A 4K laparoscopic imaging device

Abstract

This utility model relates to a 4K laparoscopic imaging device, belonging to the field of image processing technology. The device includes a cold light source, an insufflator, a photosensitive element, an optical rigid lens, a camera, a camera connection cable, a camera host, a signal connection cable, and a back-end device. It employs a noise reduction module and a total latency algorithm module to achieve low-latency, high-pixel transmission while ensuring complete preservation of image information. The powerful back-end host better handles image processing, guaranteeing the final image quality. It reduces image information loss caused by image processing at the camera module level and overcomes problems such as increased module temperature, component damage, and reduced image quality associated with image processing at the camera module level. It can be applied in the field of laparoscopic imaging.

Description

Technical Field

[0001] This utility model relates to the field of image processing technology, and in particular to a 4K laparoscopic imaging device. Background Technology

[0002] An endoscope is typically inserted into the body of the patient in a long, flexible shape. Illumination light supplied by a light source device is emitted from the front end of the insertion part, and the reflected light from the illumination light is captured by a camera at the front end of the insertion part to take an image of the body.

[0003] The published patent: Invention title, Image sensor data transmission device and 3D endoscope for a 3D endoscope, publication number: CN 215383848 U, application publication date 2022.01.04. The device includes: a first image sensor module 102: converting optical signals into a first electrical signal; a second image sensor module 103: converting optical signals into a second electrical signal; an image sensor data transmission device 104 for receiving the first and second electrical signals, and outputting first image data corresponding to the first electrical signal to a data processing system, and outputting second image data corresponding to the second electrical signal to the data processing system; a data processing system 105 for receiving the first and second image data, synthesizing the first and second image data, and outputting synthesized image data for 3D display; a data interface circuit 2015 connected to a parallel-to-serial converter circuit for transmitting data to the back end. The unknown aspects of the aforementioned disclosed patent technology are: the image processing is not simultaneous, but rather the first image and the second image are obtained sequentially; this system can only be used in endoscopic imaging systems. Published Patent: Invention Title: A 3D Fluorescence Endoscope, Imaging Method, Device and Debugging Method, Publication No.: CN117398043A, Application Publication Date: 2024.01.16. This paper discloses a 3D fluorescence endoscope, imaging method, device, and debugging method, belonging to the field of endoscopy. The endoscope includes an endoscope sleeve, an objective lens disposed within the endoscope sleeve, and a photosensitive element. A beam splitter is disposed between the objective lens and the photosensitive element, splitting the light beam passing through the objective lens into a left visible beam, a left fluorescence beam, a right visible beam, and a right fluorescence beam that are directed to the photosensitive element. A left focusing mirror aligns the optical path lengths of the left visible beam and the left fluorescence beam, and a right focusing mirror aligns the optical path lengths of the right visible beam and the right fluorescence beam, are disposed between the beam splitter and the photosensitive element. This endoscope allows four beams to be imaged simultaneously onto the photosensitive element, with no time difference between the left and right images, and no time difference between the visible light image and the fluorescence image. The entire endoscope uses only one photosensitive element, achieving consistency in time and focal plane within a small space, which is beneficial for miniaturization and high-sensitivity display of the 3D fluorescence endoscope. The unknown aspect of the aforementioned published patent technology is that it has a total of 4 photosensitive elements. The image obtained on the photosensitive elements after two reflections is a mirror image of the object, and the direction is consistent with the light that passes directly through the dichroic mirror 21, which facilitates image processing during imaging. This system can only be used in imaging endoscope systems. It does not involve image optimization and only processes image signals.

[0004] And existing laparoscopic techniques: One approach is the FPGA (Field-Programmable Gate Array) solution, characterized by high parallelism, low latency, and hardware reconfigurability. Data is processed at the camera end, with ISP image processing implemented using an FPGA chip. The drawback is that the image processing algorithm must be programmed onto the FPGA motherboard; any changes after programming require reprogramming the chip. Applications include high real-time tasks and multimodal imaging fusion; it is currently a primary solution for 4K, 3D, and fluorescence imaging.

[0005] Another option is the SOC (System-on-a-Chip) solution, characterized by hardware and software collaboration and system integration. Some of these solutions lack ISP functionality, while others have ISP functionality embedded in the chip. The drawback is the inability to customize the underlying logic, which limits flexibility, but they offer high system integration.

[0006] The research and development of a 4K laparoscopic imaging device employs a GPU solution. Data goes directly to the GPU, eliminating the need for processing at the camera end; the GPU acquires the raw image data. The GPU then performs ISP image processing, and all image data can be embedded with AI algorithms. Simultaneously, the image algorithms can be updated in real time without requiring re-burning. Optimizing and improving image quality and accuracy is therefore essential. Utility Model Content

[0007] To overcome the shortcomings of existing medical endoscopic imaging technology, a 4K laparoscopic imaging device was designed.

