359 results about "SKIN REGIONS" patented technology

A method of anonymizing medical images includes acquiring or receiving a first medical image; separating an identification area containing anatomical structure information and a de-identification area containing a skin area in the first medical image; generating a de-identified image including a plurality of pattern areas with a predetermined size for the de-identification area; and generating a second medical image by replacing the de-identification area with the de-identified image.

Disclosed are a method of anonymizing medical images, the method comprising: acquiring or receiving a first medical image; separating an identification area containing anatomical structure information and a de-identification area containing a skin area in the first medical image; generating a de-identified image including a plurality of pattern areas with a predetermined size for the de-identification area; and generating a second medical image by replacing the de-identification area with the de-identified image.

Exemplary methods and systems can be provided for resurfacing of skin that include formation of a plurality of small holes, e.g., having widths greater than about 0.2 mm and less than about 0.7 mm or 0.5 mm, using a mechanical apparatus. Compressive and / or tensile forces can then be applied to the treated region of skin as the damage heals to facilitate hole closure, and provide enhanced and / or directional shrinkage of the treated skin area.

The present invention relates to apparatus for use with a treatment device configured to perform a treatment operation on a body part of a subject, a system and a method. The apparatus (40) comprises a processing unit (46) configured to estimate a position of a current treatment area corresponding to an area of skin that the treatment device would apply a light pulse to while at the current treatment position; determine the distance, in movement direction of the treatment device, of the current treatment area from a previous treatment area corresponding to an area of skin that the treatment device applied a previous light pulse to while at a previous treatment position; determine if the distance is zero or an integer multiple of the width of the treatment area in movement direction of the treatment device; and generate a pulse control signal for controlling the treatment device to generate and apply a light pulse to the current treatment area of the skin if the distance has been determined to be zero or an integer multiple of the width of the treatment area.

The invention provides an intense pulsed light skin beauty local area identification method and system, and relates to the technical field of phototherapy, and the method comprises the steps: collecting an original face image of a patient, obtaining a historical skin treatment segmentation data set, carrying out the preprocessing of the original face image, and obtaining a standard face image; based on image feature information in the skin treatment segmentation data set, constructing a skin region division model, inputting the facial standard image into the skin region division model for target recognition, and obtaining a plurality of to-be-treated region images in the facial standard image; performing independent component analysis on the to-be-treated area image to obtain a melanin channel and a hemoglobin channel in the to-be-treated area image; constructing a multi-modal attention network model, inputting the melanin channel and the hemoglobin channel into the multi-modal attention network model for feature extraction and segmentation, and respectively obtaining melanin segmentation information and hemoglobin segmentation information; and fusing the melanin segmentation information and the hemoglobin segmentation information to obtain a skin treatment segmentation map, collecting treatment features in the skin treatment segmentation map, classifying the treatment features according to a random forest classifier, obtaining a skin treatment type corresponding to each to-be-treated area image, and obtaining the skin treatment type corresponding to each to-be-treated area image. And a treatment scheme corresponding to the skin treatment type is given. According to the method, the local detail sensitivity and the global information processing efficiency of the skin region division model can be improved.

The invention relates to the technical field of beauty instruments, and discloses a beauty instrument and a control method thereof. A massage head; the driving assembly is arranged in the machine body and connected with the massage head, and the driving assembly can drive the massage head to stretch out and draw back relative to the machine body. The driving assembly can drive the massage head to stretch out and draw back relative to the machine body, so that the massage head can be prevented from staying on the same skin area for a too long time, and face scalding or other skin injuries caused by the fact that the massage head stays for a long time are avoided. In addition, due to the fact that the driving assembly is arranged in the machine body, the machine body can protect the driving assembly.

