CT data compression method

Abstract

The invention provides a CT (Computed Tomography) data compression method executed by a computer. The method comprises the following steps: acquiring original CT data; enhancing the HU value of the original CT data by using a contrast enhancement algorithm; the enhanced CT data are quantized, and first quantized CT data are obtained; generating a first two-dimensional image sequence based on the first quantized CT data; and encoding the first two-dimensional image sequence by using a video encoding method to obtain video data, the encoding retaining each frame of the first two-dimensional image sequence.

Description

Technical Field

[0001] This application generally relates to CT data compression methods. Background Art

[0002] Nowadays, CBCT (Cone Beam Computer Tomography) is increasingly used in dental diagnosis.

[0003] However, the amount of raw data of CBCT is relatively large, generally hundreds of megabytes, and even greater than one hundred megabytes after compression, which is not conducive to remote data exchange. This limits the increasingly popular multi-party remote collaborative diagnosis and treatment and doctor-patient remote interaction today.

[0004] Therefore, it is necessary to provide a new CT data compression method. Summary of the Invention

[0005] One aspect of this application provides a computer-implemented CT data compression method, including: obtaining raw CT data; enhancing the HU values of the raw CT data using a contrast enhancement algorithm; quantifying the enhanced CT data to obtain first-quantified CT data; generating a first two-dimensional image sequence based on the first-quantified CT data; and encoding the first two-dimensional image sequence using a video encoding method to obtain video data, where the encoding retains each frame of the first two-dimensional image sequence.

[0006] In some embodiments, the CT data compression method further includes: obtaining metadata, which includes the metadata length, the number of frames of the first two-dimensional image sequence, and the size of the two-dimensional images of the first two-dimensional image sequence; and assembling the video data and the metadata to obtain compressed CT data.

[0007] In some embodiments, the metadata further includes a quantization interval.

[0008] In some embodiments, the contrast enhancement algorithm is a contrast-limited adaptive histogram equalization algorithm.

[0009] In some embodiments, the video encoding method is an HEVC video encoding method.

[0010] In some embodiments, the quantization interval for quantization is [a, b], where a is less than or equal to the HU value of the CT data ranked at 10% in ascending order, and b is greater than or equal to the HU value of the CT data ranked at 90% in ascending order.

[0011] Another aspect of the present application provides a computer system for compressing CT data, which includes a processor and a storage device. The storage device stores a computer program for compressing CT data. When it is run, the processor will execute the CT data compression method described above.

[0012] Another aspect of the present application provides a method for decompressing compressed CT data executed by a computer, including: obtaining the compressed CT data, which includes the video data described above; using a corresponding video decoder to decode the video data to obtain a second two-dimensional image sequence; and superimposing the second two-dimensional image sequence to obtain second quantized CT data.

[0013] In some embodiments, the compressed CT data further includes metadata, the metadata includes the number of frames of the first two-dimensional image sequence and the size of the two-dimensional images of the first two-dimensional image sequence, and the method for decompressing the compressed CT data further includes: verifying the second two-dimensional image sequence according to the number of frames of the first two-dimensional image sequence and the size of the two-dimensional images of the first two-dimensional image sequence.

[0014] In some embodiments, the compressed CT data further includes metadata, the metadata includes the quantization interval, and the method for decompressing the compressed CT data further includes: calculating the HU value of the CT data based on the quantization interval and the second quantized CT data.

[0015] Another aspect of the present application provides a computer system for decompressing compressed CT data, which includes a processor and a storage device. The storage device stores a computer program for decompressing compressed CT data. When it is run, the processor will execute the method for decompressing the compressed CT data described above. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] The above and other features of the present disclosure will be more fully and clearly understood by reference to the following description and the appended claims, in conjunction with the accompanying drawings. It should be understood that these drawings only depict several embodiments of the present disclosure and should not be considered as limiting the scope of the present disclosure. By using the accompanying drawings, the present disclosure will be more clearly and detailedly described.