[0008] A 4K laparoscopic imaging device includes an endoscope cannula, a cold light source, an insufflator, a photosensitive element, a camera front end, a camera host, and a rear end device. The cold light source includes: a cold light source touch screen, a cold light source module, a cold light source motherboard, a cold light source power supply, and a beam guide; the cold light source motherboard is connected to the cold light source touch screen, the cold light source module, and the cold light source power supply respectively; the beam guide is connected to the cold light source host. The pneumoperitoneum machine includes: an air source management module, a flow control module, a pressure monitoring module, a pneumoperitoneum machine motherboard, a safety protection module, a power supply module, and an exhaust system; the pneumoperitoneum machine motherboard is connected to the air source management module, the flow control module, the pressure monitoring module, the safety protection module, the power supply module, and the exhaust system respectively; The endoscope cannula integrates an optical lens imaging section and an optical fiber light transmission section; one end of the beam guide is connected to the cold light source output port, and the other end of the beam guide is located at the front end of the endoscope cannula; the inflation port of the insufflator is located at the front end of the matching instrument of the endoscope cannula. The camera front end includes a camera, which includes: an optical hard lens, an optical bayonet, a filter, a photosensitive element, a gyroscope, a keypad, a camera motherboard, a serial board, and a camera cable; The gyroscope is connected to the keypad; the keypad is connected to the camera motherboard. The light filter is located at the front end of the photosensitive element; the gyroscope is built into the camera button panel. The filter removes interfering colors and transmits the filtered image to the photosensitive element. The photosensitive element transmits image data to the input interface of the camera host through the camera cable, and the gyroscope also transmits status information to the camera host. The camera host integrates the gyroscope information and processes the image. The camera host includes: a host motherboard, a video output board, a core board, a hard disk, a deserialization board, a touch screen, a host power supply, a fan, a video expansion board, a network port, a USB port, an RS232 port, a signal output port, a display, a signal connection cable, and a signal input interface; The camera connection cable mentioned refers to the GMS L3 data cable; The photosensitive element is used to capture images obtained by the camera; The host motherboard includes a core board; the core board includes a fusion algorithm module, which includes an acquisition module, a DPC module, a BLC module, a WB module, a Demosaic module, a Gamma correct module, a CCM module, a Contrast / Brightness Enhancement module, an Edge Enhancement module, an output module, an AE Stat module, an AE Control module, a noise reduction algorithm module, and a total latency algorithm module; the motherboard is connected to the touch screen, host power supply, fan, video adapter board, signal output interface, or other host interfaces. The output module includes a video output board, a video adapter board, and a signal output terminal; the signal output terminal includes a signal output port, a network port, a USB port, and an RS232 port. The mainboard is connected to the main touchscreen, video adapter board, and signal output terminal respectively; the back-end device includes: a display or a remote receiving device. The hardware connections of the 4K laparoscopic imaging device are as follows: the lens of the optical rigid mirror acquires image information of the target area; the optical rigid mirror is connected to the optical bayonet adapter to optically transmit the acquired image information to the filter; the photosensitive element is connected to the camera motherboard; the gyroscope is connected to the keypad; the keypad is connected to the camera motherboard; the camera motherboard is connected to the serial board; the serial board is connected to the deserialization board via the camera cable; the deserialization board is connected to the core board; the core board is also connected to the hard disk and the video output board; the video output board is connected to the video expansion board; the video expansion board is connected to the signal output port; and the signal input interface is connected to the display. The image data transmission relationship of the 4K laparoscopic imaging device is as follows: the camera converts the acquired optical signals into electrical signals through the photosensitive element and transmits them to the camera mainboard; the gyroscope acquires the status information of the photosensitive element and outputs it to the camera mainboard; the serial board converts the data from the camera mainboard into serial data and transmits it at high speed to the deserialization board through the camera cable; the deserialization board converts the serial data into parallel data and inputs it to the camera host; the fusion algorithm module of the camera host core board reads the number and pixels of the connected cameras; and matches the built-in image processing algorithm module, through the exposure algorithm module and the noise reduction algorithm module, to enhance the image processing. The comparison algorithm module performs preprocessing to obtain single or multiple images, designated as State 1. It extracts the image features of State 1, automatically selects either the single-image algorithm module or the multi-image fusion algorithm module, and obtains State 2 through the fusion algorithm module. The State 2 images are then assigned and identified as single images. After processing, the spectrally filtered image and the normal image are output separately. The core board connects to the image ISP processing module, which in turn connects to the host motherboard. The host motherboard outputs image data to the signal output port, which outputs the data to the display. The display shows the optimized image, or it can be transmitted to a remote device via wired or wireless network through the signal output port.

[0009] The filter is used to filter out stray light, allowing only 400-650nm light to enter the photosensitive element.

[0010] The photosensitive element can be any one of CMOS, CCD, or infrared sensor chips.

[0011] The host computer features a touchscreen or push-button switch.

[0012] The total delay algorithm module described above ensures that the delay time for image data from the front-end device to the back-end device is within 50-100ms.

[0013] The steps for using the 4K laparoscopic imaging device and image optimization method are as follows: (1) Check that the endoscope cannula, cold light source, insufflator, photosensitive element, camera front end, camera host, and back end device are connected correctly; and confirm that the camera host is turned on; (2) The camera host is connected to the 4K monitor, and the 4K monitor is turned on; (3) The camera is connected to the camera host; (4) The camera has been fitted with a medical endoscope; (5) And confirm that the camera host is turned on.

