CN116228625A - Automatic scanning device and method for face details of patient - Google Patents

Automatic scanning device and method for face details of patient Download PDF

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CN116228625A
CN116228625A CN202211331303.2A CN202211331303A CN116228625A CN 116228625 A CN116228625 A CN 116228625A CN 202211331303 A CN202211331303 A CN 202211331303A CN 116228625 A CN116228625 A CN 116228625A
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face
patient
module
facial
scanning
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何宏
李坤昊
陈家毓
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University of Shanghai for Science and Technology
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Abstract

The invention relates to an automatic scanning device and method for face details of a patient. The facial position calibration module comprises a vertical track, a vertical lifting sliding block and a patient interaction screen, and the self-adaptive adjustment of different body heights and body shapes of patients is realized through a central control module algorithm; the face scanning module comprises a light supplementing lamp, a camera and an arc sliding rail, and is used for shooting the face of the patient at multiple angles during the movement of the camera and scanning the characteristics of the face image; the face imaging module synthesizes the obtained multi-angle images through a 3D face reconstruction algorithm of the central control module after receiving the images, and generates and displays a high-precision and multi-detail digital twin model of the face of the patient; the central control module comprises a core processor and a cooling fan set. The problem of need according to the different self-adaptation positioning patient's of patient's height size facial position to facial feature high accuracy stability catches is solved.

Description

Automatic scanning device and method for face details of patient
Technical Field
The invention relates to the field of medical facial image scanning devices and methods, in particular to an automatic scanning device and method for patient facial details for disease diagnosis and reference.
Background
Medical artificial intelligence is an emerging technological strength to address medical productivity. In China, the problems of ageing population, high-speed growth of slow diseases, serious unbalance of medical resource supply and demand, uneven regional distribution and the like are solved, and great demands on medical artificial intelligence are made; meanwhile, diagnosis of some strong regularity diseases excessively depends on subjective judgment of doctors, so that precious medical resources and time are wasted, and the problem to be solved is also to introduce medical artificial intelligence.
At present, the judgment of facial symptoms of patients in medicine mainly takes clinical diagnosis as main, such as five sense organs related diseases of ears, nose and the like, various facial skin diseases and the like; in the category of Chinese medicine, there is also a way of facial inquiry. These are time and labor consuming tasks that require conclusions to be drawn after the patient's facial details are observed by a physician. However, depending on the physician's manual judgment, there are subjective and occasional misdiagnosis uncertainty factors, which lead to different physicians possibly making different diagnoses of the same disease. In particular, there are often differences and diversity in the performance of different patients with the same disease in medicine. The problems common in these hospitals all require accurate and clear pictures to simply and clearly locate the lesion area; meanwhile, the subjectivity of doctors and the diversity of patients all hope that the technology brought by the introduction of medical artificial intelligence improves the identification accuracy.
The following 4 papers and patents provide implementation method references for the algorithms herein:
the key point detection method of the face of the person comprises the following steps: CN112417947a, entitled "optimization of key point detection model and detection method and device of facial key points", concrete implementation contents in [0047] to [0219], calculates high-precision facial key point coordinates from the input initial facial image.
3D face reconstruction method based on image enhancement technique, feng Y, wu F, shao X, et al Joint3d face reconstruction and dense alignment with position map regression network [ C ]// Proceedings of the European conference on computer vision (ECCV). 2018:534-551.
U-net medical image segmentation, ronneberger O, fischer P, brox T.U-net: convolutional networks for biomedical image segmentation [ C ]// International Conference on Medical image computing and computer-assisted interaction. Springer, cham,2015:234-241.
CNN convolutional neural networks, krizhevsky A, sutskever I, hinton G.E. Imagenet classification with deep convolutional neural networks [ J ]. Communications of the ACM,2017,60 (6): 84-90.
Along with the development of artificial intelligence of medical science in China, some top hospitals have introduced imaging devices with deep learning algorithms for imaging departments of the top hospitals. However, the existing imaging devices for face scanning have the defects of low resolution, limited fineness of face recognition and insufficient feature capture, especially for different manifestations of the same disease, and the defects that the methods can ignore many detail features and cannot accurately judge the features such as tiny focus areas, for example, the device for realizing face scanning imaging by only one image ignores different details of the same disease presented under different angles and can not reflect the detail features on an imaging model; for patients of different height and body types, the positional calibration of existing imaging devices is still based on manual adjustment, which is a cumbersome task, especially when there are many visiting patients. And each imaging result through manual position calibration has a certain position error.