[0017] Figure 1 It is a schematic flowchart of the CT data compression method in an embodiment of the present application. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0018] In the following detailed description, reference is made to the accompanying drawings which form a part hereof. In the drawings, like reference numerals generally represent like components unless the context dictates otherwise. The illustrative exemplary embodiments described in the detailed description, the drawings, and the claims are not intended to be limiting. Other embodiments may be utilized and other changes may be made without departing from the spirit or scope of the subject matter described herein. It should be readily understood that various different configurations, substitutions, combinations, and designs of the aspects of the present disclosure generally described herein and illustrated in the drawings are all clearly contemplated and form a part of the present disclosure.

[0019] One aspect of the present application provides a method for compressing CT (Computed Tomography) data. It mainly quantifies the HU value (Hounsfield Scale) of the original CT data and then encodes the quantified CT data using a video coding method. The capacity of the encoded data is significantly lower than that of the original CT data, which is very beneficial for the remote exchange of CT data. To alleviate the problem that the HU values in adjacent regions cannot be distinguished after quantization, before quantifying the HU value, a contrast enhancement algorithm is used to enhance it. In this way, while ensuring the data compression ratio, the image details are retained to the greatest extent.

[0020] Please refer Figure 1 , which is a schematic flowchart of a CT data compression method 100 executed by a computer in an embodiment of the present application.

[0021] The CT data compression method of the present application will be described in detail below using CBCT data as an example. It can be understood that in addition to CBCT data, the CT data compression method of the present application is also applicable to other types of CT data.

[0022] In 101, the original CBCT data is obtained.

[0023] The original CBCT data refers to the CBCT data that has not been compressed by the method of the present application.

[0024] The original CBCT data can be CBCT three-dimensional data in the NRRD (Nearly Raw Raster Data) file format or the DCM file format.

[0025] In 103, a contrast enhancement algorithm is used to enhance the HU value of the original CBCT data.

[0026] The inventors of the present application have found that directly quantifying the HU values of CBCT data without enhancing the HU values of CBCT data is likely to cause the problem that the HU values in adjacent regions cannot be distinguished, that is, it will cause some image details in the encoded CBCT data to be lost, thereby affecting the subsequent use of the encoded CBCT data. The HU value is a quantitative scale unit of the radiopacity, also known as the CT value.

[0027] Through a large number of experiments, the inventors of the present application have found that before quantifying the HU values of CBCT data, enhancing them using a contrast enhancement method can significantly reduce the problem that the HU values in adjacent regions cannot be distinguished after quantization.

[0028] In one embodiment, the Contrast Limited Adaptive Histogram Equalization (CLAHE) algorithm can be used to enhance the HU values of the CBCT data.

[0029] Inspired by the present application, it can be understood that in addition to the CLAHE algorithm, any other applicable contrast enhancement algorithm can also be used to enhance the HU values of the CBCT data.

[0030] In 105, the enhanced CBCT data is quantified.

[0031] The purpose of quantization is to reduce the data volume of the CBCT data.

[0032] Let the quantization interval be [a, b].

[0033] In one embodiment, the enhanced HU values can be sorted by size, and a and b are respectively taken as the HU values at 3% and 97%. Inspired by the present application, it can be understood that the values of a and b are not limited to the above values and can be adjusted according to specific circumstances. For example, a can be less than or equal to the HU value of the CT data ranked at 10% from small to large, and b can be greater than or equal to the HU value of the CT data ranked at 90% from small to large. More preferably, a can be less than or equal to the HU value of the CT data ranked at 5% from small to large, and b can be greater than or equal to the HU value of the CT data ranked at 95% from small to large.

[0034] In one embodiment, quantization can be expressed by the following equation (1):

[0035]

[0036] where Q (x,y,x) represents the quantized value at the coordinate (x, y, z), and P(x,y,z) represents the enhanced HU value at the coordinate (x, y, z), and t represents the coding depth, which can take values such as 8, 10, 12, 16, etc. according to needs.