The invention discloses a newborn face feature rare disease auxiliary diagnosis system based on AI image recognition, relates to the technical field of rare disease auxiliary diagnosis, and aims to solve the technical problem that dynamic feature analysis is insufficient in existing newborn rare disease auxiliary diagnosis. Detection, segmentation, feature classification and dynamic change analysis are completed, and abnormal textures, pigment distribution or blood vessel features are identified; the face key point analysis module is used for marking face key anatomical points, calculating three-dimensional space coordinates and analyzing relative positions and geometrical relationships of the key points and evolution trends of the key points along with time; the dynamic modeling module is used for constructing a dynamic evolution model of the facial features of the newborns along with the change of day ages, and correlating the time dependence of growth and development stages and rare disease features; and the feature fusion unit is used for integrating output results of the skin analysis module, the face key point analysis module and the dynamic modeling module. The method has the advantage of improving the diagnosis accuracy.

The invention provides a hair follicle transplantation method and system, a program unit, a storage medium and a program product, and the method comprises the steps: enabling a tensioner to apply downward pressure to the skin, driving a first tensioning part and a second tensioning part to be away from each other, and expanding the skin to form an expanded skin region; the system comprises a mechanical arm tail end tool, the mechanical arm tail end tool moves, gets close to an expanded skin area and executes a hair follicle transplantation task, the system further comprises a controller, the controller evaluates hair follicle transplantation parameters and formulates a hair follicle transplantation plan, and in a hair follicle transplantation mode, the controller controls the mechanical arm tail end tool to perform incision at a transplantation part in a manner that the incision direction and / or depth can be controlled. And the blocking device keeps the hair follicle at the required depth, and the mechanical arm tail end tool is retracted to complete the transplantation task. According to the application, the tensioner can be automatically controlled to tension the scalp or loosen the scalp, the tensioning degree of the scalp can be adjusted, the needling depth, the needling angle and the needling density are adjusted according to the obtained tensioning degree of the scalp, the batch consistency of extracted hair follicles is improved, and the hair follicle transplantation effect is improved.

The invention discloses a path planning method based on clustering, a surgical robot and related products. The method comprises the following steps: acquiring a first three-dimensional CT image, wherein the first three-dimensional CT image comprises a skin area of a target object and a first tissue of the target object; an end point of the target path is determined from the first tissue. At least two first candidate points of the target path are determined from the skin region. And determining at least two first candidate paths based on the at least two first candidate points and the end point of the target path. And clustering the at least two first candidate paths to obtain at least one first path set. And determining a second path set from the at least one first path set, wherein the number of the first candidate paths in the second path set is greater than or equal to a second threshold. And determining a target path based on the second path set. Through the method, the error-tolerant rate of the target path can be improved.

The present invention discloses a multi-wavelength tunable laser and sensing system, which relates to the field of lasers and includes: a setting module for presetting or selecting two wavelengths of laser beams in the laser; a camera module for collecting the user's target skin surface image for treatment in real time, identifying the tumor area and the healthy skin area in the image data, and identifying the current skin surface position of the laser beam. The present invention identifies the tumor area and the healthy skin area in the operation data by collecting the user's target skin surface image for treatment, further plans the laser treatment path based on the target skin surface image, and controls the laser in the process of moving according to the treatment path, in combination with the sensor to sense the tumor thickness, so as to achieve further intelligent control of the movement speed of the laser in the process of moving according to the treatment path, so that the tumor position on the user's skin surface can be treated more adaptively.

The invention discloses a skin LC-OCT image segmentation method based on improved GAN and multi-feature fusion. The skin LC-OCT image segmentation method comprises the following steps: collecting a skin B-scan sample by adopting LC-OCT equipment and storing the skin B-scan sample as an image; the method comprises the following steps: constructing a generator fusing reflection filling, multi-scale coding-decoding, self-attention and residual blocks, cooperating with a multi-scale fusion discriminator and a weight sharing twin network, and realizing high-fidelity denoising and enhancement through joint optimization of perception loss, multi-scale SSIM loss and Wasserstein adversarial loss; preprocessing and positioning a skin area based on a threshold value or morphology and normalizing the skin area; gradient is extracted from the de-noised image, and dynamic path search is carried out in combination with a gradient difference minimum criterion and a random forest; and after adaptive sampling and spline fitting are carried out on the path, candidates are generated through a random forest, and fracture or dislocation of a focus area is corrected. Therefore, accurate segmentation of the LC-OCT image of the skin layer can be realized in a high-noise environment, a high-quality enhanced data set can be constructed, and a reliable basis is provided for early diagnosis of skin diseases.

