Intraoperative brain tissue drift real-time correction device and method based on terahertz waves

Abstract

The application provides a terahertz wave-based intraoperative brain tissue drift real-time correction device and method, which can detect the position of the brain tissue of a patient in real time through terahertz waves during surgery, generate a three-dimensional fusion image in combination with a CT image, ensure that the position of the brain tissue during surgery is consistent with the position of the brain tissue in the three-dimensional fusion image, avoid brain tissue drift caused by loss of cerebrospinal fluid during surgery, cause differences between the shape and position of the brain tissue during surgery and preoperative images, solve the problem of deviation between surgical operation and preoperative planning caused by brain tissue drift, and thus ensure effective implementation of a surgical plan and improve the accuracy of surgical navigation.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of biomedical imaging technology, in particular to a device and method for real-time correction of intraoperative brain tissue drift based on terahertz waves. BACKGROUND

[0002] The cranial nerve structure is complex, the neurosurgery operation space is small, difficult and risky, and the operator is required to have high operation skills and experience. Multi-modal image guided surgery navigation can segment and model the lesion based on preoperative CT or MRI three-dimensional medical images, accurately plan the craniotomy incision position on the scalp, and intraoperative navigation can help the operator to determine the lesion site in real time.

[0003] However, in actual surgery, the loss of cerebrospinal fluid will cause the brain tissue to drift, resulting in differences between the shape and position of the brain tissue during the operation and the preoperative image. Although the rigid transformation between the intraoperative and preoperative organs is compensated after the spatial pose calibration, the non-rigid transformation caused by the deformation displacement makes the treatment plan planned on the preoperative image and the segmented tissue model unable to match the actual situation during the operation, ultimately resulting in a large deviation between the operation and the preoperative planning.

[0004] Terahertz (THz) waves, also known as t-rays, are electromagnetic waves with a frequency range of 0.1-10 terahertz. The terahertz band is located between microwaves and infrared waves, and is a key transition region from macroscopic electronics to microscopic photonics. The unique physical properties of terahertz waves make terahertz technology have broad application prospects. Terahertz waves have good penetration and high spectral resolution, making them an ideal imaging method. In addition, there is a wealth of terahertz electromagnetic information in biological bodies, which can be detected and characterized to identify biological states. However, existing medical devices generally use terahertz waves to detect samples, such as patent CN105510272A, which discloses a detection device for ischemic brain tissue based on terahertz wave transmission imaging. There is no device for detecting and navigating during surgery. SUMMARY

[0005] Therefore, the present application aims to provide a device and method for real-time correction of intraoperative brain tissue drift based on terahertz waves to solve the problem of brain tissue drift caused by the loss of cerebrospinal fluid in actual surgery, resulting in differences between the shape and position of the brain tissue during the operation and the preoperative image, and ultimately leading to a large deviation between the operation and the preoperative planning.

[0006] To achieve the above-mentioned purpose, the technical scheme of the present application is as follows:

[0007] A device for real-time correction of intraoperative brain tissue drift based on terahertz waves, comprising:

[0008] The detector is used for detecting brain tissue in real time during surgery, and comprises a detection main body, an upper portion of the detection main body is provided with a first telescopic column, an upper end of the first telescopic column is provided with a support portion, the first telescopic column can be telescoped in the up-down direction relative to the detection main body, and the position of the support portion in the up-down direction is adjusted;

[0009] A front portion of the support portion is provided with a second telescopic column, a front portion of the second telescopic column is provided with a rotating column, a first axis of the rotating column coincides with a second axis of the second telescopic column, the rotating column can be rotated around the first axis, the second telescopic column can be telescoped in the front-rear direction relative to the support portion, and the position of the rotating column in the front-rear direction is adjusted;

[0010] A front end of the rotating column is provided with an arc-shaped arm, the rotating column can drive the arc-shaped arm to rotate around the first axis, so as to adjust the position of the arc-shaped arm;

[0011] A front end of the arc-shaped arm is provided with a detection probe, the detection probe can emit terahertz waves to the brain tissue during surgery and receive the terahertz waves reflected by the brain tissue, so as to detect the brain tissue;

[0012] Further, a console is arranged, a processor, a compensator and a controller are arranged in the console, an upper portion of the console is provided with a display, the processor is used for generating a real-time image according to the terahertz waves received by the detection probe, the compensator is used for receiving a CT image and the real-time image, and generating a three-dimensional fusion image by combining the CT image and the real-time image, the display is used for displaying the three-dimensional fusion image and inputting operation information, and the controller can control the working states of the detector and the console according to the input operation information.