Disclosure of Invention
Aiming at the problems that the imaging technology has low resolution and limited facial detail capture and the position calibration of the existing imaging device is mainly manually adjusted due to the excessive dependence on the subjectivity of doctors in the current medical scene, the automatic scanning device and the method for the facial details of the patient are provided, and the facial feature information of the patient is captured through the movement of a depth+RGB color camera on a track, and then a digital twin model of the face of the patient is generated through an algorithm carried by a core processor, so that the problems of:
1. firstly, the horizontal-vertical track slide block control system based on the patient surface pose recognition algorithm and controlled by the stepping motor can calculate the difference between the face positions of the patients with different height and body types and the preset face contours of the device, and the face positions of the patients are adaptively positioned in a mode of adjusting the vertical height of the vertical track slide block and guiding the patients to adjust the horizontal positions by voice, so that the problem of input image data errors caused by a mode of manually adjusting the positions is solved. The facial pose recognition algorithm used by the device is based on a face key point detection method in the background technology, and the calibration of the scanning camera and the face of the user is completed in an auxiliary mode;
2. secondly, the mounted 3D face reconstruction method can use an image enhancement algorithm to enhance the image with limited input resolution. Under the condition of the same resolution, the enhanced image is used as the input of a 3D face reconstruction method, so that the accuracy of the reconstructed digital twin model can be obviously improved, further more facial feature details can be captured, and the problems of low imaging resolution and limited facial feature detail capture are solved. The 3D face reconstruction method used by the device is a 3D face reconstruction method based on an image enhancement technology in the background technology;
3. finally, the carried automatic scanning method for the face details of the patient based on deep learning can learn the face characteristics of the patient and appoint to finish the identification, positioning, segmentation and classification of focus areas, rapidly and objectively identify and label the abnormal areas of the face of the patient, and reduce the excessive dependence on subjective judgment of doctors and solve the problem of subjective dependence. The automatic scanning method for the face details of the patient used by the device is based on a deep neural network to divide, identify and classify the input high-definition face images of the patient and output classified face detail characteristics. The segmentation model adopts a U-net medical image segmentation neural network based on the background technology, which is a classical encoder-decoder structure for medical image segmentation to realize the facial image segmentation of a patient. The recognition and classification model adopts a CNN convolutional neural network based on the background technology, and realizes the recognition and classification of the face detail images through the extraction and the learning of the characteristics.
The technical scheme of the invention is as follows:
an automatic scanning device for the face details of a patient comprises a face position calibration module, a face image scanning module, a face imaging module and a central control module, wherein the face position calibration module, the face image scanning module and the face imaging module are arranged in a mutually crossed mode and are respectively and electrically connected with the central control module,
the facial position calibration module is used for adaptively adjusting the position of the facial scanning module according to the height and the body types of different patients;
the face scanning module scans and collects face characteristic data of a patient;
the face imaging module displays the scanning data and the generated digital twin model result of the patient, so that a doctor can check the result and perform interactive operation;
the central control module supports arithmetic logic and signal processing of the correct operation of the other 3 modules;
the face position calibration module comprises a vertical track, a vertical lifting sliding block and a patient interaction screen, wherein the vertical track is vertically arranged; the vertical lifting sliding block is fixedly arranged on a track of the vertical track, and the vertical position is automatically adjusted; the patient interaction screen is disposed at an upper position of the vertical track.
The face position calibration module further comprises a first control motor, an I-shaped screw rod, a first partition plate and a second partition plate, wherein the first partition plate is arranged at the upper position of the vertical track and provides a bottom supporting effect for the patient interaction screen, the second partition plate is arranged at the lower position of the vertical track, the I-shaped screw rod is arranged between the first partition plate and the second partition plate, the first control motor is arranged on the second partition plate and connected with the lower end of the I-shaped screw rod, and the vertical lifting slide block is fixedly arranged on the I-shaped screw rod and drives the I-shaped screw rod to rotate through the first control motor so as to realize up-down position adjustment.
The vertical lifting sliding block is provided with a first pulley at one end close to the vertical rail, the first pulley is provided with at least 2 first pulleys distributed on two sides, and the first pulleys are embedded with the vertical rail, so that the vertical lifting sliding block can stably adjust the upper position and the lower position.
The face position calibration module further comprises a screen supporting structure, the patient interaction screen is fixed on the vertical track through a first partition plate supporting the bottom of the patient interaction screen and a screen supporting structure supporting the top of the patient interaction screen, and the screen supporting structure adjusts a proper position to assist the front face of the patient interaction screen to incline to face the face of a patient.
The screen type of the patient interaction screen is a full-color LED display screen with a loudspeaker, and the contour line and other information of the standard position of the preset face are displayed under the control of the central control module, and the patient is assisted in horizontal adjustment of the position in a voice guidance mode.
The face scanning module comprises an arc sliding rail, a camera and an arc sliding rail slide block, wherein the arc sliding rail is fixedly arranged on the vertical lifting slide block, the arc sliding rail slide block which moves at a constant speed is arranged on the arc sliding rail, and the camera is arranged on the arc sliding rail through the arc sliding rail slide block;
the circular arc sliding rail comprises a bearing structure, a first edge baffle and a second edge baffle, wherein the bearing structure is arranged right below the bearing structure, the first edge baffle is arranged at one end of the bearing structure, the second edge baffle is arranged at the other end of the bearing structure, the bearing structure is fixed on the vertical lifting sliding block, and the circular arc sliding rail is fixedly arranged on the vertical lifting sliding block through the bearing structure;
the arc sliding rail is a 120-degree U-shaped arc sliding rail, a U-shaped groove is formed in the rail direction, and the U-shaped groove comprises 2U-shaped grooves on two sides;
the arc sliding rail sliding block comprises a second control motor, a second pulley on one side of the bottom and a stable resistance reducing block on the other side of the bottom, wherein the second control motor is connected with the second pulley, the second pulley and the stable resistance reducing block are respectively embedded into grooves of the 2U-shaped grooves on two sides, and the second pulley comprises at least 1 second pulley;
the circular arc sliding rail slide block also comprises a main gear and a slave gear which are meshed with each other, the second control motor is connected with the main gear, the slave gear is connected with the second pulley, and the slave gear comprises a plurality of slave gears matched with the second pulley;
the camera is a depth+RGB color camera, and a camera protection shell is arranged outside the camera.