[0014] The image processing steps of the 4K laparoscopic imaging device are as follows: Step 1: Place the filter in front of the photosensitive element to filter stray light and prevent image interference; Step 2: In order to ensure the integrity and high resolution of image information, after the image is acquired by the photosensitive element, the parallel data will be processed serially through the serial board to achieve high-speed transmission. Step 3: Using GMSL3 transmission mode, a transmission rate of 6Gbps is obtained. After the image is sent to the deserialization board, the serial signal is converted into a parallel signal; and the parallel signal is transmitted to the core board. During this process, the gyroscope transmits the position information of the photosensitive element to the core board in real time to correct the image; Step 4: The core board's fusion algorithm module automatically identifies the number and pixels of the connected cameras, automatically matches the built-in image processing algorithm module, and performs preprocessing, color restoration, image fusion, etc., through the exposure algorithm module, noise reduction algorithm module, total delay algorithm module, and contrast enhancement algorithm module to obtain single or multiple images, which are designated as state 1; The automatic identification of the number and pixels of cameras is achieved by identifying the connected sensors through the sensor driver and obtaining the corresponding resolution based on the identified sensors; Step 5: Extract the image features of state 1, automatically select the single-image algorithm module or the multi-image fusion algorithm module, and obtain state 2 through the fusion algorithm module; Step 6: Assign the State 2 image to either a single image or multiple images, and output the spectrally filtered image and the normal image respectively after processing; Step 7: The image ISP processing module continues to process single or multiple images; Step 8: The core board transmits the processed image signal to the signal output port and outputs the processed video signal to the monitor to display the camera image in real time; Step 9: Based on the instructions issued by the serial port control, the video signal processed by the core board can be stored on the hard drive or transmitted via the network port.

[0015] The low-latency implementation process is as follows: GPU-accelerated deployment: Porting image processing algorithms to GPUs and optimizing memory access patterns.

[0016] Verify performance improvements to ensure single-frame processing time is ≤5ms.

[0017] EDF scheduling integration: Configure the EDF scheduler in a real-time operating system (Linux).

[0018] Define task parameters (C i T i And test the scheduling feasibility.

[0019] Joint debugging: Monitor the latency between the front-end and back-end devices and adjust the GPU resource reservation ratio.

[0020] Handle extreme situations (such as sudden high loads) to ensure system robustness.

[0021] Clinical validation: Test the impact of latency on operation (such as doctor's control feedback time) in a simulated environment.

[0022] Target: The latency from the front-end device to the back-end device is ≤100ms.

[0023] Definitions and explanations of terms in this patent: This patent is the result of continuous improvement and innovation of the applicant's previous patent application "A Medical Image Optimization Device", patent application number: 202510278642.6, and is a 4K laparoscopic imaging device and an endoscopic image optimization method.

[0024] A pneumoperitoneum machine is a well-known specialized device used in laparoscopic surgery to establish and maintain pneumoperitoneum. Its working principle involves mechanically pressurizing and inflating the abdominal cavity with medical-grade CO2 gas, separating the abdominal wall from the organs, thus creating a surgical operating space and preventing organ damage caused by trocar insertion. The system includes: a gas source management module with a gas source interface (connecting to a carbon dioxide (CO2) cylinder or a central gas supply system to ensure gas input); a flow control module with a flow sensor (monitoring gas flow rate in real time, typically divided into high flow (initial inflation phase) and low flow (maintenance phase); a pressure regulator (reducing the pressure of the high-pressure gas source (e.g., cylinder) to a safe range suitable for use in the abdominal cavity (typically 30-50 psi); a gas filter (filtering impurities or microorganisms from the gas to ensure sterility); and a pressure monitoring module with a pressure sensor (real-time monitoring of intra-abdominal pressure, typically set at 12-15 mmHg) to prevent excessively high pressure (leading to complications) or excessively low pressure (affecting the surgical field of view). Pressure feedback system: Feeds monitoring data back to the control module, automatically adjusting inflation or deflation. Alarm system: Triggers audible and visual alarms and suspends gas supply in case of abnormal pressure (e.g., leakage, overpressure). Insufflator mainboard, microprocessor: Core control chip that processes sensor data and adjusts flow and pressure. User interface: Touchscreen or button panel for medical staff to set target pressure, flow, and other parameters. Safety protection module, overpressure protection valve: Mechanical or electronic redundancy design to cut off the gas supply or release excess gas in case of system failure. Gas leak detection: Detects leaks by abnormal changes in flow and pressure, triggering an alarm. Temperature control: Some devices are equipped with gas heating to prevent cold gas from entering the abdominal cavity and causing patient discomfort. Power module, main power adapter: Provides the power required for device operation. Exhaust system, exhaust valve: Quickly removes gas from the abdominal cavity at the end of surgery, usually controlled by a solenoid valve.

[0025] Rigid optical endoscope (RIO): Also known as a lens, one type of lens used in endoscopes is the rigid optical endoscope. It is characterized by optical components made of cylindrical glass, with a metal outer tube that is inflexible. It mainly consists of three parts: a mechanical system, an optical system, and a light-guiding system.

[0026] Gyroscope: bmi088, clearly indicates the position information of the photosensitive element.

[0027] GMSL3: High-speed data transmission reaches 6Gbps.

[0028] MIPI stands for Mobile Industry Processor Interface. Developed by the MIPI Alliance, it is a high-performance, low-power, and low-cost serial communication interface. Its purpose is to standardize internal device interfaces such as camera, display, and RF / baseband interfaces, thereby reducing the complexity of device design and increasing design flexibility.

[0029] Image sensor: Used to acquire images, with a resolution of 4K pixels.

[0030] Filters: Used to filter stray light and ensure that natural light of 450-650nm enters the photosensitive element.

[0031] The serialization board uses the MAX96789 chip. The deserialization board uses the MAX96752 chip.