[0013] The in-surgery brain tissue drift real-time correction device based on terahertz waves can detect the position of the brain tissue of a patient in real time during surgery through terahertz waves, and generate a three-dimensional fusion image in combination with a CT image, so as to ensure that the position of the brain tissue during surgery is consistent with the position of the brain tissue in the three-dimensional fusion image, avoid the brain tissue drift caused by the loss of cerebrospinal fluid during surgery, and cause the difference between the shape and position of the brain tissue during surgery and the preoperative image, solve the problem of the deviation between the surgical operation and the preoperative planning caused by the brain tissue drift, and thus ensure the effective implementation of the surgical plan and improve the accuracy of surgical navigation.

[0014] Further, the detection probe comprises a transmitting module and a receiving module, the transmitting module is used for transmitting terahertz waves to the brain tissue during detection, and the receiving module is used for receiving the terahertz waves reflected by the brain tissue.

[0015] The transmitting module and the receiving module are integrated on one probe, so that the device is more compact, and is convenient for operation and installation.

[0016] Further, the emission module comprises a plurality of emission probes capable of simultaneously emitting a plurality of groups of terahertz waves to the brain tissue, and the receiving module comprises a plurality of receiving probes for receiving the terahertz waves reflected by the head.

[0017] By arranging a plurality of emission probes and receiving probes, more data can be obtained at one time, the detection efficiency is improved, the total intensity of the signal is enhanced, the signal-to-noise ratio of the signal is improved, and thus the imaging quality is improved.

[0018] Further, the emission module is provided with a laser positioner capable of emitting laser light for positioning the to-be-detected position.

[0019] This arrangement greatly improves the efficiency of device adjustment.

[0020] Further, the console is provided with a signal receiver for receiving CT image information from the outside.

[0021] By arranging the signal receiver, the doctor does not need to leave the operating room to obtain or check the CT image information, saving time and labor cost and improving the operation efficiency.

[0022] Further, the arc-shaped arm rotates at an angle of a, 0°≤a≤360°, and an angular velocity of W, 0≤W≤10 rad / s.

[0023] The rotation range of 0° to 360° ensures comprehensive coverage of the patient's head, providing flexibility in detection, and a wide range of angular velocity allows rapid adjustment of the position, improving operation efficiency and reducing time consumption during the operation or detection process.

[0024] Further, the lower end of the detector is provided with a first pulley for movement of the detector, and the lower end of the console is provided with a second pulley for movement of the console.

[0025] The design of the pulleys enables flexible movement of the detector and the console, facilitating the doctor to adjust the position to adapt to different surgical environments and patient needs.

[0026] Further, the processor pre-processes the received terahertz waves, converts the pre-processed analog signals into digital signals, compares the digital signals with the emission signals of the terahertz waves, obtains the reflection and attenuation degree information of the brain tissue at different positions on the terahertz waves, then generates a real-time image of the brain tissue using a back-projection algorithm, extracts the boundary information of the brain tissue from the generated real-time image, and calculates the offset between the brain tissue and the skull; the pre-processing includes filtering and amplification, the filtering is used to remove noise and interference in the terahertz waves and improve the signal-to-noise ratio of the signal, and the amplification is used to enhance the intensity of the signal.

[0027] Through the filtering process, the noise and interference in the terahertz wave signal can be effectively removed, and the signal-to-noise ratio of the signal is improved, which helps to generate clearer and more accurate real-time images of brain tissue, and the amplification process enhances the intensity of the signal, so that in the subsequent processing, the effective image information can be more easily extracted, and the visualization effect of the image is improved. The boundary information of the brain tissue is extracted from the real-time image, and the offset between the brain tissue and the skull can be accurately calculated, which is crucial for real-time tracking and correction of the position of the brain tissue during the operation, and helps to reduce the operation errors caused by the drift of the brain tissue.

