A liver surgery assisting apparatus

Abstract

The application discloses a kind of liver surgery auxiliary device, including image acquisition unit, image acquisition unit is used to obtain intraoperative ultrasound image and fluoroscopy image, analysis unit, analysis unit is used to analyze intraoperative ultrasound image, obtain the boundary parameter of focus and surrounding tissue;First judging unit, first judging unit is used to judge whether boundary parameter is greater than preset first threshold value;First comparison unit, if boundary parameter is greater than preset first threshold value, first comparison unit is used to compare intraoperative focus image and calibration parameter image, obtain first coincidence degree;Second judging unit, second judging unit is used to judge whether first coincidence degree is less than preset second threshold value;First prompt unit, if first coincidence degree is less than preset first threshold value, first prompt unit is used to generate first prompt signal, doctor can know the consistency of ultrasound image and actual focus size in time during operation, so adjustment can be made quickly.

Description

Technical Field

[0001] This invention relates to the field of computer technology, and in particular to a liver surgery assistive device. Background Technology

[0002] Laparoscopic liver surgery is a minimally invasive surgical procedure that involves making a small incision in the patient's abdomen and inserting a laparoscope and other surgical instruments. Currently, imaging devices allow the surgical procedure to be performed on a visualized screen. This facilitates the operator's viewing of images and accurate identification of liver lesions, which are crucial steps in planning safe cutting paths during laparoscopic surgery. However, existing technologies present some problems and challenges.

[0003] In existing technologies, surgeons typically need to adjust the surgical path in real time based on image information reflecting the surgical status. The accuracy and feasibility of the image information provided by the equipment are clearly crucial for aiding conclusions. During actual operations, surgeons often rely on intraoperative ultrasound or fluorescence imaging for judgment. However, this judgment is often based on experience and the accuracy of the intraoperative ultrasound or fluorescence imaging. If the lesion image shown in the intraoperative ultrasound or fluorescence imaging does not match the actual lesion size or deviates from it, it will obviously cause certain biases and risks in the surgeon's intraoperative perception, leading to inconsistencies between the image data and the actual surgical path required, thus affecting the expected conclusions. Therefore, how to optimize the accuracy of the data and the security of the auxiliary data warrants further research. Summary of the Invention

[0004] To address the problem in existing technologies where the lesion image displayed by intraoperative ultrasound or fluorescence contrast imaging does not match the actual size of the lesion, and doctors cannot be informed in a timely manner during surgery, this invention provides a liver surgery auxiliary device.

[0005] The technical solution adopted in this invention is: a liver surgery auxiliary device, comprising...

[0006] An image acquisition unit is used to acquire intraoperative ultrasound images and fluorescence contrast images, wherein the intraoperative ultrasound images include intraoperative liver images, intraoperative lesion images, and images of the lesion and surrounding tissues;

[0007] An analysis unit is connected to the image acquisition unit. The analysis unit is used to analyze the intraoperative ultrasound image to obtain the boundary parameters between the lesion and the surrounding tissue.

[0008] A storage unit, wherein the storage unit stores a preset first threshold, a calibration parameter image, a preset second threshold, and a preset third threshold;

[0009] A first judgment unit is connected to the analysis unit and the storage unit respectively. The first judgment unit is used to determine whether the boundary parameter is greater than a preset first threshold.

[0010] The first comparison unit is connected to the first judgment unit, the image acquisition unit, and the storage unit respectively. If the boundary parameter is greater than a preset first threshold, the first comparison unit is used to compare the intraoperative lesion image with the calibration parameter image to obtain a first comparison result, wherein the first comparison result includes the first overlap between the intraoperative lesion image and the calibration parameter image.

[0011] The second judgment unit is connected to the first comparison unit and the storage unit. The second judgment unit is used to determine whether the first overlap is less than a preset second threshold.

[0012] A first prompting unit is connected to the second judgment unit. If the first overlap is less than a preset first threshold, the first prompting unit is used to generate a first prompting signal.

[0013] Preferably, it further includes: a second comparison unit, which is connected to the first judgment unit, the image acquisition unit, and the storage unit respectively. If the boundary parameter is less than or equal to a preset first threshold, the second comparison unit is used to compare the fluorescence imaging image with the calibration parameter image to obtain a second comparison result, wherein the second comparison result includes a second overlap between the fluorescence imaging image and the calibration parameter image.

