cloud.

[0032] Preferably, in S6, the pharmacist of the first visiting hospital downloads the visualized encrypted medical image loaded with the diagnosis record, and decrypts the diagnosis record according to his authority, so as to provide the patient with the medicine, as follows:

[0033] The pharmacist at the first visit hospital downloads the encrypted medical data from the cloud, obtains the encrypted diagnosis record, and decrypts it with the data encryption key to view the diagnosis record generated by the doctor, so as to provide drugs to the patient.

[0034] Preferably, in S7, the doctor at the second visit hospital downloads the visualized encrypted medical image of the load diagnosis record, and decrypts, decodes and inverses integer wavelet transforms the original medical image according to the authority to facilitate the second diagnosis as follows:

[0035] S71: The doctor at the second visit hospital downloads the visualized encrypted medical image of the load diagnosis record from the cloud and retrieves the encrypted medical image;

[0036] S72: taking out an 8×K-bit binary tag sequence from the visualization area of ​​the visualization encrypted medical image recorded in the load diagnosis; extracting the encrypted concatenated sequence from the middle-high and high-frequency areas of the visualization encrypted medical image, decrypting the concatenated sequence using the image encryption key, extracting the least significant bits of the first 8×K pixels in the original low-frequency area, and restoring the original visualization area;

[0037] S73: using the 8×K-bit binary mark sequence taken out from the visualization area to assist in decoding the encrypted run-length coding sequence in the concatenated sequence;

[0038] S74: Combine the original visualization area and the decoded run-length coding sequence to obtain an image after iterative K-times Haar wavelet transformation and perform inverse Haar wavelet transformation to obtain the original medical image, so as to make a secondary medical diagnosis based on the original medical image.

[0039] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0040] In order to protect the privacy of medical images while retaining a certain degree of readability, this paper proposes a method for protecting medical images based on integer wavelet transform and encryption domain steganography. This paper can not only effectively protect the security of encrypted medical images, but also provide a degraded visual input to assist cloud managers in archiving and managing images. Experimental results show that compared with traditional image encryption, the scheme proposed by this paper facilitates cloud managers to manage and archive images on the cloud, and has superior performance. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] Figure 1 It is a framework diagram of the method proposed in the present invention;

[0042] Figure 2 is a specific example of Haar wavelet transform;

[0043] Figure 3 This is a schematic diagram of the original medical image after three iterations of Haar wavelet transform;

[0044] Figure 4 is the reading order of the image sequence to be encoded after 3 times Haar wavelet transformation;

[0045] Figure 5 Schematic diagram of 3 sequences to be encoded generated in each of the 8 bit planes;

[0046] Figure 6 Schematic diagram for visualizing encrypted medical images. DETAILED DESCRIPTION

[0047] In order to facilitate ordinary technicians in this field to understand and implement the present invention, the present invention is further described in detail below with reference to the accompanying drawings. It should be understood that the embodiments described herein are only used to illustrate and explain the present invention, and are not used to limit the present invention.

[0048] In a preferred embodiment of the present invention, a method for protecting medical images based on integer wavelet transform and encryption domain steganography is provided, which is used to provide privacy protection for medical images stored in the cloud while providing a certain readability, so as to facilitate the archiving and management of medical images. The framework is as follows: Figure 1 As shown, the specific steps are as follows:

[0049] S1: The medical center management terminal performs integer wavelet transform on the acquired medical images.

[0050] In an embodiment of the present invention, in the above step S1, the method by which the medical center management terminal performs integer wavelet transform on the acquired medical image of the patient is as follows:

[0051] The medical center management end iterates K times of Haar wavelet transform on the original medical image to generate an image after K times of Haar wavelet transform. During the iterative process, each Haar wavelet transform will generate corresponding low-frequency areas, horizontal medium-high frequency areas, vertical medium-high frequency areas and high-frequency areas, and the i-th Haar wavelet transform needs to be performed on the low-frequency area generated by the i-1th Haar wavelet transform, i = 2, 3..., K; finally, the low-frequency area generated by the K-th Haar wavelet transform is used as the visualization area of ​​the image.