[0028] Further, the compensator fuses the real-time image and the CT image to generate a three-dimensional fusion image according to the offset between the brain tissue and the skull, so that the brain tissue in the three-dimensional fusion image is consistent with the actual brain tissue; the fusion process includes the steps of:

[0029] S1: extracting feature points from the real-time image and the CT image using the FAST algorithm;

[0030] S2: matching the feature points in the real-time image and the CT image using the SIFT algorithm;

[0031] S3: calculating the geometric transformation between the real-time image and the CT image using the least squares method;

[0032] S4: adjusting the CT image using an elastic deformation model to adapt to different deformations, and resampling the deformed CT image to ensure that the real-time image and the CT image are accurately aligned in the same coordinate system;

[0033] S5: superimposing the aligned real-time image and the CT image together, and generating a three-dimensional fusion image using a fusion algorithm.

[0034] The fusion process combines the real-time nature of the real-time image and the high definition and high resolution advantages of the CT image, so that the three-dimensional fusion image not only contains the real-time position information of the brain tissue, but also maintains the structural details of the preoperative image, improves the overall clarity and information of the image, thereby reducing the deviation between the operation and the preoperative planning, improving the accuracy and success rate of the operation, and providing more accurate navigation information for the doctor.

[0035] The application also provides a real-time correction method for intraoperative brain tissue drift, which is applied to the terahertz wave-based real-time correction device for intraoperative brain tissue drift described above, and includes the following steps:

[0036] Step 1: After the patient lies on the operating table, the head of the patient is fixed by the fixer;

[0037] Step 2: control the motion state of the first telescopic column, the second telescopic column and the rotating column, adjust the position of the detection probe relative to the head;

[0038] Step 3: determine the brain tissue lesion position and the craniotomy position by using the preoperative CT image;

[0039] Step 4: use the detection probe to emit terahertz waves to the patient's head for scanning the head to obtain the initial position information of the brain tissue and the skull;

[0040] Step 5: after the operation starts, use the terahertz waves to detect the relative position between the brain tissue and the skull in real time, and calculate the offset between the brain tissue and the skull;

[0041] Step 6: when the position of the brain tissue is detected to be offset, the real-time image and the CT image are fused once every t time to generate a new three-dimensional fusion image;

[0042] Step 7: the display outputs the generated three-dimensional fusion image.

[0043] This real-time correction method combines the real-time nature of the real-time image and the high definition and high resolution of the CT image by using real-time detection and dynamic adjustment, so that the three-dimensional fusion image contains both the real-time position information of the brain tissue and the structural details of the preoperative image, improves the overall clarity and information amount of the image, and ensures that the doctor can accurately grasp the actual position of the brain tissue during the operation and timely adjust the operation scheme.

[0044] Compared with the prior art, the intraoperative brain tissue drift real-time correction device and method based on terahertz waves have the following advantages:

[0045] 1) can detect the position of the patient's brain tissue in real time during the operation by using terahertz waves, generate a three-dimensional fusion image in combination with the CT image, ensure that the position of the brain tissue during the operation is consistent with the position of the brain tissue in the three-dimensional fusion image, avoid the brain tissue drift caused by the loss of cerebrospinal fluid during the operation, cause the difference between the shape and position of the brain tissue during the operation and the preoperative image, and improve the accuracy of the operation navigation;

[0046] 2) combines the real-time nature of the real-time image and the high definition and high resolution of the CT image, so that the three-dimensional fusion image contains both the real-time position information of the brain tissue and the structural details of the preoperative image, improves the overall clarity and information amount of the image, and ensures that the doctor can accurately grasp the actual position of the brain tissue during the operation and timely adjust the operation scheme. BRIEF DESCRIPTION OF DRAWINGS

[0047] Figure 1 is a structure schematic view of the intraoperative brain tissue drift real-time correction device based on terahertz waves described in the embodiments of the present application.