[0037] The clip function is expressed by the following equation (2):

[0038]

[0039] In 107, a two-dimensional image sequence is generated based on the quantized CBCT data.

[0040] In one embodiment, the quantized CBCT data can be unfolded along a predetermined direction (e.g., along the X-axis direction) to obtain a CBCT two-dimensional image sequence, where each frame of the two-dimensional images in the two-dimensional image sequence has the same size (i.e., resolution) and is a grayscale image.

[0041] In one embodiment, the two-dimensional image sequence can be in the JPEG format. The capacity of the two-dimensional image sequence obtained in this way can reach about 15MB.

[0042] In 109, the two-dimensional image sequence is encoded using a video coding method.

[0043] In one embodiment, the HEVC (High Efficiency Video Coding) coding method can be used to encode the two-dimensional image sequence to obtain video data. In one embodiment, the video data can be in the AnnexB format.

[0044] Inspired by the present application, it can be understood that in addition to the HEVC coding method, any other applicable video coding method can also be used to encode the two-dimensional image sequence.

[0045] In order to retain as much image detail as possible, all frames are retained when encoding the two-dimensional image sequence using a video coding method, that is, no frame of the two-dimensional image sequence is discarded during encoding.

[0046] In 111, metadata is obtained, and the metadata and the video data are assembled to obtain the encoded data.

[0047] In one embodiment, the encoded data includes three parts: L + M + D. Among them, L represents the length of the metadata bytes, M represents the metadata, and D represents the video data.

[0048] In one embodiment, the metadata can include the following content:

[0049] 9 * [4-byte floating point number]: Direction matrix (i.e., the directions of the three coordinate axes of the three-dimensional coordinate system based on which the two-dimensional image sequence is generated);

[0050] 3 * [4-byte floating point number]: Origin coordinates (i.e., the coordinates of the origin of the three-dimensional coordinate system based on which the two-dimensional image sequence is generated);

[0051] 3 * [2-byte integer]: Sizes of the CBCT data in the x, y, and z directions (including the number of frames of the two-dimensional image sequence and the size of each two-dimensional image);

[0052] 3 * [4-byte floating point number]: Inter-slice spacings of the CBCT data in the x, y, and z directions; and

[0053] Quantization interval.

[0054] Through actual tests, when using the method of this application to compress CBCT data, its data capacity is only 1 / 50 to 1 / 30 of that using traditional compression methods, and can reach about 5MB, greatly shortening the time-consuming for remote uploading or downloading.

[0055] To decode the encoded data, first read the first two bits to obtain the length L of the metadata, then read the subsequent L-bit data to obtain the metadata M, and the data after the metadata M is the video data D.

[0056] Then, use the corresponding video decoding method to decode the video data D to obtain the two-dimensional image sequence. In one embodiment, the decoded two-dimensional image sequence can be verified according to the number of frames of the two-dimensional image sequence and the size of each two-dimensional image in the metadata. If the number of frames of the decoded two-dimensional image sequence and the size of each two-dimensional image do not match the corresponding data in the metadata, then it is determined that the decoded two-dimensional image sequence is invalid.

[0057] Superimpose the decoded two-dimensional image sequence to obtain the quantized CBCT data.

[0058] In one embodiment, the quantized Q value can be used as the HU value, and in specific applications, the directly decoded CBCT data is adopted.

[0059] In another embodiment, based on the decoded quantized CBCT data, the quantization interval [a, b], and the coding depth t, the HU value can be calculated according to the following equation (3) to obtain the CBCT data with the HU value restored, and in specific applications, the CBCT data with the HU value restored is adopted.

[0060]

[0061] Typical uses of the decoded CBCT data include: the quantized CBCT data obtained by decoding or the CBCT data with HU values restored can be used for 3D preview; based on the decoded 2D image sequence, disease diagnosis can be performed. It can be understood that the uses of the decoded CBCT data are not limited to those listed above.