The face scanning module further comprises a light supplementing lamp and an angle adjusting roller, wherein the light supplementing lamp is arranged at the top position of the vertical track to provide illumination compensation; the light supplementing lamp is characterized in that angle adjusting rollers are arranged in the light supplementing lamp, at least 1 angle adjusting roller is arranged, and the angle adjusting rollers are used for adjusting proper angles to assist the light lamp to incline to face the face of a patient.
The central control module comprises a core processor, a cooling fan group and a main body shell, wherein the core processor and the cooling fan group are arranged in the main body shell, the bottom end of the vertical track is fixedly arranged on a vertical surface of the main body shell, the doctor interaction screen is fixedly arranged on the other opposite inclined surface of the main body shell, and the inclined surface faces the doctor direction;
the processor type of the core processor is a processor carrying a deep learning chip, calculation power and rendering support of a CPU and a GPU are respectively provided for a motor control algorithm, a gesture recognition algorithm, a patient face detail automatic scanning algorithm and a 3D face reconstruction algorithm, and the core processor provides a storage space for caching scanning data and storing a final digital twin model;
the core processor is reserved with interfaces required by the functions of the expansion device; the radiating fan group is arranged on the core processor and is clung to the vent hole on one side of the main body shell, and the radiating fan group comprises at least 1 radiating fan; the main body shell is made of metal with strong heat dissipation performance.
The face imaging module comprises a doctor interaction screen, wherein the doctor interaction screen is arranged in a direction facing a doctor, and the screen type is a capacitive screen with a touch control function.
An automatic scanning method for the face details of a patient comprises the following operation steps:
constructing an automatic scanning device for the face details of the patient;
configuring an initial environment: the initializing device is used for sending a facial position calibration starting signal to the central control module when the patient is perceived to reach a preset position;
facial position calibration: the central control module receives a face position calibration start signal, invokes the face position calibration module to capture an initial image of the face of a patient, transmits the initial image to the central control module, calculates the difference between the initial position of the face of the patient and a preset face standard position through a gesture recognition algorithm, outputs gesture data to a motor control algorithm, performs vertical calibration according to a difference result, invokes the face position calibration module through the motor control algorithm to adjust to the corresponding horizontal height of the face of the patient, displays the outline of the preset face standard position, guides the patient to adjust to complete the horizontal calibration of the face position, prompts the patient to not adjust again after the vertical and horizontal position calibration of the face of the patient is completed, and sends a face image scanning start signal to the central control module;
scanning a face image: after receiving a facial image scanning start signal, the central control module invokes the facial position calibration module to perform illumination compensation operation through a light supplementing lamp, then controls the arc sliding rail slide block to collect facial image characteristic data on one side of a patient through a motor control algorithm, and then collects facial image characteristic data on the other side of the patient, and resets after the facial position calibration module is collected and sends a 3D face reconstruction start signal to the central control module;
3D face reconstruction: after receiving a 3D face reconstruction starting signal, the central control module pre-processes face data of a patient through a 3D face reconstruction algorithm, converts depth image data into point cloud data, converts the point cloud data into three-dimensional grid data, and performs texture mapping on RGB color image data to realize 3D reconstruction of the face of the patient and generate a digital twin model of the face of the patient;
doctor interaction operation: the central control module transmits the scanning data and the digital twin model to the facial imaging module for display to a doctor, and the doctor browses, edits, saves and analyzes the data on the facial imaging module with the touch control function at the moment.
The invention has the beneficial effects that:
1. the face position calibration module is provided with vertical lifting and horizontal posture calibration at the same time: as shown in fig. 1, the module can analyze gesture data of an initial image acquired by a patient interaction screen through a gesture recognition algorithm carried by a core processor, and then control a vertical lifting slide block on a circular arc slide rail to move through a first control motor based on a gesture recognition result, so that the vertical position of a camera on the circular arc slide rail slide block relative to a scanning object is automatically calibrated, and meanwhile, the horizontal position of a patient is calibrated in an auxiliary voice interaction mode. The face position calibration system can adaptively adjust the positions of the camera and the circular arc slide rail according to the height and the shape of a patient, and finally, the accurate positioning of the face of the scanned object is realized.
2. Face scanning module of U type slide rail formula face scanning that has illumination compensation and stable control simultaneously: the implementation process is as shown in fig. 2, the top end of the device is provided with a light supplementing lamp so as to ensure illumination compensation in the face shooting process of the camera, ensure that the image is not influenced by surrounding light sources, and ensure that a high-definition face image is acquired for analysis of facial organ diseases. The U-shaped groove, the second control motor, the second pulley, the stable friction reducing block, the master gear and the slave gear are reasonably arranged, so that the camera slider can move stably and uniformly.