[0048] Figure 2 For Figure 1 the structure diagram of the second telescopic column in the detector;

[0049] Figure 3 For Figure 2 the structure diagram of the second telescopic column in the detector;

[0050] Figure 4 For Figure 2 the structure diagram of the rotating column.

[0051] BRIEF DESCRIPTION OF DRAWINGS:

[0052] 1, detection body; 2, first telescopic column; 3, support part; 4, second telescopic column; 42, second axis; 5, rotating column; 51, first axis; 6, arc-shaped arm; 7, detection probe; 100, detector; 101, first pulley; 200, control console; 201, display; 202, second pulley; 300, operating bed; 301, detection platform. DETAILED DESCRIPTION

[0053] In order to make the above-mentioned purposes, features and advantages of the present application more obvious and easy to understand, the specific embodiments of the present application will be described in detail below with reference to the drawings.

[0054] Example 1

[0055] As Figures 1-4 shown, a terahertz wave-based intraoperative brain tissue drift real-time correction device, comprising:

[0056] A detector 100 is used for real-time detection of brain tissue during surgery, and the detector 100 comprises a detection body 1, the upper part of the detection body 1 is provided with a first telescopic column 2, the upper end of the first telescopic column 2 is provided with a support part 3, the first telescopic column 2 can be telescoped in the up-down direction relative to the detection body 1, and the position of the support part 3 in the up-down direction is adjusted;

[0057] The front part of the support part 3 is provided with a second telescopic column 4, the front part of the second telescopic column 4 is provided with a rotating column 5, the first axis 51 of the rotating column 5 coincides with the second axis 42 of the second telescopic column 4, the rotating column 5 can rotate around the first axis 51, and the second telescopic column 4 can be telescoped in the front-back direction relative to the support part 3, and the position of the rotating column 5 in the front-back direction is adjusted;

[0058] The front end of the rotating column 5 is provided with an arc-shaped arm 6, the rotating column 5 can drive the arc-shaped arm 6 to rotate around the first axis 51, and is used for adjusting the position of the arc-shaped arm 6;

[0059] The front end of the arc-shaped arm 6 is provided with a detection probe 7, which can emit terahertz waves to the brain tissue during the operation and receive the terahertz waves reflected by the brain tissue for detecting the brain tissue.

[0060] The console 200 is further provided with a processor, a compensator and a controller, the upper part of the console 200 is provided with a display 201, the processor is used to generate a real-time image according to the terahertz waves received by the detection probe 7, the compensator is used to receive the CT image and the real-time image, and generate a three-dimensional fusion image by combining the CT image and the real-time image, the display 201 is used to display the three-dimensional fusion image and input operation information, and the controller can control the working state of the detector 100 and the console 200 according to the input operation information.

[0061] The in-operation brain tissue drift real-time correction device based on terahertz waves can flexibly adjust the detection probe 7 in the up-down, front-back and rotating directions to adapt to different operation requirements and patient positions, and can detect the position of the patient's brain tissue in real time during the operation through terahertz waves, and generate a three-dimensional fusion image in combination with the CT image, so as to ensure that the position of the brain tissue in the operation is consistent with the position of the brain tissue in the three-dimensional fusion image, avoid the brain tissue drift caused by the loss of cerebrospinal fluid during the operation, and cause the difference between the shape and position of the brain tissue in the operation and the preoperative image, solve the problem of deviation between the operation and the preoperative planning caused by the brain tissue drift, and thus ensure the effective implementation of the operation plan and improve the accuracy of the operation navigation.

[0062] As a preferred example of the present application, the detection probe 7 comprises a transmitting module and a receiving module, the transmitting module is used to emit terahertz waves to the brain tissue during detection, and the receiving module is used to receive the terahertz waves reflected by the brain tissue.

[0063] Specifically, the transmitting module and the receiving module are integrated on one probe, so that the device is more compact, convenient to operate and install.

[0064] Preferably, one end of the operating bed 300 is provided with a detection platform 301, the detection platform 301 is provided with a fixer for fixing the head of the patient, and the detection platform 301 is located at the upper end of the detection probe. This arrangement can ensure that the patient's head remains stable during the operation, reduces the detection error caused by head movement, and improves the accuracy of the operation.