[0014] The third judgment unit is connected to the second comparison unit and the storage unit respectively; the third judgment unit is used to determine whether the second overlap is less than a preset third threshold.

[0015] The second prompting unit is connected to the third judgment unit. If the second overlap is less than a preset third threshold, the second prompting unit is used to generate a second prompting signal.

[0016] Preferably, the analysis unit includes a first analysis subunit and a second analysis subunit, the first analysis subunit and the second analysis subunit being connected to the image acquisition unit respectively, and the boundary parameters including the edge parameters of the lesion and the surrounding tissue and the texture parameters of the lesion surface;

[0017] The first analysis subunit is used to analyze the intraoperative ultrasound image to obtain the edge parameters of the lesion and surrounding tissue;

[0018] The second analysis subunit is used to analyze the intraoperative ultrasound image to obtain the texture parameters of the lesion surface.

[0019] Preferably, the first judgment unit includes a first judgment subunit and a second judgment subunit, and the preset first threshold includes a preset edge parameter threshold and a preset texture parameter threshold;

[0020] The first judgment subunit is used to determine whether the edge parameter between the lesion and the surrounding tissue is greater than a preset edge parameter threshold;

[0021] The second judgment subunit is used to determine whether the texture parameter of the lesion surface is greater than a preset texture parameter threshold.

[0022] Preferably, the first comparison unit includes a pixel extraction subunit, which is connected to the first judgment unit, the image acquisition unit, and the storage unit respectively. The pixel extraction subunit is used to extract the pixel values ​​of the intraoperative lesion image and the pixel values ​​of the calibration parameter image.

[0023] A pixel comparison subunit is connected to the pixel extraction subunit. The pixel comparison subunit is used to compare the pixel values ​​of the lesion image and the pixel values ​​of the calibration parameter image to generate a pixel comparison result.

[0024] A first overlap calculation subunit is connected to the pixel comparison subunit. The first overlap calculation subunit is used to calculate a similarity value based on the comparison result and use the similarity value as the first overlap.

[0025] Preferably, the second comparison unit includes a feature extraction subunit, which is connected to the first judgment unit, the image acquisition unit, and the storage unit respectively, and is used to extract features from the fluorescence imaging image and the calibration parameter image.

[0026] A feature comparison subunit is connected to the feature extraction subunit. The feature comparison subunit is used to compare the features extracted by the feature extraction subunit and generate a feature comparison result.

[0027] The second overlap calculation subunit is connected to the feature comparison subunit, and the second overlap calculation subunit calculates the second overlap based on the feature comparison result.

[0028] One possible beneficial effect of this invention is as follows: First, an image acquisition unit acquires intraoperative ultrasound images and fluorescence contrast images. These images include intraoperative liver images, intraoperative lesion images, and images of the lesion and surrounding tissues. An analysis unit analyzes these images and extracts boundary parameters between the lesion and surrounding tissues. This step provides the doctor with boundary information regarding the relationship between the lesion and surrounding tissues, allowing the doctor to choose whether to use the intraoperative ultrasound image or the fluorescence contrast image as the preferred reference. A first judgment unit makes a judgment based on the boundary parameters provided by the analysis unit. If the boundary parameters are greater than a preset first threshold, it indicates that the boundary between the lesion and surrounding tissues is clear, and further image comparison is needed. After determining the images to be compared, the first comparison unit compares the intraoperative lesion image with the calibration parameter image and calculates their overlap, i.e., the first overlap. This step helps the doctor understand the similarity between the intraoperative lesion image and the calibration parameter image. A second judgment unit judges the first overlap. If the first overlap is less than a preset second threshold, it indicates that there is a significant difference between the intraoperative lesion image and the calibration parameter image, requiring the doctor to be alerted. When the initial overlap is less than a preset first threshold, the first prompting unit will generate a prompt signal to inform the doctor that adjustments are needed. This solution allows doctors to promptly ascertain the consistency between the ultrasound image and the actual lesion size during surgery, enabling them to make quick adjustments. Attached Figure Description

[0029] Figure 1 This is a system overall block diagram of Embodiment 1 of this application;

[0030] Figure 2 This is a system overall block diagram of Embodiment 2 of this application.