[0032] 4K medical endoscope: A imaging system that uses sensors to collect image signals and outputs them in real time to a 4K display for medical staff to view during surgery.

[0033] Sensor input: The isp pipe for inputting images acquired by the sensor.

[0034] DPC (Dead Pixel Correction): Image dead pixel detection: Detects dead pixels in the sensor and corrects them. Dead pixels are white dots in the output image under complete darkness and black dots in the output image under bright light.

[0035] BLC (Black Level Compensation): From the perspective of sensor characteristics, the lowest output voltage of the sensor is the black level voltage. By calibrating the black level, the influence of the black level on the image can be eliminated.

[0036] WB (White Balance): White balance corrects color deviations in the sensor at different color temperatures. It calculates the gain values ​​of the RGB three channels using white cardstock to complete white balance correction.

[0037] Demosaic: Removes mosaic effects from images captured by a single CMOS sensor that contain only one color in the RGB spectrum. It restores the missing colors in the image through interpolation.

[0038] Gamma Correction, also known as gamma correction or gamma nonlinearity adjustment, is a nonlinear operation or inverse operation technique used to adjust image or video signals. It is used to encode and decode linear brightness or RGB values ​​to match the nonlinear characteristics of display devices. Furthermore, gamma correction can expand or compress the dynamic range of an image.

[0039] CCM (Color Correction Matrix): Due to the non-ideal nature of the sensor's spectral response and the different spectral distribution of the ambient light source, there will be a large color difference between the sensor image and the actual scene. By calculating the color correction matrix, the image color can be adjusted to make the image color closer to the actual color.

[0040] Contrast / Brightness Enhancement: By enhancing image contrast and brightness, it makes the brightness distribution of images under non-uniform lighting more uniform and enhances the image's transparency.

[0041] Edge Enhancement: This feature uses edge detection technology to extract image edges and enhance them, thereby improving image sharpness.

[0042] Output: Convert RGB image format to YUV420 output.

[0043] AE Stat: Automatic Exposure Information Statistics: Statistics on image brightness, variance, histogram, etc., used to assess whether the current image is underexposed or overexposed.

[0044] AE Control: Evaluates the current exposure based on exposure statistics, calculates the exposure parameters for the next frame, and transmits the exposure parameters of the next frame back to the sensor to complete automatic exposure control.

[0045] Contrast enhancement refers to adjusting the contrast of an image to make its details clearer and enhance its visual appeal. Contrast refers to the degree of difference between the brightest and darkest parts of an image; by increasing this difference, the details of the image can be made more prominent.

[0046] Brightness enhancement adjusts the brightness level of an image, making it brighter or darker. Brightness refers to the average light intensity of an image; adjusting the brightness changes the lightness or darkness of the image, thus affecting the visual effect.

[0047] Automatic identification of camera quantity and pixel count is achieved by using a sensor driver to identify connected sensors and obtaining the corresponding resolution based on the identified sensors.

[0048] CCD: Charge Coupled Device, is a semiconductor device used for image acquisition.

[0049] CMOS stands for Complementary Metal Oxide Semiconductor; it is an integration technology that fabricates transistors, resistors, capacitors, and diodes on the same silicon wafer using standard processes. CMOS chips have advantages such as low power consumption, high integration density, and strong anti-interference capabilities, and are widely used in microprocessors, digital signal processors, memory, and image sensors.

[0050] GMSL3: is the third generation of Gigabit Multimedia Serial Link technology; high data transmission rate: GMSL3 supports data transmission rates up to 12 Gbps, which can meet the bandwidth requirements of high-definition cameras and other high-speed data transmission devices; low latency: enables low-latency video data transmission, ensuring the real-time performance of the system.

[0051] EDF (Earliest Deadline First) real-time task management in intelligent scheduling is a dynamic priority scheduling algorithm widely used in scenarios that require strict adherence to task deadlines. Through dynamic priority allocation and data-driven decision-making mechanisms, EDF real-time task management has become one of the core technologies of intelligent scheduling.

[0052] Core board: A custom NVIDIA AGX Orin 64G is used as the core board to process the image information received by the camera.

[0053] Beam Guide: In a camera, the beam guide is a component used to transmit light. It primarily consists of a bundle of optical fibers and efficiently transmits light emitted from the light source to the object being measured. The beam guide plays a crucial role in the imaging process. It ensures that light is projected onto the object's surface along a predetermined path, forming specific light spots or streaks on the surface.

[0054] Hardware specifications Table 1 Camera Host

[0055] Table 2 Technical Specifications of Cold Light Source The applicant has conducted testing, as detailed in the "4K Medical Endoscopic Camera System Test Report".

[0056] "in conclusion

[0057] (1) The noise reduction performance meets the image quality requirements.

[0058] (2) The system latency (98.8ms) meets the requirements for real-time surgical interaction (≤100ms). Special note: The applicant requires system latency to be within ≤100ms, while the industry standard is typically only ≤150ms.