[0065] As a preferred example of the present application, the transmitting module comprises a plurality of transmitting probes, which can emit a plurality of groups of terahertz waves to the brain tissue at the same time, and the receiving module comprises a plurality of receiving probes for receiving the terahertz waves reflected by the head.

[0066] Specifically, by setting multiple transmitting probes and receiving probes, more data can be obtained at one time, the detection efficiency is improved, the total intensity of the signal is enhanced, the signal-to-noise ratio of the signal is improved, and thus the imaging quality is improved, because the reflected waves can be received from different angles, more detailed brain tissue structure information can be provided, the spatial resolution of the imaging is improved, and the multi-probe design can further optimize the penetration direction and angle of the beam and enhance the penetration ability of the brain tissue.

[0067] Preferably, the transmitting probe has the characteristics of high precision and low noise, ensuring the stability of the terahertz waves.

[0068] As a preferred example of the present application, the transmitting module is provided with a laser positioner capable of emitting laser light for positioning the detection position.

[0069] Specifically, before detection, the laser positioner can help the operator accurately move the detection probe 7 to the detection area, and the laser positioner is automatically turned off when the detection starts. This setting greatly improves the efficiency of device adjustment.

[0070] As a preferred example of the present application, the control console 200 is provided with a signal receiver for receiving CT image information from the outside.

[0071] Specifically, by setting the signal receiver, the doctor does not need to leave the operating room to obtain or check the CT image information, saving time and labor costs and improving the operation efficiency.

[0072] As a preferred example of the present application, the angle of rotation of the arc-shaped arm 6 is α, and 0°≤α≤360°, and the angular velocity is W, and 0≤W≤10 rad / s.

[0073] Specifically, the rotation range of 0° to 360° ensures comprehensive coverage of the patient's head, providing flexibility in detection, and a wide range of angular velocity allows rapid adjustment of position, improving operation efficiency and reducing time consumption during the operation or detection process.

[0074] As a preferred example of the present application, the lower end of the detector 100 is provided with a first pulley 101 for movement of the detector 100, and the lower end of the control console 200 is provided with a second pulley 202 for movement of the control console 200.

[0075] Specifically, the design of the pulleys enables flexible movement of the detector 100 and the control console 200, facilitating the doctor to adjust their positions to adapt to different surgical environments and patient needs.

[0076] As a preferred example of the present application, the processor preprocesses the received terahertz waves, converts the preprocessed analog signals into digital signals, compares the digital signals with the emission signals of the terahertz waves, obtains the reflection and attenuation degree information of the brain tissue at different positions on the terahertz waves, then generates a real-time image of the brain tissue using a back-projection algorithm, extracts the boundary information of the brain tissue from the generated real-time image, and calculates the offset between the brain tissue and the skull. The preprocessing includes filtering and amplification. The filtering is used to remove noise and interference in the terahertz waves and improve the signal-to-noise ratio of the signals. The amplification is used to enhance the intensity of the signals.

[0077] Specifically, through the filtering process, noise and interference in the terahertz wave signals can be effectively removed, and the signal-to-noise ratio of the signals can be improved, which helps to generate clearer and more accurate real-time images of the brain tissue. The amplification process enhances the intensity of the signals, making it easier to extract effective image information in subsequent processing and improving the visualization effect of the images. Extracting the boundary information of the brain tissue from the real-time image can accurately calculate the offset between the brain tissue and the skull, which is crucial for real-time tracking and correction of the position of the brain tissue during surgery and helps to reduce surgical errors caused by brain tissue drift.

[0078] The amplitude of the received digital signal reflects the intensity of the terahertz wave reflection signal. By comparing the amplitude of the received signal with the amplitude of the emission signal, the reflection coefficient can be calculated. The reflection coefficient is the ratio of the reflection signal intensity to the incident signal intensity. During the propagation of the terahertz wave, the phase will change due to the difference in medium. By analyzing the phase difference between the received signal and the emission signal, more details about the medium characteristics can be obtained. The attenuation degree of the terahertz wave can be obtained by comparing the amplitude difference between the emission signal and the received signal. Based on the analysis of the reflection coefficient, phase difference, and attenuation degree of the terahertz wave, the structural characteristics of the brain tissue at different positions can be calculated.