[0031] Figure 3 This is a structural block diagram of the analysis unit in Embodiment 2 of this application;

[0032] Figure 4 This is a structural block diagram of the first comparison unit in Embodiment 2 of this application;

[0033] Figure 5 This is a block diagram of the second comparison unit in Embodiment 2 of this application.

[0034] Figure Descriptions: 10, Image Acquisition Unit; 20, Analysis Unit; 201, First Analysis Subunit; 202, Second Analysis Subunit; 30, Storage Unit; 40, First Judgment Unit; 401, First Judgment Subunit; 402, Second Judgment Subunit; 50, First Comparison Unit; 501, Pixel Extraction Subunit; 502, Pixel Comparison Subunit; 503, First Overlap Calculation Subunit; 60, Second Judgment Unit; 70, First Prompt Unit; 80, Second Comparison Unit; 801, Feature Extraction Subunit; 802, Feature Comparison Subunit; 803, Second Overlap Calculation Subunit; 90, Third Judgment Unit; 100, Second Prompt Unit. Detailed Implementation

[0035] The embodiments of the present invention will now be described in detail with reference to the accompanying drawings.

[0036] In current techniques, surgeons typically need to adjust the surgical path in real time based on the surgical situation. When making these adjustments, surgeons often refer to intraoperative ultrasound or fluorescence imaging images. This adjustment relies on the accuracy of the intraoperative ultrasound or fluorescence imaging. However, because the distribution and flow of contrast agent are affected by various factors, the lesion area shown by the contrast agent may not match the actual lesion area. This leads to a discrepancy between the area enclosed by the pre-planned cutting path and the lesion area shown by the contrast agent. The accuracy of intraoperative ultrasound is affected by various factors, such as the quality of the equipment, the surgeon's skill, and the scanning angle and depth. If the lesion image shown by the intraoperative ultrasound or fluorescence imaging does not match the actual lesion size, and the surgeon cannot detect this in time during the procedure, the adjustment of the surgical path may not meet expectations.

[0037] Example 1

[0038] To address the issue of surgeons not being able to promptly detect discrepancies between intraoperative ultrasound images and calibration parameter images, such as... Figure 1 As shown, this embodiment provides a liver surgery assistance device, including...

[0039] The image acquisition unit 10 is used to acquire intraoperative ultrasound images, including intraoperative liver images, intraoperative lesion images, and images of the lesion and surrounding tissues. The image acquisition unit 10 can be a commonly used intraoperative ultrasound imaging device, typically comprising an ultrasound probe, an image acquisition unit, an image processor, and a display. The ultrasound probe transmits ultrasound waves and receives reflected ultrasound signals. The image acquisition unit and image processor then convert the received signals into digital image data, which is finally displayed on the monitor.

[0040] An analysis unit 20, connected to the image acquisition unit 10, analyzes the intraoperative ultrasound images to obtain boundary parameters between the lesion and surrounding tissues. The analysis unit 20 can be a common image processing chip specifically designed for processing image data, including performing various operations and analyses. The image processing chip may include dedicated hardware logic circuits and memory to achieve efficient image processing tasks. Connected to the image acquisition unit 10, the image processing chip can receive intraoperative ultrasound image data, analyze the images, and extract boundary parameters between the lesion and surrounding tissues. Boundary parameters are parameters used to describe or distinguish different regions or objects when analyzing images or signals. In the above image analysis, boundary parameters may include edge parameters between the lesion and surrounding tissues and texture parameters of the lesion surface.

[0041] The storage unit 30 stores a preset first threshold, a calibration parameter image, a preset second threshold, and a preset third threshold. The storage unit 30 can be a common type of memory, including random access memory (RAM), read-only memory (ROM), or electrically erasable programmable read-only memory (EEPROM). By storing the preset first threshold, calibration parameter image, preset second threshold, and preset third threshold in a memory chip, the storage unit 30 can acquire and save this data for subsequent use.

[0042] A first judgment unit 40 is connected to both the analysis unit 20 and the storage unit 30. The first judgment unit 40 is used to determine whether the boundary parameter is greater than a preset first threshold. The first judgment unit 40 can be a microprocessor, a common type of computing and control unit capable of performing various arithmetic and logical operations. By connecting to the analysis and storage unit, the microprocessor can receive and analyze the boundary parameter and compare it against the preset first threshold. The microprocessor can run corresponding algorithms and instructions and perform appropriate operations based on the judgment result, such as issuing an alarm or controlling other devices.