Drawings
FIG. 1 is a flow chart of an implementation of a facial position calibration module according to the present invention;
FIG. 2 is a flow chart of an implementation of the facial scanning module of the present invention;
FIG. 3 is a schematic view of a part of the vertical lift slider of the present invention;
FIG. 4 is a schematic diagram of a face position calibration module portion of the present invention;
FIG. 5 is a schematic view of the position structure of the patient interaction screen of the present invention;
FIG. 6 is a schematic diagram of a light compensating lamp according to the present invention;
FIG. 7 is a schematic view of a partial structure of a circular arc slide rail according to the present invention;
FIG. 8 is a schematic view of the structure of the U-shaped groove of the present invention;
FIG. 9 is a schematic diagram of the structural relationship between a camera and a circular arc slide rail slider of the present invention;
FIG. 10 is a schematic diagram showing the transmission relationship between the inside of the circular arc slide rail slide block and the second pulley;
FIG. 11 is a bottom view of a camera and arcuate slide rail slider of the present invention;
FIG. 12 is a bottom view of the arcuate slide rail slider of the present invention;
FIG. 13 is a schematic view of a doctor interaction screen according to the present invention;
FIG. 14 is a schematic view of the overall structure of the patient face detail self-scanning apparatus of the present invention;
FIG. 15 is a flow chart of the process of implementing the patient face detail self-scanning method of the present invention;
fig. 16 is a schematic diagram of a patient face detail self-scanning method of the present invention.
The attached drawings are identified:
1. a vertical rail; 2. a vertical lifting slide block; 3. patient interaction screen: 4. a first pulley; 5. a first control motor; 6. an I-shaped screw; 7. a first separator; 8. a second separator; 9. a screen support structure; 10. a light supplementing lamp; 11. arc slide rail; 12. a camera; 13. arc slide rail slide block; 14. an angle adjusting roller; 15. a support structure; 16. a first edge baffle; 17. a second edge baffle; 18. a U-shaped groove; 19. a second control motor; 20. a second pulley; 21. a stable resistance reducing block; 22. a main gear; 23. a slave gear; 24. a doctor interaction screen; 25. a core processor; 26. a heat radiation fan group; 27. a main body housing.
Detailed Description
The invention will now be described in detail with reference to the drawings and specific examples. The present embodiment is implemented on the premise of the technical scheme of the present invention, and a detailed implementation manner and a specific operation process are given, but the protection scope of the present invention is not limited to the following examples.
In the description of the present invention, it should be noted that, if terms such as "center", "upper", "lower", "left", "right", "vertical", "horizontal", "inner", "outer", and the like are used, the indicated orientation or positional relationship is based on the orientation or positional relationship shown in the drawings, only for convenience of describing the present invention and simplifying the description, and does not indicate or imply that the indicated apparatus or element must have a specific orientation, be configured and operated in a specific orientation, and thus should not be construed as limiting the present invention.
An automatic scanning device for the face details of a patient comprises a face position calibration module, a face image scanning module, a face imaging module and a central control module, wherein the face position calibration module, the face image scanning module and the face imaging module are mutually crossed and are respectively and electrically connected with the central control module,
the facial position calibration module is mainly responsible for adaptively adjusting the positions of the facial scanning modules according to the height and the body types of different patients;
the face scanning module is mainly responsible for scanning and collecting facial feature data of a patient;
the face imaging module is mainly responsible for displaying the scanning data and the results of the digital twin model of the patient generated by the 3D face reconstruction algorithm, so that a doctor can check the results and perform interactive operation;
the central control module is mainly responsible for supporting the arithmetic logic and signal processing of the correct operation of the other 3 modules, and is a core module for correctly realizing the functions of the device.
The face position calibration module comprises a vertical track 1, a vertical lifting sliding block 2 and a patient interaction screen 3, wherein the vertical track 1 is vertically arranged, the vertical lifting sliding block 2 capable of automatically adjusting the upper and lower positions is fixedly arranged on the track of the vertical track 1, and the patient interaction screen 3 is arranged at the upper position of the vertical track 1.
As shown in fig. 3, a first pulley 4 is disposed at one end of the vertical lifting slider 2 near the vertical rail 1, the first pulley 4 has at least 2 first pulleys distributed on two sides, and the first pulley 4 is embedded in the vertical rail 1, so that the vertical lifting slider 2 can stably adjust the vertical position.
The structure of the facial position calibration model realizes the adjustment of the vertical height of the scanning area according to the different body types of the patients so as to accurately acquire the facial characteristic data of the patients.
The screen type of the patient interaction screen 3 is a full-color LED display screen with a loudspeaker, other necessary information such as the current position of a patient, the progress of facial image characteristic data acquisition and the like can be displayed through the control of a central control module, and when the horizontal position of the patient is greatly different from the standard position of a preset face through a gesture recognition algorithm, the contour line of the standard position of the preset face can be displayed on the patient interaction screen 3, and the patient is assisted in horizontal adjustment of the position in a voice guidance mode.
As shown in fig. 4, the facial position calibration module further includes a first control motor 5, an i-shaped screw 6, a first partition 7 and a second partition 8, wherein the first partition 7 is disposed at an upper position of the vertical track 1 and provides a bottom supporting effect for the patient interaction screen 3, the second partition 8 is disposed at a lower position of the vertical track 1, the i-shaped screw 6 is disposed between the first partition 7 and the second partition 8, the first control motor 5 is disposed on the second partition 8 and connected with a lower end of the i-shaped screw 6, and the vertical lifting slide 2 is fixedly disposed on the i-shaped screw 6 and drives the i-shaped screw 6 to rotate through the first control motor 5 to realize vertical position adjustment.