[0059] The significant advancements and innovative technical features of this 4K laparoscopic imaging device are: The technical approach adopted is a 4K endoscope camera solution. The process involves: CMOS converting the acquired image into a digital signal and transmitting the parallel signal to a serial board; the gyroscope acquiring the CMOS's status information and outputting it to the serial board's signal output port; the serial board compiles the parallel signal into a serial signal and transmits it at high speed to the deserialization board, achieving high-speed transmission over tens of meters; simultaneously, the gyroscope also transmits its status information at high speed to the backend. The host computer integrates the gyroscope information and processes the image. Because the image information is completely preserved throughout the entire image transmission, higher quality images can be obtained. This primarily overcomes the image information loss problem caused by image processing at the camera module level, and also addresses issues such as increased module temperature, component damage, and reduced image quality that can result from image processing at the camera module level. The technical objective is to achieve low-latency, high-resolution transmission while ensuring complete preservation of image information. A powerful backend host can then better process the image, guaranteeing the final image quality. This patent's data goes directly to the GPU; the camera itself doesn't process it. The GPU acquires the raw image data, and then performs ISP image processing. All image data can be embedded with AI algorithms, which can be updated in real time without needing to be re-encoded. This backend processing method preserves the image information. Other patents perform image processing at the camera's front end, which may result in the loss of image information.

[0060] The achieved technical effects include: image data transmission to a display screen for real-time viewing by medical staff; simultaneous processing of the image data on a GPU chip processor; and overlaying the processed data onto the optimized image data before real-time display; the optimized image data can also be copied to external storage devices, such as a USB flash drive for backup, or transmitted remotely over a network. Attached Figure Description

[0061] Figure 1This is a schematic diagram of the structure of this utility model.

[0062] Figure 2 This is a schematic diagram of the data flow of this utility model.

[0063] Figure 3 This is a schematic diagram of the module structure in this utility model.

[0064] Figure 4 This is a schematic diagram of the module flowchart in this utility model.

[0065] Figure 5 This is a flowchart of the processing of image state 1 to image state 2 in this utility model.

[0066] Figure 6 This is a flowchart of the low-latency processing in this utility model.

[0067] Figure 7 This is a flowchart of the noise reduction process in this utility model.

[0068] In the diagram: Cold light source 4-1, Cold light source touchscreen 4-1-1, Cold light source module 4-1-2, Cold light source motherboard 4-1-3, Cold light source power supply 4-1-4, Beam guide 4-1-5, Inflator 4-2, Air source management module 4-2-1, Flow control module 4-2-2, Pressure monitoring module 4-2-3, Inflator motherboard 4-2-4, Safety protection module 4-2-5, Power supply module 4-2-6, Exhaust system 4-2-7, 4K camera system 1, Optical hard lens 1-1, Camera 1-2, Optical bayonet 1-2-1, Filter 1-2-2, Photosensitive element 1-2-3, Gyroscope 1- 2-4, Button board 1-2-5, Camera motherboard 1-2-6, Serial board 1-2-7, Camera cable 1-3, Camera host 1-4, Host motherboard 1-4-1, Video output board 1-4-1-1, Core board 1-4-1-2, Hard drive 1-4-1-3, Deserialization board 1-4-1-4, Host touch screen 1-4-2, Host power supply 1-4-3, Video expansion board 1-4-4, Network port 1-4-5, USB port 1-4-6, RS232 port 1-4-7, Signal output port 1-4-8, Monitor 1-5, Signal connection cable 1-5-1, Signal input interface 1-5-2. Detailed Implementation

[0069] The technical solutions of the present utility model will be clearly and completely described below with reference to the accompanying drawings of the embodiments. Obviously, the described embodiments are only some embodiments of the present utility model, and not all embodiments. Based on the embodiments of the present utility model, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the protection scope of the present utility model.