[0052] In the embodiment of the present invention, the above K is preferably 3, that is, the medical center management segment iterates the original medical image for a total of 3 times of Haar wavelet transform. Haar wavelet transform is a special integer wavelet transform, such as Figure 2 The original medical image is transformed by iterating 3 times the Haar wavelet transform to obtain the image as shown in the example Figure 3 , where each Haar wavelet transform will generate the corresponding low-frequency area LL, horizontal medium-high frequency area HL, vertical medium-high frequency area LH and high frequency area HH. And because the i-th Haar wavelet transform is performed on the low-frequency area generated by the i-1-th Haar wavelet transform, only the low-frequency area generated by the K-th Haar wavelet transform is retained in the image after the K-th Haar wavelet transform. This low-frequency area is recorded as the visualization area of ​​the entire image, and the rest of the area can be used as the information hiding area of ​​the image. Figure 4 As shown in Figure 2, during the three Haar wavelet transforms, the first Haar wavelet transform generates the corresponding low-frequency region LL. 1 , horizontal mid-high frequency area HL 1 , longitudinal mid-high frequency area LH 1 and high frequency region HH 1, in the low frequency region LL 1 Based on the second Haar wavelet transform, the corresponding low-frequency area LL is generated. 2 , horizontal mid-high frequency area HL 2 , longitudinal mid-high frequency area LH 2 and high frequency region HH 2 , in the low frequency region LL 2 Based on the third Haar wavelet transform, the corresponding low-frequency area LL is generated 3 , horizontal mid-high frequency area HL 3 , longitudinal mid-high frequency area LH 3 and high frequency region HH 3 LL 3 is the visualization area of ​​the entire image.

[0053] S2: The medical center management end performs run-length coding on the medium-high frequency area and high frequency area of ​​the medical image after integer wavelet transform.

[0054] In an embodiment of the present invention, in the above step S2, the medical center management terminal performs run length coding on the medium-high frequency area and the high frequency area of ​​the medical image converted by integer wavelet transform as follows:

[0055] S21: The medical center management terminal converts the image after K-times Haar wavelet transformation in the original medical image into 8 value bit planes and 1 sign bit plane;

[0056] S22: For each value bit plane, respectively obtain the horizontal medium and high frequency area, the vertical medium and high frequency area and the high frequency area generated in each iteration, and read the bit values ​​from the relative positions of the three areas generated in each iteration in the order of the horizontal medium and high frequency area, the vertical medium and high frequency area and the high frequency area, and concatenate them into a sequence to be encoded, so that each value bit plane generates K sequences to be encoded with inconsistent lengths;

[0057] S23: For each sequence to be encoded, use run-length coding to encode it. If it is encodable, record the run-length coding sequence obtained after encoding and mark the sequence as 1 in the mark sequence. If it is not encodable, record the original sequence to be encoded and mark the sequence as 0 in the mark sequence. Based on this, in addition to generating the run-length coding sequence, an 8×K-bit binary mark sequence will eventually be obtained.

[0058] In this embodiment, the values ​​after K-times Haar wavelet transform can be converted into 8 value bit planes by equation (1), and the image values ​​after K-times Haar wavelet transform can be converted into 1 sign bit plane by equation (2):

[0059]

[0060]

[0061] Where: IH (i,j) Represents the value at coordinate (i, j) in the image after K-times Haar wavelet transform, Indicates rounding down. and IS (i,j) Represents the value at coordinate (i, j) in the kth value bit plane and sign bit plane respectively.

[0062] in addition, Figure 4 The horizontal medium and high frequency area, the vertical medium and high frequency area and the high frequency area corresponding to the three iterations, as well as the reading order of the corresponding sequence to be encoded are shown. The three sequences to be encoded with different lengths generated in each of the eight bit planes are shown in Figure 1. Figure 5 shown.

[0063] S3: The medical center management end encrypts the travel code, fills the encrypted travel code into the original medium-high frequency area and high-frequency area in the medical image, generates a visualized encrypted medical image, and uploads it to the cloud.

[0064] In an embodiment of the present invention, in the above step S3, the medical center management end encrypts the code, fills the encrypted run code into the original medium-high and high-frequency areas, generates a visual encrypted medical image, and uploads it to the cloud as follows:

[0065] S31: The medical center management terminal extracts the least significant bits of the first 8×K pixels from the low-frequency area generated by the K-th Haar wavelet transform, and sequentially fills the 8×K-bit binary mark sequence obtained in S23 into it, thereby forming a visualization area of ​​the visualized encrypted medical image;

[0066] S32: The least significant bit of the 8×K pixels extracted in S31, the run-length coding sequence generated in S23, and the symbol bit plane generated in S21 are concatenated to generate a concatenated sequence, and the concatenated sequence is encrypted with the image encryption key (Key-I). The encrypted concatenated sequence is then filled into the horizontal medium and high frequency areas, the vertical medium and high frequency areas, and the high frequency areas generated by each iteration in the order of the bit planes from large to small and K from large to small, and the redundant space is filled with random binary codes. Finally, a visual encrypted medical image is generated and uploaded to the cloud.