The first control motor 5 is a stepper motor.
As shown in fig. 5, the facial position calibration module further comprises a screen support structure 9, the patient interaction screen 3 being fixed on the vertical rail 1 by means of a first partition 7 supporting its bottom and a screen support structure 9 supporting its top, the screen support structure 9 being able to adjust the position to assist the front of the patient interaction screen 3 to tilt to face the patient's face.
The patient interaction screen 3 is preset to be inclined at an angle of 15 ° to the vertical.
The face scanning module comprises a light supplementing lamp 10, an arc sliding rail 11, a camera 12 and an arc sliding rail slide block 13, wherein the light supplementing lamp 10 for providing illumination compensation is arranged at the top position of the vertical track 1, the arc sliding rail 11 is fixedly arranged on the vertical lifting slide block 2, the arc sliding rail slide block 13 capable of stably moving at a uniform speed is arranged on the arc sliding rail 11, and the camera 12 is arranged on the arc sliding rail 11 through the arc sliding rail slide block 13.
As shown in fig. 6, the light filling lamp 10 is provided with at least 1 angle adjusting roller 14, and the angle adjusting rollers 14 can manually adjust a proper angle according to the actual environment to assist the light filling lamp 10 to incline to face the face of the patient.
The light supplementing lamp 10 is preset to have an inclination angle of 30 degrees with respect to the vertical direction.
The main function of the light supplementing lamp is illumination compensation, so that the face characteristic acquisition data with similar illumination can be obtained at the near point of the device no matter what the indoor illumination environment is, or auxiliary light is provided when shooting under the condition of lack of light. This enhances the regularity of the facial feature acquisition data at the numerical level, and the constant illuminance also brings about improvement in accuracy.
The patient interaction screen 3 is located in the middle of the vertical direction of the light supplement lamp 10 and the circular arc slide rail 11.
As shown in fig. 4 and 7, the circular arc slide rail 11 includes a supporting structure 15 disposed directly below, a first edge baffle 16 at one end, and a second edge baffle 17 at the other end, the supporting structure 15 is fixed on the vertical lifting slide block 2, and the circular arc slide rail 11 is fixedly disposed on the vertical lifting slide block 2 through the supporting structure 15.
As shown in fig. 8, the arc slide rail 11 further includes a U-shaped groove 18 formed along the rail direction, the arc slide rail 11 is a 120 ° U-shaped arc slide rail, and the U-shaped groove 18 includes 2U-shaped grooves on two sides.
The camera 12 is a depth+rgb color camera, and is externally provided with a camera protection housing, which provides picture support for the facial position calibration module.
As shown in fig. 9-12, the arc slide rail slide block 13 includes a second control motor 19, a second pulley 20 on one side of the bottom and a stabilizing and resistance reducing block 21 on the other side of the bottom, the second control motor 19 is connected with the second pulley 20, the second pulley 20 and the stabilizing and resistance reducing block 21 are respectively embedded in 2U-shaped grooves on two sides, and the second pulley 20 includes 2 second pulleys.
The second control motor 19 is a stepper motor.
The circular arc slide rail slide block 13 further comprises a main gear 22 and a secondary gear 23 which are meshed with each other, the second control motor 19 is connected with the main gear 22, the secondary gear 23 is connected with the second pulley 20, and the secondary gear 23 comprises 2 secondary gears matched with the second pulley 20.
The circular arc slide rail 11 and the circular arc slide rail slider 13 are structurally designed to be stable. The main gear 22 driven by the second control motor 19 in the circular arc slide rail slide block 13 rotates, so that the driven gear 23 drives the pulley to be embedded with the U-shaped groove on one side of the circular arc slide rail 11 and roll, and uniform and stable movement of the circular arc slide rail slide block 13 is realized; the stable friction reducing block 21 is assisted in the process to fix the embedded stable gravity center of the U-shaped groove at the other side, so that the stability of the structures of the whole circular arc sliding rail 11 and the circular arc sliding rail slide block 13 is ensured.
The function of the face scanning module is to control the second control motor 19 through a motor control algorithm so that the circular arc slide rail slide block 13 carrying the camera 12 moves on the circular arc slide rail 11 at a uniform speed, and therefore the collection of facial image characteristic data of a patient is achieved.
As shown in fig. 13, the face imaging module includes a doctor interaction screen 24, where the doctor interaction screen 24 is set in a direction facing the doctor (i.e. a direction facing away from the patient), and the screen is a capacitive screen with a touch function, so that the doctor can browse scan data and imaging results and perform corresponding interaction operations, and the interaction modes include browsing, editing, storing and analyzing the scan data and imaging results.
The central control module comprises a core processor 25, a cooling fan set 26 and a main body shell 27, wherein the core processor 25 and the cooling fan set 26 are arranged in the main body shell 27, the bottom end of the vertical track 1 is fixedly arranged on a vertical surface of the main body shell 27, the doctor interaction screen 24 is fixedly arranged on the other opposite inclined surface of the main body shell 27, and the inclined surface faces the doctor direction.