[0079] Extracting the boundary information of the brain tissue from the generated real-time image usually involves image processing techniques, such as edge detection algorithms (e.g., Canny edge detection). By identifying areas with significant intensity changes in the image, the boundaries of the brain tissue can be determined. The processor will compare this information with the preoperative CT image, calculate the distance between the brain tissue boundary in the real-time image and the corresponding boundary in the CT image using the least squares method, and obtain the offset between the brain tissue and the skull. These algorithms and the back-projection algorithm are all prior art and will not be described here.

[0080] As a preferred example of the present application, the compensator fuses the real-time image and the CT image to generate a three-dimensional fused image according to the offset between the brain tissue and the skull, so that the brain tissue in the three-dimensional fused image is consistent with the actual brain tissue; the fusion process includes the steps of:

[0081] S1: extracting feature points from the real-time image and the CT image using the FAST algorithm;

[0082] S2: matching the feature points in the real-time image and the CT image using the SIFT algorithm;

[0083] S3: calculating the geometric transformation between the real-time image and the CT image using the least squares method;

[0084] S4: adjusting the CT image using an elastic deformation model to adapt to different deformations, and resampling the deformed CT image to ensure that the real-time image and the CT image are accurately aligned in the same coordinate system;

[0085] S5: superimposing the aligned real-time image and the CT image together, and generating a three-dimensional fused image using a fusion algorithm.

[0086] Specifically, in S1, common feature point extraction algorithms include Harris corner detection, FAST, SIFT (Scale Invariant Feature Transform), etc. These algorithms can extract feature points with significant and stable characteristics from images, and are suitable for subsequent matching and alignment. In S2, common feature point matching algorithms include SIFT and SURF, which are powerful feature matching algorithms that can handle images of different scales and rotations. Through these algorithms, the feature points in the real-time image and the CT image can be effectively matched. In S3, common geometric transformation algorithms include the least squares method and RANSAC, which can effectively calculate the transformation relationship between the real-time image and the CT image. In S4, common elastic deformation models include B-spline and thin-plate spline, which can handle non-rigid deformation in images and adapt to possible deformation of brain tissue during surgery. The resampling process can ensure that the deformed CT image is spatially aligned with the real-time image. In S5, the three-dimensional fused image can be generated by weighted averaging, maximum value projection, etc. The fusion algorithm can combine the information of the real-time image and the CT image to generate a three-dimensional fused image with higher information content and clarity. The algorithms used in the fusion process are all existing technologies and will not be described here.

[0087] The fusion processing combines the real-time of the real-time image and the high definition and high resolution of the CT image, so that the three-dimensional fusion image contains the real-time position information of the brain tissue and maintains the structural details of the preoperative image, improves the overall definition and information amount of the image, reduces the deviation between the operation and the preoperative planning, improves the accuracy and success rate of the operation, and can provide more accurate navigation information for the doctor.

[0088] The application also provides a real-time correction method for brain tissue drift during operation, which is applied to the terahertz wave-based real-time correction device for brain tissue drift during operation and comprises the following steps:

[0089] Step 1: After the patient lies on the operating table 300, the head of the patient is fixed by using the fixer;

[0090] Step 2: The motion state of the first telescopic column 2, the second telescopic column 4 and the rotating column 5 is controlled to adjust the position of the detection probe 7 relative to the head;

[0091] Step 3: The position of the brain tissue lesion and the craniotomy incision is determined by using the preoperative CT image;

[0092] Step 4: The terahertz wave is emitted to the head of the patient by using the detection probe 7 to scan the head and obtain the initial position information of the brain tissue and the skull;

[0093] Step 5: After the operation starts, the relative position between the brain tissue and the skull is detected in real time by using the terahertz wave, and the offset amount between the brain tissue and the skull is calculated;

[0094] Step 6: When the position of the brain tissue is detected to be offset, the real-time image and the CT image are fused once every t time interval to generate a new three-dimensional fusion image;

[0095] Step 7: The generated three-dimensional fusion image is output by the display 201; wherein t is the interval time length between adjacent two three-dimensional fusion images, and the doctor can adjust t according to the need.