[0067] in, Figure 6 An example of the results of visually encrypted medical images uploaded to the cloud in an embodiment of the present invention is shown.

[0068] S4: The doctor at the hospital where the patient is first visited downloads the visualized encrypted medical image from the cloud by sending a download request, and decrypts, decodes and inverses integer wavelet transform the downloaded visualized encrypted medical image to obtain the original medical image for medical diagnosis and thus generating a diagnosis record.

[0069] In an embodiment of the present invention, in the above step S4, the doctor of the first-visit hospital decrypts, decodes and inverses integer wavelet transforms the downloaded visualized encrypted medical image, obtains the original medical image and performs medical diagnosis, and the method for generating a diagnosis record is as follows:

[0070] S41: The doctor at the first visit hospital downloads the visualized encrypted medical images from the cloud;

[0071] S42: extracting an 8×K-bit binary tag sequence from a visualization area of ​​the visualized encrypted medical image;

[0072] S43: extracting the encrypted concatenated sequence from the middle-high and high-frequency regions of the visualized encrypted medical image, decrypting the concatenated sequence using the image encryption key, extracting the least significant bits of the first 8×K pixels in the original low-frequency region, and filling them back into the visualized region, thereby restoring the original visualized region;

[0073] S44: using the 8×K-bit binary mark sequence taken out from the visualization area to assist in decoding the encrypted run-length coding sequence in the concatenated sequence;

[0074] S45: Combine the original visualization area and the decoded run-length coding sequence to obtain an image after iterative K-times Haar wavelet transformation and perform inverse Haar wavelet transformation to obtain the original medical image, so as to make a medical diagnosis based on the original medical image and generate a diagnosis record.

[0075] It should be noted that the original medical image acquisition process in the above step S4 is essentially the reverse process of the encryption process performed by the medical center management end, and the specific operations can be performed in reverse according to the corresponding encryption process.

[0076] S5: The doctor at the first visiting hospital encrypts the diagnosis record and embeds it into the downloaded visualized encrypted medical image, generates a visualized encrypted medical image carrying the diagnosis record, and uploads it to the cloud.

[0077] In an embodiment of the present invention, in the above step S5, the doctor of the hospital visiting the patient for the first time encrypts the diagnosis record and embeds it into the downloaded encrypted medical image, generates a visual encrypted medical image carrying the diagnosis record, and uploads it to the cloud as follows:

[0078] S51: The doctor at the first visiting hospital encrypts the generated diagnosis record using the data encryption key (Key-D);

[0079] S52: Embed the encrypted diagnosis record into the redundant space of the visualized encrypted medical image, generate a visualized encrypted medical image carrying the diagnosis record, and upload it to the cloud.

[0080] S6: The pharmacist at the first visit hospital downloads the visualized encrypted medical image of the payload diagnosis record from the cloud by sending a download request, and decrypts the diagnosis record according to his authority, so as to provide drugs to the patient according to the diagnosis record.

[0081] In an embodiment of the present invention, in the above step S6, the pharmacist of the first-visit hospital downloads the visualized encrypted medical image of the load diagnosis record, and decrypts the diagnosis record according to its authority to provide the patient with medicine as follows:

[0082] The pharmacist at the first visit hospital downloads the encrypted medical data from the cloud, obtains the encrypted diagnosis record, and decrypts it with the data encryption key to view the diagnosis record generated by the doctor, so as to provide drugs to the patient.

[0083] S7: The doctor at the secondary visit hospital downloads the visualized encrypted medical image of the payload diagnosis record from the cloud by sending a download request, and decrypts, decodes, and inverses integer wavelet transforms according to his authority to obtain the original medical image and perform a secondary diagnosis.

[0084] In an embodiment of the present invention, in the above step S7, the doctor of the second visit hospital downloads the visualized encrypted medical image of the load diagnosis record, and decrypts, decodes and inverses integer wavelet transforms according to the authority to obtain the original medical image for the second diagnosis as follows:

[0085] S71: The doctor at the second visit hospital downloads the visualized encrypted medical image of the load diagnosis record from the cloud and retrieves the encrypted medical image;

[0086] S72: taking out an 8×K-bit binary tag sequence from the visualization area of ​​the visualized encrypted medical image recorded in the load diagnosis; extracting the encrypted concatenated sequence from the middle-high and high-frequency areas of the visualized encrypted medical image, decrypting the concatenated sequence using the image encryption key, extracting the least significant bits of the first 8×K pixels in the original low-frequency area, and filling them back into the visualization area, thereby restoring the original visualization area;

[0087] S73: using the 8×K-bit binary mark sequence taken out from the visualization area to assist in decoding the encrypted run-length coding sequence in the concatenated sequence;

[0088] S74: Combine the original visualization area and the decoded run-length coding sequence to obtain an image after iterative K-times Haar wavelet transformation and perform inverse Haar wavelet transformation to obtain the original medical image, so as to make a secondary medical diagnosis based on the original medical image.