[0062] The CT data compression method of this application is executed by a computer. Another aspect of this application provides a computer system for compressing CT data, which includes a processor and a storage device. The storage device stores a computer program for compressing CT data. When it is run, the processor will execute the method 100 for compressing CT data.

[0063] Although multiple aspects and embodiments of this application are disclosed herein, other aspects and embodiments of this application will be obvious to those skilled in the art inspired by this application. Each aspect and embodiment disclosed herein is for illustrative purposes only, not for limiting purposes. The scope of protection and the gist of this application are determined only by the appended claims.

[0064] Similarly, each diagram may illustrate an exemplary architecture or other configuration of the disclosed method and system, which helps to understand the features and functions that may be included in the disclosed method and system. The claimed subject matter is not limited to the illustrated exemplary architecture or configuration, and the desired features can be implemented with various alternative architectures and configurations. In addition, for flowcharts, functional descriptions, and method claims, the order of the boxes given here should not be limited to the order in which various embodiments perform the functions in the same order, unless explicitly stated in the context.

[0065] Unless otherwise explicitly stated, the terms and phrases and their variants used herein should be interpreted as open-ended rather than restrictive. In some instances, the presence of expansive vocabulary and phrases such as "one or more", "at least", "but not limited to", or other similar terms should not be construed as intending or requiring a narrowing situation in examples where such expansive terms may not be present.

Claims

1. A computer - implemented CT data compression method, comprising: Obtaining original CT data; Enhancing the HU values of the original CT data by using a contrast enhancement algorithm; Quantifying the enhanced CT data to obtain first - quantified CT data; Generating a first two - dimensional image sequence based on the first - quantified CT data; And Encoding the first two - dimensional image sequence by using a video encoding method to obtain video data, wherein the encoding retains each frame of the first two - dimensional image sequence.

2. The CT data compression method according to claim 1, wherein It further comprises: Obtaining metadata, which includes metadata length, the number of frames of the first two - dimensional image sequence, and the size of the two - dimensional images of the first two - dimensional image sequence; and Assembling the video data and the metadata to obtain compressed CT data.

3. The CT data compression method according to claim 2, wherein The metadata further includes a quantization interval.

4. The CT data compression method according to claim 1, wherein The contrast enhancement algorithm is a contrast - limited adaptive histogram equalization algorithm.

5. The CT data compression method according to claim 1, wherein The video encoding method is an HEVC video encoding method.

6. The CT data compression method according to claim 1, wherein The quantization interval for the quantization is [a, b], where a is less than or equal to the HU value of the CT data ranked at the 10% position in ascending order, and b is greater than or equal to the HU value of the CT data ranked at the 90% position in ascending order.

7. A computer system for compressing CT data, which includes a processor and a storage device, the storage device stores a computer program for compressing CT data, and when it is run, the processor will execute the CT data compression method as claimed in claim 1.

8. A computer - implemented decompression method for compressed CT data, comprising: Obtaining compressed CT data, which includes the video data as claimed in claim 1; Decoding the video data by using a corresponding video decoder to obtain a second two - dimensional image sequence; and Superimposing the second two - dimensional image sequence to obtain second - quantified CT data.

9. The decompression method of compressed CT data according to claim 7, characterized in that, The compressed CT data further includes metadata, the metadata includes the number of frames of the first two - dimensional image sequence and the size of the two - dimensional images of the first two - dimensional image sequence, and the decompression method for the compressed CT data further includes: verifying the second two - dimensional image sequence according to the number of frames of the first two - dimensional image sequence and the size of the two - dimensional images of the first two - dimensional image sequence.

10. The decompression method of the compressed CT data according to claim 7, characterized in that, The compressed CT data further includes metadata, the metadata includes the quantization interval, and the decompression method for the compressed CT data further includes: calculating the HU value of the CT data based on the quantization interval and the second - quantified CT data.

11. A computer system for decompressing compressed CT data, which includes a processor and a storage device, the storage device stores a computer program for decompressing compressed CT data, and when it is run, the processor will execute the decompression method for compressed CT data as claimed in claim 8.

Images