The invention relates to the technical field of computers, in particular to a parameter optimization method and system for processing a skin abnormal area through SOD, according to the method, a reference skin area image can be flexibly selected according to an actual application scene, an SOD basic parameter vector used for assisting SOD component parameter adjustment can be determined through an image analysis and data processing process, and the SOD basic parameter vector can be used for assisting SOD component parameter adjustment. The SOD basic parameter vector does not need to be obtained through an experiment mode, the application scene of the SOD basic parameter vector can be flexibly adjusted by replacing a plurality of processed reference skin area images, so that the SOD component parameter optimization can be carried out by taking the SOD basic parameter vector as a reference, and the SOD component parameter optimization efficiency is improved. Compared with the prior art that experiments are carried out by traversing the SOD component parameters, the method has the advantages that the number of experiments in the SOD component research process can be reduced, so that the efficiency of optimizing the SOD component parameters is improved, corresponding SOD basic parameter vectors can be provided for different scenes, and the efficiency of optimizing the SOD component parameters is further improved.

The invention relates to the technical field of image data processing, in particular to an identification photo intelligent reloading processing method and device, and the method comprises the steps: carrying out the cleaning operation of clothes and non-face skin regions of a user image, and synchronously updating a corresponding mask image, and calculating neck key points according to the user image after cleaning the clothes and the non-human face skin area and the mask image, mapping a neck template to a corresponding area of the user image by using the neck key points, and performing replacement and detail processing to obtain the user image after the neck is regenerated. And determining position coordinates of clothes to be replaced on the user image after the neck is regenerated, and fusing the position coordinates with the user image after the neck is regenerated so as to generate a final clothes replacement result graph. According to the invention, the photo that the neck part is shielded by the tall-necked clothes or scarf and uploaded by the user can be optimized, and the final clothes changing effect is achieved.

The embodiment of the invention provides a high-resolution portrait photo processing method and device, equipment and a medium, and relates to the technical field of image processing. The method comprises the following steps: acquiring an original portrait picture, wherein the original portrait picture is a high-resolution portrait picture; performing skin segmentation on the original human image photo to obtain a skin area mask; slicing the original human picture to obtain a plurality of image slices; determining a target image slice from the plurality of image slices by adopting a skin area mask; processing the target image slice by adopting a preset flaw removing network to obtain a target flaw removed slice image of the target image slice; and generating a target effect picture corresponding to the original figure picture according to the target flaw removal slice picture and the original figure picture. Therefore, by firstly slicing and then removing the flaws, the flaw detection is avoided, the flaw removing precision is improved, the image processing of the ultrahigh-resolution large image is also realized, the image processing application range is expanded, and the image processing cost is reduced.

A fractional handpiece and systems thereof for skin treatment include a passively Q-switched laser assembly operatively connected to a pump laser source to receive a pump laser beam having a first wavelength and a beam-splitting assembly operable to scan a solid beam emitted by the passively Q-switched laser assembly and form an array of micro-beams across a segment of skin. The passively Q-switched laser assembly generates a sub-nanosecond pulsed laser beam having a second wavelength. The fractional handpiece may also incorporate a wavelength switching assembly, enabling selective delivery of both the second and third wavelengths, while providing control over the energy output at each wavelength, all within a single handpiece. The passively Q-switched laser assembly has an unstable cavity operation.