[0089] It should be specially noted that, in the present invention, how doctors generate diagnostic records, make secondary medical diagnoses, and how pharmacists provide drugs to patients are not part of the technical solution of the present invention.

[0090] The above-described embodiment is only a preferred solution of the present invention, but it is not intended to limit the present invention. A person skilled in the relevant technical field may make various changes and modifications without departing from the spirit and scope of the present invention. Therefore, any technical solution obtained by equivalent replacement or equivalent transformation falls within the protection scope of the present invention.

Claims

1. A medical image protection method based on integer wavelet transform and steganography in the encrypted domain, which provides privacy protection for medical images stored in the cloud while providing a certain degree of readability. Characterized in that, The specific steps are as follows: S1: The medical center management terminal performs integer wavelet transform on the acquired medical images. S2: The medical center management terminal performs run-length encoding on the middle-high frequency region and high-frequency region of the medical images after integer wavelet transform. S3: The medical center management terminal encrypts the run-length encoding, fills the encrypted run-length encoding into the original middle-high frequency region and high-frequency region of the medical images, generates a visual encrypted medical image, and uploads it to the cloud. S4: The doctor terminal of the first visit hospital downloads the visual encrypted medical image from the cloud by sending a download request, decrypts, decodes and performs inverse integer wavelet transform on the downloaded visual encrypted medical image to obtain the original medical image for medical diagnosis to generate a diagnosis record. S5: The doctor terminal of the first visit hospital encrypts the diagnosis record and embeds it into the downloaded visual encrypted medical image to generate a visual encrypted medical image carrying the diagnosis record, and uploads it to the cloud. S6: The pharmacist terminal of the first visit hospital downloads the visual encrypted medical image carrying the diagnosis record from the cloud by sending a download request and decrypts the diagnosis record according to its authority to facilitate providing drugs for the patient according to the diagnosis record. S7: The doctor terminal of the second visit hospital downloads the visual encrypted medical image carrying the diagnosis record from the cloud by sending a download request and decrypts, decodes and performs inverse integer wavelet transform according to its authority to obtain the original medical image and perform a second diagnosis.

2. A medical image protection method based on integer wavelet transform and steganography in the encrypted domain according to claim 1, Characterized in that, In the said S1, the method for the medical center management terminal to perform integer wavelet transform on the acquired medical images is as follows: The medical center management terminal iteratively performs Haar wavelet transform on the original medical image K times to generate an image after K times of Haar wavelet transform. In the iterative process, each Haar wavelet transform will generate corresponding low-frequency region, horizontal middle-high frequency region, vertical middle-high frequency region and high-frequency region. And the i-th Haar wavelet transform needs to be performed on the low-frequency region generated by the (i - 1)-th Haar wavelet transform, where i = 2, 3..., K; finally, the low-frequency region generated by the K-th Haar wavelet transform is used as the visual region of the image.

3. A medical image protection method based on integer wavelet transform and steganography in the encrypted domain according to claim 2, Characterized in that, In the said S2, the method for the medical center management terminal to perform run-length encoding on the middle-high frequency region and high-frequency region of the medical images after integer wavelet transform is as follows: S21: The medical center management terminal converts the image after K times of Haar wavelet transform in the original medical image into 8 value bit planes and 1 sign bit plane. S22: For each value bit plane, respectively obtain the horizontally middle-high frequency region, vertically middle-high frequency region, and high frequency region generated corresponding to each iteration, and read the bit values from these three regions generated in each iteration in the order of the horizontally middle-high frequency region, vertically middle-high frequency region, and high frequency region and concatenate them into a sequence to be encoded, so that each value bit plane generates K sequences to be encoded with inconsistent lengths; S23: For each sequence to be encoded, perform run-length encoding on it. If it can be encoded, record the obtained run-length encoded sequence after encoding and mark this sequence as 1 in the marking sequence. If it cannot be encoded, record the original sequence to be encoded and mark this sequence as 0 in the marking sequence; finally, obtain an 8×K-bit binary marking sequence.