The processor type of the core processor 25 is a processor on which a deep learning chip is mounted, calculation power and rendering support of a CPU and a GPU are respectively provided for a motor control algorithm, a gesture recognition algorithm, a patient face detail automatic scanning method and a 3D face reconstruction algorithm, and meanwhile, the core processor 25 also provides a storage space for caching scanning data and storing a final digital twin model.
The core processor 25 reserves interfaces required for other expansion device functions, such as PCIE interfaces supporting an expansion graphics dock.
The cooling fan set 26 is arranged on the core processor 25 and clings to the vent hole on one side of the main body shell 27, and is of a vertical structure, the cooling fan set 26 comprises at least 1 cooling fan, and the cooling fan set is used for rapidly dispersing high temperature generated by the deep learning chip through fan rotation when the core processor 25 operates at high speed, so that the service life of the core processor is prolonged, and meanwhile, limitation of calculation force of the deep learning chip caused by overhigh temperature is avoided.
The main body case 27 is made of metal having high heat dissipation performance.
An overall structural schematic of an automated scan of patient facial details is shown in fig. 14.
An automatic scanning method for the face details of a patient comprises the following operation steps:
constructing an automatic scanning device for the face details of the patient;
configuring an initial environment: the initializing device is used for sending a facial position calibration starting signal to the central control module when the patient is perceived to reach a preset position;
facial position calibration: after receiving a face position calibration start signal, the central control module invokes the face position calibration module to capture an initial image of the face of a patient and transmits the initial image to the central control module, the central control module calculates the difference between the initial position of the face of the patient and a preset face standard position through a gesture recognition algorithm, outputs gesture data to a motor control algorithm and carries out vertical calibration according to a difference result, invokes the face position calibration module through the motor control algorithm to adjust to the corresponding horizontal height of the face of the patient, and the face position calibration module displays the outline of the preset face standard position, guides the patient to adjust to complete the horizontal calibration of the face position;
scanning a face image: after receiving the facial image scanning start signal, the central control module invokes the facial position calibration module to perform illumination compensation operation through the light supplementing lamp, then controls the arc sliding rail slide block to collect facial image characteristic data on one side of a patient through the motor control algorithm, then collects facial image characteristic data on the other side of the patient, resets after the facial position calibration module collects, and sends a 3D face reconstruction start signal to the central control module;
3D face reconstruction: after receiving a 3D face reconstruction starting signal, the central control module preprocesses face data of a patient through a 3D face reconstruction algorithm, converts depth image data into point cloud data, converts the point cloud data into three-dimensional grid data, and performs texture mapping on RGB color image data to realize 3D reconstruction of the face of the patient and generate a digital twin model of the face of the patient;
doctor interaction operation: the central control module transmits the scanning data and the digital twin model to the facial imaging module for display to a doctor, and the doctor can browse, edit, store and analyze the data on the facial imaging module with the touch control function at the moment.
The implementation process of this embodiment is as follows:
in order to acquire a high-precision face scanning image of a patient and facilitate diagnosis and analysis of facial organ diseases by doctors, the invention develops an automatic scanning device for the face details of the patient in a medical scene. The whole process of patient face scanning using the device of the present invention includes configuring 5 parts of the initial environment, face position calibration, face image scanning, 3D face reconstruction, doctor interaction, as shown in fig. 15. The specific process is as follows:
1 configuring an initial Environment
Step 1.1: maintaining an indoor environment with proper temperature and humidity, switching on a power supply, and initializing the device;
step 1.2: the patient sits directly in front of the device, and the front end camera 12 of the device senses whether the patient sits and signals the core processor 25 to begin facial position calibration.
2 facial position calibration
Step 2.1: upon receipt of the start signal, the device will first invoke camera 23 to transmit the captured initial image of the patient's face to core processor 25;
step 2.2: the core processor 25 calculates the difference between the initial position of the face of the patient and the standard position of the preset standing case of the device according to the captured image through a gesture recognition algorithm;
step 2.3: according to the gesture recognition result of the initial position of the face of the patient, when the position of the patient cannot meet the condition, the core processor 25 calls a vertical calibration motor control algorithm, and sends a command to the first control motor 5 according to the gesture data of the patient and the algorithm result, and controls the vertical lifting slide block 2 to adjust the vertical height, so that the camera 12 and the face of the patient are at the same horizontal height;
step 2.4: after the vertical calibration is completed, the core processor 25 will continue to call the patient interaction screen 3 to send out a voice command according to the gesture recognition result, and display the outline of the preset standard face position on the patient interaction display screen 3, and the voice prompt guides the patient to complete the horizontal calibration of the face position so as to ensure that the face of the patient returns to the correct scanning area;
step 2.5: when the alignment of the vertical and horizontal positions of the patient's face is completed, the core processor 25 issues a command to perform a face scanning process, and the camera 12 starts moving from an initial position located at the very middle of the circular arc slide rail 11.