[0096] Specifically, the real-time correction method combines the real-time of the real-time image and the high definition and high resolution of the CT image by using real-time detection and dynamic adjustment, so that the three-dimensional fusion image contains the real-time position information of the brain tissue and maintains the structural details of the preoperative image, improves the overall definition and information amount of the image, ensures that the doctor can accurately master the actual position of the brain tissue during the operation, and adjusts the operation scheme in time.

[0097] In summary, the intraoperative brain tissue drift real-time correction device and method based on terahertz waves has the following advantages: 1) can detect the position of the patient's brain tissue in real time during the operation through terahertz waves, and generate a three-dimensional fusion image combined with the CT image, to ensure that the position of the brain tissue during the operation is consistent with the position of the brain tissue in the three-dimensional fusion image, avoid the brain tissue drift caused by the loss of cerebrospinal fluid during the operation, cause the difference between the shape and position of the brain tissue during the operation and the preoperative image, solve the problem of the deviation between the operation operation and the preoperative planning caused by the brain tissue drift, and thus ensure the effective implementation of the operation scheme and improve the accuracy of the operation navigation; 2) combines the real-time of the real-time image and the high definition and high resolution of the CT image, so that the three-dimensional fusion image contains not only the real-time position information of the brain tissue, but also the structure details of the preoperative image, improves the overall clarity and information amount of the image, and ensures that the doctor can accurately master the actual position of the brain tissue during the operation and timely adjust the operation scheme.

[0098] Although the present application is disclosed as above, it is not limited thereto. Any person skilled in the art, without departing from the spirit and scope of the present application, can make various changes and modifications, and therefore the protection scope of the present application should be limited by the scope defined by the claims.

Claims

1. A real-time correction device for intraoperative brain tissue drift based on terahertz waves, characterized in that: include: A detector (100) is used for detecting brain tissue in real time during surgery. The detector (100) comprises a detection body (1). A first telescopic column (2) is provided on the upper portion of the detection body (1). A support portion (3) is provided at the upper end of the first telescopic column (2). The first telescopic column (2) can be telescoped in the vertical direction relative to the detection body (1) to adjust the position of the support portion (3) in the vertical direction. A second telescopic column (4) is provided at the front portion of the support portion (3). A rotating column (5) is provided at the front of the support portion (3); a first axis (51) of the rotating column (5) coincides with a second axis (42) of the second telescopic column (4); the rotating column (5) can rotate around the first axis (51); the second telescopic column (4) can be telescoped in the front-to-back direction relative to the support portion (3) to adjust the position of the rotating column (5) in the front-to-back direction; an arc-shaped arm (6) is provided at the front end of the rotating column (5); the rotating column (5) can drive the arc-shaped arm (6) to rotate around the first axis (51) to adjust the position of the arc-shaped arm (6); A detection probe (7) is provided at the front end of the arc-shaped arm (6). The detection probe (7) is capable of transmitting terahertz waves to the brain tissue during surgery and receiving terahertz waves reflected back from the brain tissue for detecting the brain tissue. After the surgery begins, the terahertz waves are used to detect the relative position between the brain tissue and the skull in real time, and the offset between the brain tissue and the skull is calculated. A console (200) is provided with a processor, a compensator, and a controller. A display (201) is provided on the upper portion of the console (200). The processor is used to generate a real-time image based on the terahertz wave received by the detection probe (7). The compensator is used to receive a CT image and a real-time image and generate a three-dimensional fused image by combining the CT image and the real-time image. The display (201) is used to display the three-dimensional fused image and to input operation information. The controller can control the working state of the detector (100) and the console (200) based on the input operation information.

2. The device for real-time correction of intraoperative brain tissue drift based on terahertz waves according to claim 1, characterized in that: The detection probe (7) comprises a transmitting module and a receiving module, wherein the transmitting module is used to transmit terahertz waves to brain tissue during detection, and the receiving module is used to receive the terahertz waves reflected back by the brain tissue.