4. A medical image protection method based on integer wavelet transform and steganography in the encrypted domain according to claim 3, characterized in that, in S3, the medical center management terminal encrypts the encoding, fills the encrypted run-length encoding into the original middle-high and high frequency regions to generate a visual encrypted medical image, and uploads it to the cloud by the following method: S31: The medical center management terminal extracts the least significant bits of the first 8×K pixels from the low frequency region generated by the K-th Haar wavelet transform, and sequentially fills the 8×K-bit binary marking sequence obtained in S23 into it, so as to form the visual region of the visual encrypted medical image; S32: Concatenate the least significant bits of the 8×K pixels extracted in S31, the run-length encoded sequence generated in S23, and the symbol bit plane generated in S21 to generate a concatenated sequence, encrypt the concatenated sequence with the image encryption key, and then fill the encrypted concatenated sequence into the horizontally middle-high frequency region, vertically middle-high frequency region, and high frequency region generated in each iteration in the order of the bit plane from large to small and K from large to small, and fill the redundant space with random binary encoding. Finally, generate a visual encrypted medical image and upload it to the cloud.

5. A medical image protection method based on integer wavelet transform and steganography in the encrypted domain according to claim 4, characterized in that, in S4, the doctor terminal of the first visiting hospital decrypts, decodes, and performs inverse integer wavelet transform on the downloaded visual encrypted medical image, obtains the original medical image and performs medical diagnosis, and generates a diagnosis record by the following method: S41: The doctor terminal of the first visiting hospital downloads the visual encrypted medical image from the cloud; S42: Take out the 8×K-bit binary marking sequence from the visual region of the visual encrypted medical image; S43: Extract the encrypted concatenated sequence from the middle-high and high frequency regions of the visual encrypted medical image, decrypt it with the image encryption key to obtain the concatenated sequence, extract the least significant bits of the first 8×K pixels in the original low frequency region from it, and restore the original visual region; S44: Use the 8×K-bit binary marking sequence taken out from the visual region to assist in decoding the encrypted run-length encoded sequence in the concatenated sequence; S45: Combine the original visualization region and the decoded run-length encoded sequence to obtain the image after the Haar wavelet transform iterated K times and perform the inverse Haar wavelet transform to obtain the original medical image, so as to facilitate making a medical diagnosis based on the original medical image and generating a diagnosis record.

6. A medical image protection method based on integer wavelet transform and steganography in the encrypted domain according to claim 5, wherein, in the said S5, the doctor in the first visit hospital encrypts the diagnosis record and embeds it into the downloaded encrypted medical image to generate a visual encrypted medical image carrying the diagnosis record, and the method of uploading it to the cloud is as follows: S51: The doctor in the first visit hospital encrypts the generated diagnosis record with the data encryption key; S52: Embed the encrypted diagnosis record into the redundant space of the visual encrypted medical image to generate a visual encrypted medical image carrying the diagnosis record, and upload it to the cloud.

7. A medical image protection method based on integer wavelet transform and steganography in the encrypted domain according to claim 6, wherein, in the said S6, the pharmacist side in the first visit hospital downloads the visual encrypted medical image carrying the diagnosis record and decrypts the diagnosis record according to its authority, so as to facilitate providing drugs for the patient. The method is as follows: The pharmacist side in the first visit hospital downloads the encrypted medical data from the cloud, obtains the encrypted diagnosis record, and decrypts it with the data encryption key, so as to view the diagnosis record generated by the doctor side, so as to provide drugs for the patient.

8. A medical image protection method based on integer wavelet transform and steganography in the encrypted domain according to claim 7, wherein, in the said S7, the doctor side in the second visit hospital downloads the visual encrypted medical image carrying the diagnosis record and decrypts, decodes and performs the inverse integer wavelet transform according to its authority to obtain the original medical image for the purpose of making a second medical diagnosis. The method is as follows: S71: The doctor in the second visit hospital downloads the visual encrypted medical image carrying the diagnosis record from the cloud and extracts the encrypted medical image; S72: Extract an 8×K-bit binary marker sequence from the visualization region of the visual encrypted medical image carrying the diagnosis record; Extract the encrypted concatenated sequence from the middle-high and high-frequency regions of the visual encrypted medical image, decrypt it with the image encryption key to obtain the concatenated sequence, extract the least significant bits of the first 8×K pixels in the original low-frequency region from it, and restore the original visualization region; S73: Use the 8×K-bit binary marker sequence extracted from the visualization region to assist in decoding the encrypted run-length encoded sequence in the concatenated sequence; S74: Combine the original visualization region and the decoded run-length encoded sequence to obtain the image after the Haar wavelet transform iterated K times and perform the inverse Haar wavelet transform to obtain the original medical image for the purpose of making a second medical diagnosis based on the original medical image.

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