[0070] Example 1

[0071] A 4K laparoscopic imaging device includes an endoscope cannula, a cold light source 4-1, an insulated abdomen 4-2, a photosensitive element 1-2-3, a camera front end, a camera host, and a rear end device. The cold light source 4-1 includes: a cold light source touch screen 4-1-1, a cold light source module 4-1-2, a cold light source motherboard 4-1-3, a cold light source power supply 4-1-4, and a beam guide 4-1-5; the cold light source motherboard 4-1-3 is connected to the cold light source touch screen 4-1-1, the cold light source module 4-1-2, and the cold light source power supply 4-1-4 respectively, and the beam guide 4-1-5 is connected to the cold light source 4-1; The pneumoperitoneum machine 4-2 includes: an air source management module 4-2-1, a flow control module 4-2-2, a pressure monitoring module 4-2-3, a pneumoperitoneum machine main board 4-2-4, a safety protection module 4-2-5, a power supply module 4-2-6, and an exhaust system 4-2-7. The pneumoperitoneum machine main board is connected to the air source management module 4-2-1, the flow control module 4-2-2, the pressure monitoring module 4-2-3, the safety protection module 4-2-5, the power supply module 4-2-6, and the exhaust system 4-2-7, respectively. The endoscope cannula integrates an optical lens imaging section and an optical fiber light transmission section; one end of the beam guide 4-1-5 is connected to the cold light source output port, and the other end of the beam guide 4-1-5 is located at the front end of the endoscope cannula; the inflation port of the insufflator 4-2 is located at the front end of the matching instrument of the endoscope cannula. The camera front end includes: an optical hard lens 1-1, a camera 1-2, an optical bayonet 1-2-1, a filter 1-2-2, a photosensitive element 1-2-3, a gyroscope 1-2-4, a keypad 1-2-5, a camera motherboard 1-2-6, a serial board 1-2-7, and a camera cable 1-3; The gyroscope 1-2-4 is connected to the button board 1-2-5; the button board 1-2-5 is connected to the camera motherboard 1-2-6. The filter 1-2-2 is disposed at the front end of the photosensitive element 1-2-3; the gyroscope 1-2-4 is mounted on the built-in keypad 1-2-6; The filter 1-2-2 filters out interfering noise and transmits the filtered image to the photosensitive element 1-2-3; The photosensitive element 1-2-3 transmits image data to the input interface of the camera host 1-4 through the camera cable 1-3. The gyroscope 1-2-4 also transmits status information to the camera host 1-4. The camera host 1-4 integrates the information from the gyroscope 1-2-4 and processes the image. The camera host 1-4 includes: host motherboard 1-4-1, video output board 1-4-1-1, core board 1-4-1-2, hard disk 1-4-1-3, deserialization board 1-4-1-4, host touch screen 1-4-2, host power supply 1-4-3, fan, video expansion board 1-4-4, network port 1-4-5, USB port 1-4-6, RS232 port 1-4-7, signal output port 1-4-8, display 1-5, signal connection cable 1-5-1, and signal input interface 1-5-2; The camera connection cables 1-3 mentioned above refer to the GMSL3 data cables; The photosensitive elements 1-2-3 are used to capture images obtained by the camera 1-2; The host motherboard 1-4-1 includes: a core board 1-4-1-2; the core board 1-4-1-2 includes a fusion algorithm module, which includes an acquisition module, a DPC module, a BLC module, a WB module, a Demosaic module, a Gammacorrect module, a CCM module, a Contrast / Brightness Enhancement module, an Edge Enhancement module, an output module, an AE Stat module, an AE Control module, a noise reduction algorithm module, and a total delay algorithm module; the host motherboard 1-4-1 is connected to the touch screen 1-4-2, the host power supply 1-4-3, a fan, a video adapter board 1-4-4, a signal output interface 1-5-2, or other host interfaces. The output module includes a video output board 1-4-1-1, a video adapter board 1-4-4, and a signal output terminal; the signal output terminal includes a signal output port 1-4-8, a network port 1-4-51-4-6, a USB port, and an RS232 port 1-4-7. The back-end device includes: displays 1-5, or a remote receiving device; The hardware connections of the 4K laparoscopic imaging device are as follows: the lens of the optical rigid lens 1 / 1 acquires image information of the target area; the optical rigid lens 1 / 1 is adapted and connected to the optical bayonet 1-2-1 to optically transmit the acquired image information to the filter 1-2-2; the photosensitive element 1-2-3 is connected to the camera motherboard 1-2-6; the gyroscope 1-2-4 is connected to the camera motherboard 1-2-6; the keypad 1-2-5 is connected to the camera motherboard 1-2-6; and the camera motherboard 1-2-6 is connected to the serial board. 1-2-7 connection; serial board 1-2-7 is connected to deserialization board 1-4-1-4 via camera cable 1-3, deserialization board 1-4-1-4 is connected to core board 1-4-1-2, core board 1-4-1-2 is also connected to hard disk 1-4-1-3 and video output board 1-4-1-1; video output board 1-4-1-1 is connected to video expansion board 1-4-4, video expansion board 1-4-4 is connected to the back-end device via wired or wireless network, and monitor 1-5 in the back-end device displays the optimized medical images; The image data transmission relationship of the 4K laparoscopic imaging device is as follows: the camera 1-2 converts the collected optical signals into electrical signals through the photosensitive element 1-2-3 and transmits them to the camera mainboard 1-2-6; the gyroscope 1-2-4 collects the status information of the photosensitive element 1-2-3 and outputs it to the camera mainboard 1-2-6; the serial board 1-2-7 converts the data of the camera mainboard into