[0043] A first comparison unit 50 is connected to the first judgment unit 40, the image acquisition unit 10, and the storage unit 30. If the boundary parameter is greater than a preset first threshold, the first comparison unit 50 compares the intraoperative lesion image with the calibration parameter image to obtain a first comparison result. The first comparison result includes a first degree of overlap between the intraoperative lesion image and the calibration parameter image; the meaning of the first degree of overlap is not specified. The first comparison unit 50 can be a common graphics processing unit (GPU), a device specifically designed for processing graphics data. Connected to the first judgment unit, the image acquisition unit, and the storage unit, the GPU can receive the boundary parameter, the intraoperative lesion image, and the calibration parameter image. When the boundary parameter is greater than the preset first threshold, the GPU can utilize its powerful parallel processing capabilities to run a comparison algorithm, perform image comparison, and calculate the first degree of overlap. The first degree of overlap refers to the degree of overlap between the intraoperative lesion image and the calibration parameter image. It measures the similarity and consistency of two images in terms of spatial location, shape, and size.

[0044] When the intraoperative lesion image and the calibration parameter image have a high degree of overlap, it indicates that the lesion is accurately located and the surgical procedure is proceeding normally. However, when the overlap is low, it suggests that there may be a deviation in lesion location or a problem with the surgical procedure, requiring the doctor or operator to pay attention and take appropriate measures to correct and adjust.

[0045] The second judgment unit 60 is connected to the first comparison unit 50 and the storage unit 30. The second judgment unit 60 is used to determine whether the first overlap is less than a preset second threshold.

[0046] A first prompting unit 70 is connected to the second judgment unit 60. If the first overlap degree is less than a preset first threshold, the first prompting unit 70 generates a first prompt signal. The first prompting unit 70 can be a conventional screen display device, which can display information such as text, images, or videos, and can also be used to generate prompt signals. The first prompting unit 70 can be connected to a screen display device to display corresponding prompt information on the screen when the first overlap degree is less than the preset first threshold.

[0047] In this embodiment, intraoperative ultrasound and fluorescence imaging images are first acquired by the image acquisition unit 10. These images include intraoperative liver images, intraoperative lesion images, and images of the lesion and surrounding tissues. The analysis unit 20 analyzes these images and extracts boundary parameters between the lesion and surrounding tissues. This step provides the doctor with important information about the relationship between the lesion and surrounding tissues. The first judgment unit 40 makes a judgment based on the boundary parameters provided by the analysis unit 20. If the boundary parameters are greater than a preset first threshold, it indicates that the boundary between the lesion and surrounding tissues is clear. When the boundary between the lesion and surrounding tissues is relatively clear, the doctor may rely more on ultrasound images to observe the real-time dynamic information of the lesion.

[0048] Therefore, it is necessary to compare the lesion image with the calibration parameter image at this time. The first comparison unit 50 compares the intraoperative lesion image with the calibration parameter image and calculates their overlap, i.e., the first overlap. This step helps the doctor understand the similarity between the intraoperative lesion image and the calibration parameter image. The second judgment unit 60 judges the first overlap. If the first overlap is less than the preset second threshold, it indicates that there is a large difference between the intraoperative lesion image and the calibration parameter image, and the doctor needs to be alerted. When the first overlap is less than the preset first threshold, the first prompting unit 70 will generate a prompt signal to inform the doctor that adjustments are needed. Through this scheme, the doctor can know the consistency between the ultrasound image and the actual lesion size in a timely manner during the operation, and thus can make adjustments quickly.

[0049] Example 2:

[0050] Considering that intraoperative ultrasound and fluorescence imaging are used in combination during liver resection surgery, and to address the issue that the lesion images displayed by intraoperative ultrasound and fluorescence imaging do not match the actual lesion size, and that surgeons cannot promptly detect this discrepancy during surgery, this application provides a liver surgery auxiliary device, comprising:

[0051] Image acquisition unit 10, the image acquisition unit 10 is used to acquire intraoperative ultrasound images and fluorescence contrast images, wherein the intraoperative ultrasound images include intraoperative liver images, intraoperative lesion images, and images of the lesion and surrounding tissues;

[0052] Analysis unit 20, which is connected to image acquisition unit 10, is used to analyze the intraoperative ultrasound image to obtain boundary parameters between the lesion and surrounding tissues;

[0053] Storage unit 30, wherein the storage unit 30 stores a preset first threshold, a calibration parameter image, a preset second threshold, and a preset third threshold;

[0054] The first judgment unit 40 is connected to the analysis unit 20 and the storage unit 30 respectively. The first judgment unit 40 is used to determine whether the boundary parameter is greater than a preset first threshold.