3. The device for real-time correction of intraoperative brain tissue drift based on terahertz waves according to claim 2, characterized in that: The transmitting module includes multiple transmitting probes, which can simultaneously transmit multiple groups of terahertz waves to brain tissue. The receiving module includes multiple receiving probes, which are used to receive the terahertz waves reflected back from the head.

4. The device for real-time correction of intraoperative brain tissue drift based on terahertz waves according to claim 2, characterized in that: The transmitting module is provided with a laser locator, which can emit laser for locating a position to be detected.

5. The device for real-time correction of intraoperative brain tissue drift based on terahertz waves according to claim 1, characterized in that: A signal receiver is provided in the console (200), and the signal receiver is used to receive CT image information from the outside world.

6. The device for real-time correction of intraoperative brain tissue drift based on terahertz waves according to claim 1, characterized in that: The arc-shaped arm (6) rotates at an angle α, 0°≤α≤360°, and an angular velocity W, 0≤W≤10 rad / s.

7. The device for real-time correction of intraoperative brain tissue drift based on terahertz waves according to claim 1, characterized in that: A first pulley (101) is provided at the lower end of the detector (100), and the first pulley (101) is used for moving the detector (100). A second pulley (202) is provided at the lower end of the console (200), and the second pulley (202) is used for moving the console (200).

8. The device for real-time correction of intraoperative brain tissue drift based on terahertz waves according to claim 1, characterized in that: The processor pre-processes the received terahertz waves and converts the pre-processed analog signals into digital signals. The digital signals are then compared with the transmitted signals of the terahertz waves to obtain information on the reflection and attenuation of the terahertz waves by brain tissue at different locations. A back-projection algorithm is then used to generate a real-time image of the brain tissue. The boundary information of the brain tissue is extracted from the generated real-time image, and the offset between the brain tissue and the skull is calculated. The pre-processing includes filtering and amplification. The filtering is used to remove noise and interference in the terahertz waves and improve the signal-to-noise ratio of the signal. The amplification is used to enhance the strength of the signal.

9. The device for real-time correction of intraoperative brain tissue drift based on terahertz waves according to claim 8, characterized in that: The compensator fuses the real-time image and the CT image according to the offset between the brain tissue and the skull to generate a three-dimensional fused image, so that the position of the brain tissue in the three-dimensional fused image is consistent with the actual brain tissue. The fusion process includes the following steps: S1: extracting feature points from the real-time image and the CT image using the FAST algorithm; S2: matching the feature points in the real-time image and the CT image using the SIFT algorithm; S3: calculating the geometric transformation between the real-time image and the CT image using the least squares method; S4: Using the elastic deformation model to adjust the CT image to adapt to different deformations, the deformed CT image is resampled to ensure that the real-time image and the CT image are accurately aligned in the same coordinate system; S5: The aligned real-time image is superimposed on the CT image, and a fusion algorithm is used to generate a three-dimensional fused image.

10. A method for real-time correction of intraoperative brain tissue drift, applied to the device for real-time correction of intraoperative brain tissue drift based on terahertz waves according to any one of claims 1 to 9, characterized in that: The following steps are involved: Step 1: After the patient lies on the operating table (300), the patient's head is fixed using a fixator; Step 2: Control the motion states of the first telescopic column (2), the second telescopic column (4) and the rotating column (5), and adjust the position of the detection probe (7) relative to the head; Step 3: Use preoperative CT images to determine the location of brain lesions and craniotomy incision; Step 4: using the detection probe (7) to transmit terahertz waves to the patient's head to scan the head and obtain initial position information of the brain tissue and skull; Step 5: After the operation begins, the relative position between the brain tissue and the skull is detected in real time using terahertz waves to calculate the offset between the brain tissue and the skull; Step 6: When the position of the brain tissue is detected to be shifted, the real-time image and the CT image are fused once every t time interval to generate a new 3D fused image; Step 7: The display (201) outputs the generated three-dimensional fused image.

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