serial data and transmits it at high speed to the deserialization board 1-4-1-4 through the camera cable 1-3; the deserialization board 1-4-1-4 converts the serial data into parallel data and inputs it to the camera host 1-4. The camera converts the captured image information into digital signals. The camera motherboard 1-2-6 transmits the parallel signals to the serial board 1-2-7. The gyroscope 1-2-4 collects the status information of the photosensitive element 1-2-3 and outputs it to the signal input port in the serial board 1-2-7. The serial board compiles the parallel signals into serial signals and transmits them at high speed to the deserialization board 1-4-1-4. At the same time, the gyroscope 1-2-4 also transmits the status information to the input interface of the camera host 1-4, and the camera cable 1-3 transmits image data to the input interface of the camera host 1-4. The camera host 1-4 integrates the information from the gyroscope 1-2-4 and processes the image. The fusion algorithm module set on the core board 1-4-1-2 of the camera host 1-4 reads the number and pixels of the connected cameras 1-2, automatically matches the built-in image processing algorithm module, and processes the image through the exposure algorithm module, noise reduction algorithm module, and contrast enhancement algorithm module. Preprocessing is performed to obtain single or multiple images, designated as State 1. Image features of State 1 are extracted, and either a single-image algorithm module or a multi-image fusion algorithm module is automatically selected. State 2 is obtained through the fusion algorithm module. The State 2 images are assigned and identified as single images. After processing, spectrally filtered images and normal images are output separately. The camera host core board 1-4-1-2 is connected to the image ISP processing module. The ISP processing module is connected to the host motherboard 1-4-1. The host motherboard 1-4-1 is connected to the video output board 1-4-1-1. The video output board 1-4-1-1 is connected to the video expansion board 1-4-4. The video expansion board 1-4-4 is connected to the host signal output port 1-4-8. The host signal output port 1-4-8 is connected to the display 1-5, or transmitted to a remote device via wired or wireless network through the signal output interface. The display 1-5 in the back-end device displays the optimized image. The lens of the optical hard lens 1 / 1 acquires image information of the target area. The optical hard lens 1 / 1 is connected to the optical mount 1-2-1 to optically transmit the acquired image information to the filter 1-2-2. The photosensitive element 1-2-3 is connected to the camera motherboard 1-2-6; the gyroscope 1-2-4 is connected to the camera motherboard 1-2-6; the button board 1-2-5 is connected to the camera motherboard 1-2-6; the camera motherboard 1-2-6 is connected to the serial board 1-2-7; the serial board 1... -2-7 is connected to the deserialization board 1-4-1-4 via camera connection cable 1-3. The deserialization board 1-4-1-4 is connected to the core board 1-4-1-2. The core board 1-4-1-2 is also connected to the hard drive 1-4-1-3 and the video output board 1-4-1-1. The video output board 1-4-1-1 is connected to the video adapter board 1-4-4. The video adapter board 1-4-4 is connected to the back-end device via wired or wireless network. The monitor 1-5 in the back-end device displays the optimized medical images. The image data transmission relationship of the 4K laparoscopic imaging device is as follows: the camera converts the acquired image information into digital signals; the camera motherboard 1-2-6 transmits the parallel signals to the serial board 1-2-7; the gyroscope 1-2-4 acquires the status information of the photosensitive element 1-2-3 and outputs it to the signal input port in the serial board 1-2-7; the serial board compiles the parallel signals into serial signals and transmits them at high speed to the deserialization board 1-4-1-4; simultaneously, the gyroscope 1-2-4 also transmits the status information to the input interface of the camera host 1-4; the camera connection cable 1-3 transmits image data to the input interface of the camera host 1-4; the camera host 1-4 integrates the information from the gyroscope 1-2-4 and processes the image; the fusion algorithm module set on the core board 1-4-1-2 of the camera host 1-4 automatically identifies the number and pixels of the connected cameras 1-2, automatically matches the built-in image processing algorithm module, and through the exposure algorithm module and noise reduction algorithm module... The system preprocesses the image using the total delay algorithm module and the contrast enhancement algorithm module to obtain one or more images, designated as State 1. It then extracts the image features of State 1 and automatically selects either the single-image algorithm module or the multi-image fusion algorithm module to obtain State 2. The State 2 image is then assigned and identified as a single image. After processing, the spectrally filtered image and the normal image are output separately. The camera host core board 1-4-1-2 is connected to the image ISP processing module, which in turn is connected to the host motherboard 1-4-1. The host motherboard 1-4-1 is connected to the video output board 1-4-1-1, which is connected to the video adapter board 1-4-4. The video adapter board 1-4-4 is connected to the signal output port 1-4-8, which is connected to the display 1-5. Alternatively, the image can be transmitted to a remote device via wired or wireless network through the signal output interface. The display 1-5 in the backend device displays the optimized image.