A multimodal imaging unit for depth-surface imaging of a skin region of interest includes an ultrasound imaging transceiver, an optically transparent acoustic deflector, an optical module, and an optical camera sensor. An ultrasound beam emitted towards the acoustic deflector is deflected towards the skin region of interest, and an ultrasound beam reflected from the skin region of interest is returned to the ultrasound imaging transceiver. An optical beam from the optical module is passed through the acoustic deflector to a skin area of the skin region of interest and an optical beam reflected from the skin area is returned to an optical camera sensor through the acoustic deflector. The transceiver and the acoustic deflector are surrounded by an intermediary coupling medium and are hermetically enclosed by a cover provided with an acoustically and optically transparent access port for the ultrasound beams and the optical beams.

A method for measuring a non-contact biometric information, includes steps of photographing an image including a user's face; detecting a face area in a frame of a photographed image; detecting a landmark within the face area and starting a tracking mode when a specific landmark is detected; detecting a movement of the face area in the tracking mode and determining a section in which the movement of the face is less than a reference value; and extracting a skin area within the face area in the determined section and acquiring pixel change component data of the skin area.

The invention provides a multi-target person image face replacement and skin color coordination method and system, and relates to the technical field of artificial intelligence image processing, and the method comprises the steps: receiving a source face image and a target image sequence containing a plurality of target persons; performing character detection on each target image, and retaining a character detection frame of which the confidence is higher than a threshold value; cutting the figure area based on the detection frame and expanding pixel redundancy to form an expanded cut image including a head and an adjacent skin area; zooming all the expanded and cut images to a uniform resolution ratio and then splicing the expanded and cut images into an optimized long image; and performing semantic segmentation on the optimized long graph, generating a multi-layer mask comprising a core mask layer, an extension mask layer and a coordination mask layer, and performing adaptive edge processing. Through a preprocessing strategy, multi-layer mask control, a style guiding mechanism and a skin color and illumination coordination technology, the quality, efficiency and practicability of a face changing result are improved.

A method of operation of a compute system includes: qualifying a patient image for analyzing a suspected skin condition; detecting a skin area in the patient image; segmenting the skin area into a segmented image including the suspected skin condition; cropping the segmented image to form a cropped image including the suspected skin condition at a center of the cropped image; analyzing the suspected skin condition to identify a skin disease result and a disease subclass from the cropped image; and assembling a disease identification display including the patient image, a skin disease indication, an image match score, and the disease subclass for displaying on a device.

The invention discloses an AI-based multi-disease chronic disease information intelligent management system, and relates to the technical field of medical information, and the system is provided with a laser response capture module and a multi-dimensional data processing module, and can collect an RGB image data set and an infrared thermogram data set of a skin area at a set time point after laser treatment, and can obtain an RGB image data set and an infrared thermogram data set; and performing standardization processing and white spot region segmentation on the image based on an AI image processing model, and further extracting morphological parameters such as area, edge curvature kurtosis and tangential direction disturbance of the white spots and thermal parameters such as a temperature gradient recovery value, temperature change curvature and regional heat flux density. According to the system, a structural convergence tension index STCI and a thermal response consistency mapping index HRCI are calculated through cooperative work of a structural convergence analysis module and a thermal recovery analysis module, the skin response process is comprehensively measured from the two dimensions of structure and thermal power, and the problem of inaccurate evaluation caused by traditional visual observation and subjective judgment is effectively solved.

The invention discloses a semi-supervised non-contact neonatal jaundice home intelligent early warning method based on image calibration, and the method comprises the steps: building a camera response function database, and building a color constancy depth model and a skin region segmentation network; designing a strong and weak enhancement strategy by using a large amount of label-free home data, constructing a time and context comparison learning module, and performing self-supervised training on a feature encoder; a small amount of labeled hospital data and a large amount of unlabeled family data are combined, and semi-supervised fine tuning is realized through pseudo label generation and supervised comparative learning; image sequences continuously uploaded by a user are input into the model, multi-day prediction of the bilirubin level is achieved, prediction uncertainty is quantified in combination with a Bayesian method, the risk boundary is dynamically adjusted, and personalized early warning is provided. According to the method, a user does not need to use a physical colorimetric card, color measurement errors caused by model differences of mobile equipment and variability of household illumination are inhibited from a data source, and the accuracy and robustness of subsequent jaundice assessment are improved; through a training framework combining self-supervised pre-training and semi-supervised fine tuning, the understanding ability and generalization performance of the model for the sequential characteristics of jaundice are improved.