3 facial image scanning
Step 3.1: the core processor 25 sends out a light supplementing command, and the light supplementing lamp 10 above the device is lightened, so that the process of collecting the facial data of the patient is always carried out under the similar illumination environment;
step 3.2: the core processor 25 starts a horizontal scanning control algorithm, controls the second control motor 19 to enable the circular arc slide rail slide block 13 carrying the camera 12 to move towards one side at a constant speed and stably around the face of a patient to the first edge baffle 16 on the side of the circular arc slide rail 11, and collects facial image characteristic data of the patient corresponding to the side;
step 3.3: then the second control motor 19 controls the camera 12 to stably move 120 DEG towards the other side at a constant speed to the second edge baffle 17 at the other side of the circular arc slide rail 11, and facial image characteristic data of the other side corresponding to the patient are acquired;
step 3.4: finally, the camera 12 moves at a constant speed and stability for 60 degrees to the middle of the arc slide rail 11 towards the original direction, and reset is completed;
step 3.5: after the facial image scanning is completed, the motor control algorithm feeds back a completion signal to the core processor 25, and then the core processor 25 sends out a command to enter a 3D face reconstruction process.
4:3D face reconstruction
Step 4.1: after receiving the face image scan data, the core processor 25 invokes a 3D face reconstruction algorithm to pre-process the patient data, converting the depth image data into point cloud data;
step 4.2: the 3D face reconstruction algorithm converts the point cloud data into three-dimensional grid data, and performs texture mapping on RGB color image data, so that 3D reconstruction of the face of the patient is realized, and a digital twin model of the face of the patient is generated.
5 doctor interaction operation
Step 5.1: finally, the device displays the scanning data and the digital twin model on a doctor interaction screen, and the doctor can browse, edit, store and analyze the data on the interaction screen with the touch function at the moment.
An overall method implementation schematic of a patient facial detail auto-scan method is shown in fig. 16.
The above examples illustrate only one embodiment of the invention, which is described in more detail and is not to be construed as limiting the scope of the invention. It should be noted that it will be apparent to those skilled in the art that several variations and modifications can be made without departing from the spirit of the invention, which are all within the scope of the invention. Accordingly, the scope of protection of the present invention is to be determined by the appended claims.

Claims (10)

1. The automatic scanning device for the face details of the patient is characterized by comprising a face position calibration module, a face image scanning module, a face imaging module and a central control module, wherein the face position calibration module, the face image scanning module and the face imaging module are mutually crossed and are respectively and electrically connected with the central control module,
the facial position calibration module is used for adaptively adjusting the position of the facial scanning module according to the height and the body types of different patients;
the face scanning module scans and collects face characteristic data of a patient;
the face imaging module displays the scanning data and the generated digital twin model result of the patient, so that a doctor can check the result and perform interactive operation;
the central control module supports arithmetic logic and signal processing of the correct operation of the other 3 modules;
the face position calibration module comprises a vertical track (1), a vertical lifting sliding block (2) and a patient interaction screen (3), wherein the vertical track (1) is vertically arranged; the vertical lifting sliding block (2) is fixedly arranged on a track of the vertical track (1) and automatically adjusts the upper and lower positions; the patient interaction screen (3) is arranged at an upper position of the vertical track (1).
2. The automatic scanning device for the face details of the patient according to claim 1, wherein the face position calibration module further comprises a first control motor (5), an i-shaped screw (6), a first partition plate (7) and a second partition plate (8), the first partition plate (7) is arranged at the upper position of the vertical track (1) and provides a bottom supporting effect for the patient interaction screen (3), the second partition plate (8) is arranged at the lower position of the vertical track (1), the i-shaped screw (6) is arranged between the first partition plate (7) and the second partition plate (8), the first control motor (5) is arranged on the second partition plate (8) and is connected with the lower end of the i-shaped screw (6), and the vertical lifting slide block (2) is fixedly arranged on the i-shaped screw (6) and drives the i-shaped screw (6) to rotate through the first control motor (5) so as to realize up-down position adjustment.
3. The automatic patient face detail scanning device according to claim 2, wherein a first pulley (4) is arranged at one end of the vertical lifting slide block (2) close to the vertical track (1), the first pulley (4) is provided with at least 2 first pulleys distributed on two sides, and the first pulleys (4) are embedded into the vertical track (1) so that the vertical lifting slide block (2) can stably adjust the upper position and the lower position.
4. A patient face detail automatic scanning apparatus as claimed in claim 3, characterized in that said face position calibration module further comprises a screen support structure (9), said patient interaction screen (3) being fixed on said vertical rail (1) by a first baffle (7) supporting its bottom and a screen support structure (9) supporting its top, said screen support structure (9) being adapted in position to assist tilting of the front face of said patient interaction screen (3) to face the patient's face.
5. The automatic patient face detail scanning device according to claim 4, wherein the screen type of the patient interaction screen (3) is a full-color LED display screen with a speaker, and the central control module is used for displaying contour lines and other information of the preset face standard position and assisting the patient in horizontally adjusting the position in a voice guidance mode.