[0055] The first comparison unit 50 is connected to the first judgment unit 40, the image acquisition unit 10, and the storage unit 30 respectively. If the boundary parameter is greater than a preset first threshold, the first comparison unit 50 is used to compare the intraoperative lesion image with the calibration parameter image to obtain a first comparison result, wherein the first comparison result includes the first overlap between the intraoperative lesion image and the calibration parameter image.

[0056] The second judgment unit 60 is connected to the first comparison unit 50 and the storage unit 30. The second judgment unit 60 is used to determine whether the first overlap is less than a preset second threshold.

[0057] The first prompting unit 70 is connected to the second judgment unit 60. If the first overlap is less than a preset first threshold, the first prompting unit is used to generate a first prompting signal.

[0058] The second comparison unit 80 is connected to the first judgment unit 40, the image acquisition unit 10, and the storage unit 30 respectively. If the boundary parameter is less than or equal to a preset first threshold, the second comparison unit is used to compare the fluorescence imaging image with the calibration parameter image to obtain a second comparison result, wherein the second comparison result includes the second overlap between the fluorescence imaging image and the calibration parameter image.

[0059] The third judgment unit 90 is connected to the second comparison unit 80 and the storage unit 30 respectively; the third judgment unit 90 is used to determine whether the second overlap is less than a preset third threshold.

[0060] The second prompting unit 100 is connected to the third judgment unit 90. If the second overlap is less than a preset third threshold, the second prompting unit 100 generates a second prompting signal.

[0061] In this embodiment, the image acquisition unit 10 first acquires intraoperative ultrasound and fluorescence contrast images. These images include intraoperative liver images, intraoperative lesion images, and images of the lesion and surrounding tissues. Next, the analysis unit 20 analyzes these images to extract boundary parameters between the lesion and surrounding tissues. This step provides the physician with important information about the relationship between the lesion and surrounding tissues. Then, the first judgment unit 40 makes a judgment based on the boundary parameters provided by the analysis unit.

[0062] If the boundary parameter is greater than the preset first threshold, it indicates that the boundary between the lesion and the surrounding tissue is clear. When the boundary between the lesion and the surrounding tissue is relatively clear, doctors may rely more on intraoperative ultrasound images to observe the real-time dynamic information of the tumor. If the boundary parameter is less than the preset first threshold, it indicates that the boundary between the lesion and the surrounding tissue is unclear. When the boundary between the lesion and the surrounding tissue is unclear, doctors may rely more on fluorescence imaging to determine the extent of tumor resection.

[0063] Therefore, when the boundary between the lesion and surrounding tissue is relatively clear, the first comparison unit 50 compares the intraoperative lesion image with the calibration parameter image and calculates their overlap, i.e., the first overlap. This step helps the doctor understand the similarity between the intraoperative lesion image and the calibration parameter image. The second judgment unit 60 judges the first overlap. If the first overlap is less than a preset second threshold, it indicates that there is a large difference between the intraoperative lesion image and the calibration parameter image, and the doctor needs to be alerted. When the first overlap is less than a preset first threshold, the first prompting unit 70 generates a prompt signal to inform the doctor that adjustments are needed.

[0064] When the boundary between the lesion and surrounding tissue is unclear, the second comparison unit 80 compares the fluorescence imaging image with the calibration parameter image to calculate a second degree of overlap. The third judgment unit 90 judges the second degree of overlap. If the second degree of overlap is less than a preset third threshold, it indicates a significant difference between the fluorescence imaging image and the calibration parameter image, which also requires the doctor's attention. When the second degree of overlap is less than the preset third threshold, the second prompting unit 100 generates a prompt signal to inform the doctor that the fluorescence imaging image may be abnormal.

[0065] This approach allows doctors to monitor the consistency between ultrasound or fluorescence imaging and the actual lesion size during surgery, enabling them to make rapid adjustments and ensure the smooth progress of the procedure and the patient's safety.