[0072] The cameras 1-2 described herein acquire data in a single channel.

[0073] The filter 1-2-2 is used to filter stray light, allowing only 400-650nm light to enter the photosensitive element 1-2-3.

[0074] The photosensitive element 1-2-3 is a CMOS.

[0075] The endoscope mentioned is an endoscope for the digestive tract.

[0076] The cameras 1-2 are connected to the endoscope adapter.

[0077] The image information includes raw medical imaging data from medical endoscopes.

[0078] The cameras 1-2 mentioned above refer to those that read raw medical image data from one channel with a resolution of 4K and a frame rate of 60 frames.

[0079] The aforementioned host touchscreen 1-4-2 is a touchscreen switch.

[0080] The total delay algorithm module described above ensures that the delay time for image data from the front-end device to the back-end device is within 50-100ms.

[0081] Example 2

[0082] The aforementioned host touchscreen 1-4-2 is a push-button switch.

[0083] The rest is the same as above.

[0084] The specific embodiments of the present invention have been described in detail above with reference to the accompanying drawings. However, the present invention is not limited to the above embodiments. Within the scope of knowledge possessed by those skilled in the art, various changes can be made without departing from the spirit of the present invention.

Claims

1. A 4K laparoscope imaging device, characterized in that: Including the endoscope cannula and cold light source, Insufflator, photosensitive element, camera front end, camera main unit, and back end device; The cold light source includes: a cold light source touch screen, a cold light source module, a cold light source motherboard, a cold light source power supply, and a beam guide; the cold light source motherboard is connected to the cold light source touch screen, the cold light source module, and the cold light source power supply respectively; the beam guide is connected to the cold light source host. The pneumoperitoneum machine includes: an air source management module, a flow control module, a pressure monitoring module, a pneumoperitoneum machine motherboard, a safety protection module, a power supply module, and an exhaust system; the pneumoperitoneum machine motherboard is connected to the air source management module, the flow control module, the pressure monitoring module, the safety protection module, the power supply module, and the exhaust system respectively; The endoscope cannula integrates an optical lens imaging section and an optical fiber light transmission section; one end of the beam guide is connected to the cold light source output port, and the other end of the beam guide is located at the front end of the endoscope cannula; the inflation port of the insufflator is located at the front end of the matching instrument of the endoscope cannula. The camera front end includes a camera, which includes: an optical hard lens, an optical bayonet, a filter, a photosensitive element, a gyroscope, a keypad, a camera motherboard, a serial board, and a camera cable; The gyroscope is connected to the keypad; the keypad is connected to the camera motherboard. The light filter is located at the front end of the photosensitive element; the gyroscope is built into the camera button panel. The filter removes interfering colors and transmits the filtered image to the photosensitive element. The photosensitive element transmits image data to the input interface of the camera host through the camera cable, and the gyroscope also transmits status information to the camera host. The camera host integrates the gyroscope information and processes the image. The camera host includes: a host motherboard, a video output board, a core board, a hard disk, a deserialization board, a touch screen, a host power supply, a fan, a video expansion board, a network port, a USB port, an RS232 port, a signal output port, a display, a signal connection cable, and a signal input interface; The camera connection cable mentioned refers to the GMSL3 data cable; The photosensitive element is used to capture images obtained by the camera; The core board includes a fusion algorithm module, which comprises an acquisition module, a DPC module, a BLC module, a WB module, a Demosaic module, a Gamma correct module, a CCM module, a Contrast / BrightnessEnhancement module, an Edge Enhancement module, an output module, an AE Stat module, an AE Control module, a noise reduction algorithm module, and a total delay algorithm module. The host motherboard is connected to the touchscreen, host power supply, fan, video adapter board, signal output port, or other host interfaces. The output module includes a video output board, a video adapter board, and a signal output terminal; The motherboard is connected to the host touchscreen, video adapter board, and signal output terminal respectively; the signal output terminal includes a signal output port, a network port, a USB port, and an RS232 port. The back-end device includes: a display, or a remote device; The hardware connections of the 4K laparoscopic imaging device are as follows: the lens of the optical rigid mirror acquires image information of the target area; the optical rigid mirror is connected to the optical bayonet adapter to optically transmit the acquired image information to the filter; the photosensitive element is connected to the camera motherboard; the gyroscope is connected to the keypad; the keypad is connected to the camera motherboard; the camera motherboard is connected to the serial board; the serial board is connected to the deserialization board via the camera cable; the deserialization board is connected to the core board; the core board is also connected to the hard disk and the video output board; the video output board is connected to the video expansion board; the video expansion board is connected to the signal output port; and the signal input interface is connected to the display. The image data transmission relationship of the 4K laparoscopic imaging device is as follows: the camera converts the acquired optical signals into electrical signals through the photosensitive element and transmits them to the camera mainboard; the gyroscope acquires the status information of the photosensitive element and outputs it to the camera mainboard; the serial board converts the data from the camera mainboard into serial data and transmits it at high speed to the deserialization board through the camera cable; the deserialization board converts the serial data into parallel data and inputs it to the camera host; the fusion algorithm module of the camera host core board reads the number and pixels of the connected cameras; and matches the built-in image processing algorithm module, through the exposure algorithm module and the noise reduction algorithm module, to enhance the image processing. The comparison algorithm module performs preprocessing to obtain single or multiple images, designated as State 1. It extracts the image features of State 1, automatically selects either the single-image algorithm module or the multi-image fusion algorithm module, and obtains State 2 through the fusion algorithm module. The State 2 images are then assigned and identified as single images. After processing, the spectrally filtered image and the normal image are output separately. The core board connects to the image ISP processing module, which in turn connects to the host motherboard. The host motherboard outputs image data to the signal output port, which outputs the data to the display. The display shows the optimized image, or it can be transmitted to a remote device via wired or wireless network through the signal output port.

2. The 4K laparoscopic imaging device of claim 1, wherein: The host touch The screen is either a touchscreen switch or a button switch.

3. The 4K laparoscopic imaging device of claim 1, wherein: The cold light source display The color index is ≥90; the correlated color temperature of the cold light source is 5200-6200K; the radiant flux ratio of red, green and blue light of the cold light source (based on the green radiant flux Φeg in the wavelength range of 515nm~545nm) is 630nm~660nm, the ratio of red radiant flux Φer to Φeg in the wavelength range should be 0.67, with a tolerance of ±20; the ratio of blue radiant flux Φeb to Φeg in the wavelength range of 435nm~465nm should be 1.3, with a tolerance of ±20%; the infrared cutoff performance of the cold light source should have a radiant flux to luminous flux ratio of no more than 6mW / lm in the wavelength range of 300nm~1700nm.

4. The 4K laparoscopic imaging device as described in claim 1, characterized in that: The technical parameters of the aforementioned camera host are: Signal-to-noise ratio (dB): Nominal value is 50 dB, peak signal-to-noise ratio is 82 dB, tolerance should be -20%, upper limit is not considered; Minimum illuminance (Lux): ≤0.1 Lx; Image sensor ADC bit width: 12 bits; Brightness response characteristics: linear fitting coefficient not less than 0.98; Spatial Frequency Response: When the SFR value of the camera system is 50%, the corresponding nominal spatial frequency value is 48 lp / (°); when the SFR value of the camera system is 30%, the corresponding nominal spatial frequency value is 57 lp / (°); the spatial frequency response tolerance should be -20%, with no upper limit. Still image latitude: The nominal value of still image latitude is 180, the tolerance should be -20%, and the upper limit is not considered; Horizontal resolution: The system horizontal resolution is 2000 lines, with a tolerance of -20% and no upper limit. Field of view: The field of view is 20°, and the tolerance should be within ±10%. Image resolution: 3840×2160; Overall noise level: ≤45dB.

5. The 4K laparoscopic imaging device of claim 1, wherein: The total latency algorithm module has a latency of ≤100ms from the front-end device to the back-end device.

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