6. The automatic scanning device for patient face details according to any one of claims 1-5, wherein the face scanning module comprises an arc slide rail (11), a camera (12) and an arc slide rail slide block (13), the arc slide rail (11) is fixedly arranged on the vertical lifting slide block (2), the arc slide rail slide block (13) which moves at a constant speed is arranged on the arc slide rail (11), and the camera (12) is arranged on the arc slide rail (11) through the arc slide rail slide block (13);
the circular arc sliding rail (11) comprises a bearing structure (15) arranged right below, a first edge baffle (16) at one end and a second edge baffle (17) at the other end, the bearing structure (15) is fixed on the vertical lifting sliding block (2), and the circular arc sliding rail (11) is fixedly arranged on the vertical lifting sliding block (2) through the bearing structure (15);
the arc sliding rail (11) is a 120-degree U-shaped arc sliding rail, a U-shaped groove (18) is formed along the rail direction, and the U-shaped groove (18) comprises 2U-shaped grooves on two sides;
the arc sliding rail sliding block (13) comprises a second control motor (19), a second pulley (20) at one side of the bottom and a stable friction reducing block (21) at the other side of the bottom, wherein the second control motor (19) is connected with the second pulley (20), the second pulley (20) and the stable friction reducing block (21) are respectively embedded into grooves of the 2U-shaped grooves at two sides, and the second pulley (20) comprises at least 1 second pulley;
the circular arc sliding rail slide block (13) further comprises a main gear (22) and a slave gear (23) which are meshed with each other, the second control motor (19) is connected with the main gear (22), the slave gear (23) is connected with the second pulley (20), and the slave gear (23) comprises a plurality of slave gears matched with the second pulley (20);
the camera (12) is a depth+RGB color camera and is externally provided with a camera protection shell.
7. The patient facial detail automatic scanning apparatus as claimed in claim 6, wherein the facial scanning module further comprises a light supplement lamp (10) and an angle adjustment roller (14), the light supplement lamp (10) being disposed at a top position of the vertical track (1) to provide illumination compensation; an angle adjusting roller (14) is arranged in the light supplementing lamp (10), at least 1 angle adjusting roller (14) is arranged, and the angle adjusting roller (14) adjusts a proper angle to assist the light lamp (10) to incline to face the face of a patient.
8. The automatic patient face detail scanning apparatus as set forth in claim 7, wherein the central control module includes a core processor (25), a radiator fan group (26) and a main body casing (27), the core processor (25), the radiator fan group (26) are all disposed in the main body casing (27), the bottom end of the vertical rail (1) is fixedly disposed on a vertical surface of the main body casing (27), and the doctor interaction screen (24) is fixedly disposed on another opposite inclined surface of the main body casing (27), the inclined surface facing the doctor direction;
the processor type of the core processor (25) is a processor carrying a deep learning chip, calculation power and rendering support of a CPU and a GPU are respectively provided for a motor control algorithm, a gesture recognition algorithm, a patient face detail automatic scanning algorithm and a 3D face reconstruction algorithm, and the core processor (25) provides a storage space for caching scanning data and storing a final digital twin model;
the core processor (25) is reserved with interfaces required by the functions of the expansion device; the radiating fan group (26) is arranged on the core processor (25) and is clung to a vent hole on one side of the main body shell (27), and the radiating fan group (26) comprises at least 1 radiating fan; the main body housing (27) is made of metal with strong heat dissipation performance.
9. The patient facial detail automatic scanning apparatus as claimed in claim 8, wherein the facial imaging module comprises a doctor interaction screen (24), the doctor interaction screen (24) being arranged to face a doctor direction, the screen being of the capacitive screen type with touch control.
10. An automatic scanning method for the face details of a patient is characterized by comprising the following operation steps:
constructing an automatic scanning device for the face details of the patient;
configuring an initial environment: the initializing device is used for sending a facial position calibration starting signal to the central control module when the patient is perceived to reach a preset position;
facial position calibration: the central control module receives a face position calibration start signal, invokes the face position calibration module to capture an initial image of the face of a patient, transmits the initial image to the central control module, calculates the difference between the initial position of the face of the patient and a preset face standard position through a gesture recognition algorithm, outputs gesture data to a motor control algorithm, performs vertical calibration according to a difference result, invokes the face position calibration module through the motor control algorithm to adjust to the corresponding horizontal height of the face of the patient, displays the outline of the preset face standard position, guides the patient to adjust to complete the horizontal calibration of the face position, prompts the patient to not adjust again after the vertical and horizontal position calibration of the face of the patient is completed, and sends a face image scanning start signal to the central control module;
scanning a face image: after receiving a facial image scanning start signal, the central control module invokes the facial position calibration module to perform illumination compensation operation through a light supplementing lamp, then controls the arc sliding rail slide block to collect facial image characteristic data on one side of a patient through a motor control algorithm, and then collects facial image characteristic data on the other side of the patient, and resets after the facial position calibration module is collected and sends a 3D face reconstruction start signal to the central control module;
3D face reconstruction: after receiving a 3D face reconstruction starting signal, the central control module pre-processes face data of a patient through a 3D face reconstruction algorithm, converts depth image data into point cloud data, converts the point cloud data into three-dimensional grid data, and performs texture mapping on RGB color image data to realize 3D reconstruction of the face of the patient and generate a digital twin model of the face of the patient;
doctor interaction operation: the central control module transmits the scanning data and the digital twin model to the facial imaging module for display to a doctor, and the doctor browses, edits, saves and analyzes the data on the facial imaging module with the touch control function at the moment.
CN202211331303.2A 2022-10-28 2022-10-28 Automatic scanning device and method for face details of patient Pending CN116228625A (en)

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CN202211331303.2A CN116228625A (en) 2022-10-28 2022-10-28 Automatic scanning device and method for face details of patient

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Application Number Priority Date Filing Date Title
CN202211331303.2A CN116228625A (en) 2022-10-28 2022-10-28 Automatic scanning device and method for face details of patient

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