[0066] In one possible implementation, such as Figure 3 As shown, the analysis unit 20 includes a first analysis subunit 201 and a second analysis subunit 202. The first analysis subunit 201 and the second analysis subunit 202 are respectively connected to the image acquisition unit 10. The boundary parameters include the edge parameters between the lesion and the surrounding tissue and the texture parameters of the lesion surface.

[0067] The first analysis subunit 201 is used to analyze the intraoperative ultrasound image to obtain the edge parameters of the lesion and surrounding tissue;

[0068] The second analysis subunit 202 is used to analyze the intraoperative ultrasound image to obtain the texture parameters of the lesion surface.

[0069] The first judgment unit 40 includes a first judgment subunit 401 and a second judgment subunit 402. The first judgment subunit 401 is connected to the first analysis subunit 201 and the storage unit 30, respectively. The second judgment subunit 402 is connected to the second analysis subunit 202 and the storage unit 30, respectively. The preset first threshold includes a preset edge parameter threshold and a preset texture parameter threshold.

[0070] The first judgment subunit 401 is used to determine whether the edge parameter between the lesion and the surrounding tissue is greater than a preset edge parameter threshold.

[0071] The second judgment subunit 402 is used to determine whether the texture parameter of the lesion surface is greater than a preset texture parameter threshold.

[0072] When the edge parameter between the lesion and the surrounding tissue is greater than the preset edge parameter threshold or the texture parameter on the lesion surface is greater than the preset texture parameter threshold, it indicates that the boundary between the lesion and the surrounding tissue is unclear.

[0073] In this embodiment, by refining the image analysis task, the analysis of edge and texture parameters can be more precise and detailed. This improves the understanding of lesion boundaries and surface features, contributing to a more accurate assessment of the condition. Processing and judging edge and texture parameters separately reduces the complexity of the analysis and improves its efficiency. Furthermore, setting separate thresholds for edge and texture parameters better adapts to different conditions and types of lesions, making the analysis results more reliable.

[0074] In one possible implementation, such as Figure 4 As shown, the first comparison unit 50 includes:

[0075] The pixel extraction subunit 501 is connected to the first judgment unit 40, the image acquisition unit 10, and the storage unit 30, respectively. The pixel extraction subunit 501 is used to extract the pixel values ​​of the intraoperative lesion image and the pixel values ​​of the calibration parameter image.

[0076] A pixel comparison subunit 502 is connected to the pixel extraction subunit 501. The pixel comparison subunit 502 is used to compare the pixel values ​​of the lesion image and the pixel values ​​of the calibration parameter image to generate a pixel comparison result.

[0077] A first overlap calculation subunit 503 is connected to the pixel comparison subunit 502. The first overlap calculation subunit 503 is used to calculate a similarity value based on the comparison result and use the similarity value as the first overlap.

[0078] In this embodiment, by extracting and comparing the pixel values ​​of the lesion image and the calibration parameter image, the similarity and difference between them can be determined more accurately. By calculating the similarity value as the first degree of overlap, the degree of matching between the intraoperative lesion image and the calibration parameter image can be quantitatively assessed.

[0079] In one possible implementation, such as Figure 5 As shown, the second comparison unit 80 includes:

[0080] A feature extraction subunit 801 is connected to the first judgment unit 40, the image acquisition unit 10, and the storage unit 30, respectively. The feature extraction subunit 801 is used to extract features from the fluorescence imaging image and the calibration parameter image.

[0081] Feature comparison subunit 802 is connected to feature extraction subunit 801. Feature comparison subunit 802 is used to compare the features extracted by feature extraction subunit 801 and generate feature comparison results.

[0082] The second overlap calculation subunit 803 is connected to the feature comparison subunit 802, and the second overlap calculation subunit 803 calculates the second overlap degree based on the feature comparison result.

[0083] In this embodiment, feature extraction subunit 801 can extract features from fluorescence imaging images and calibration parameter images, which helps to better understand the morphology and characteristics of tumors. The feature comparison results can be used to calculate the second degree of overlap, quantitatively assess the degree of matching between fluorescence imaging images and calibration parameter images. Through the second degree of overlap calculation subunit, doctors can obtain the degree of matching between fluorescence imaging images and calibration parameter images.

[0084] The embodiments described above are merely illustrative of specific implementations of the present invention, and while the descriptions are detailed, they should not be construed as limiting the scope of the present invention. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of the present invention, and these modifications and improvements all fall within the scope of protection of the present invention.

Claims

1. A liver surgery assist device, comprising an image acquisition unit, characterized in that: It also includes an analysis unit connected to the image acquisition unit. The image acquisition unit acquires intraoperative ultrasound images and fluorescence contrast images. The analysis unit analyzes the intraoperative ultrasound images and obtains the boundary parameters between the lesion and surrounding tissues. The intraoperative ultrasound images include intraoperative liver images, intraoperative lesion images, and images of the lesion and surrounding tissues. The device also includes: A storage unit, wherein a first threshold, a calibration parameter image, a second threshold, and a third threshold are configured within the storage unit; A first judgment unit is connected to the analysis unit and the storage unit respectively. The first judgment unit is used to determine whether the boundary parameter is greater than a preset first threshold. The first comparison unit is connected to the first judgment unit, the image acquisition unit, and the storage unit respectively. If the boundary parameter is greater than a preset first threshold, the first comparison unit is used to compare the intraoperative lesion image with the calibration parameter image to obtain a first comparison result, wherein the first comparison result includes the first overlap between the intraoperative lesion image and the calibration parameter image. The second judgment unit is connected to the first comparison unit and the storage unit. The second judgment unit is used to determine whether the first overlap is less than a preset second threshold. A first prompting unit is connected to the second judgment unit. If the first overlap is less than a preset second threshold, the first prompting unit is used to generate a first prompting signal. Also includes: The second comparison unit is connected to the first judgment unit, the image acquisition unit, and the storage unit respectively. If the boundary parameter is less than or equal to a preset first threshold, the second comparison unit is used to compare the fluorescence imaging image with the calibration parameter image to obtain a second comparison result. The second comparison result includes the second overlap between the fluorescence imaging image and the calibration parameter image. The third judgment unit is connected to the second comparison unit and the storage unit respectively; the third judgment unit is used to determine whether the second overlap is less than a preset third threshold. The second prompting unit is connected to the third judgment unit. If the second overlap is less than a preset third threshold, the second prompting unit is used to generate a second prompting signal. The analysis unit includes a first analysis subunit and a second analysis subunit, which are respectively connected to the image acquisition unit. The boundary parameters include edge parameters between the lesion and surrounding tissues, and the boundary parameters also include texture parameters of the lesion surface. The first analysis subunit is used to analyze the intraoperative ultrasound image to obtain the edge parameters of the lesion and surrounding tissue; The second analysis subunit is used to analyze the intraoperative ultrasound image to obtain the texture parameters of the lesion surface; The first judgment unit includes a first judgment subunit and a second judgment subunit. The first judgment subunit is connected to the first analysis subunit and the storage unit, respectively, and the second judgment subunit is connected to the second analysis subunit and the storage unit, respectively. The preset first threshold includes a preset edge parameter threshold and a preset texture parameter threshold. The first judgment subunit is used to determine whether the edge parameter between the lesion and the surrounding tissue is greater than a preset edge parameter threshold; The second judgment subunit is used to determine whether the texture parameter of the lesion surface is greater than a preset texture parameter threshold; The first comparison unit includes: A pixel extraction subunit is connected to the first judgment unit, the image acquisition unit, and the storage unit, respectively. The pixel extraction subunit is used to extract the pixel values ​​of the intraoperative lesion image and the pixel values ​​of the calibration parameter image. A pixel comparison subunit is connected to the pixel extraction subunit. The pixel comparison subunit is used to compare the pixel values ​​of the intraoperative lesion image and the pixel values ​​of the calibration parameter image to generate a pixel comparison result. A first overlap calculation subunit is connected to the pixel comparison subunit. The first overlap calculation subunit is used to calculate a similarity value based on the pixel comparison result and use the similarity value as the first overlap.

2. The liver surgery auxiliary device according to claim 1, characterized in that, The second comparison unit includes: A feature extraction subunit is connected to the first judgment unit, the image acquisition unit, and the storage unit, respectively. The feature extraction subunit is used to extract features from the fluorescence imaging image and the calibration parameter image. A feature comparison subunit is connected to the feature extraction subunit. The feature comparison subunit is used to compare the features extracted by the feature extraction subunit and generate a feature comparison result. The second overlap calculation subunit is connected to the feature comparison subunit, and the second overlap calculation subunit calculates the second overlap based on the feature comparison result.

Images