A skin inspection device for identifying abnormalities; the device comprising: a transparent panel having an inspection area; an array of thermochromic liquid crystal (TLC) formations provided on the transparent panel which are operable to change colour in response to a change of temperature; and one or more image capture devices for capturing a colour image of the TLC formations and an area of skin of a target located in the inspection area; the captured colour image being analysed to identify abnormalities in the area of skin.

The invention relates to a method for operating an air conditioning unit (28) of a motor vehicle (10), wherein a control unit (12) causes a sensor unit (20) to scan a body part of a user (26) of the motor vehicle (10) (S3); receives a passenger scan signal from the sensor unit (20) (S4) describing passenger scan data; uses the passenger scan data to define at least one uncovered and perspiring skin area of ​​the body part as the temperature measurement area (S5); and causes the sensor unit (20) to perform a surface temperature measurement of only the defined temperature measurement area using an infrared light-based sensor (S8). The control unit (12) receives a surface temperature signal (S9) from the sensor unit (20) describing the measured surface temperature and compares the measured surface temperature with a predetermined temperature setpoint (S10).In case of a deviation, the control unit (12) determines a target temperature value which leads to a change in the measured surface temperature to a value of the stored temperature setpoint, generates an air conditioning signal (S13) which describes an adjustment of the determined target temperature value by the air conditioning unit (28) and transmits this to the air conditioning unit (28) (S14).

The invention discloses an intelligent face wrinkle removal method and system based on a generative adversarial network. The method comprises the following steps: S1, performing face detection and face key point detection on an original first image; s2, performing face extraction and face correction on the first image to obtain a second image; s3, inputting the second image into a wrinkle segmentation model to obtain a wrinkle mask image, and adopting an improved unet network structure; s4, splicing the second image and the wrinkle mask image to obtain a third image, inputting the third image into the face wrinkle removal model to obtain a fourth image, and adopting an improved generative adversarial network structure; s5, subtracting the fourth image from the second image, and performing inverse affine transformation to obtain a difference graph; s6, adding the difference image into the first image to obtain a fifth image; and S7, protecting a non-face skin area in the fifth image to obtain a final wrinkle removal result image. According to the invention, through combination of precise segmentation and intelligent wrinkle removal technologies, efficient and natural beautifying experience is provided for the user.

The invention discloses a non-contact heart rate detection method based on a three-color channel signal fusion technology, and aims to solve the problems that an existing heart rate detection method is complex in algorithm and high in calculation capability requirement, and measurement errors are caused by illumination variation and motion artifacts. According to the system, a face video is captured through a camera, a region of interest (ROI) is extracted, and non-skin regions are removed by combining skin pixel detection of a YCrCb color space. Then, rPPG signals are extracted through a three-channel signal fusion technology, signal noise reduction is carried out through signal segmentation, mean translation and discrete wavelet transform technologies, and finally the heart rate spectrum is analyzed through fast Fourier transform. Real-time, low-cost and accurate non-contact heart rate detection can be realized, the signal quality and the robustness of a measurement result are remarkably improved, and the method is suitable for various actual scenes.

A method for generating speech includes uploading a reference set of features that were extracted from sensed movements of one or more target regions of skin on faces of one or more reference human subjects in response to words articulated by the subjects and without contacting the one or more target regions. A test set of features is extracted a from the sensed movements of at least one of the target regions of skin on a face of a test subject in response to words articulated silently by the test subject and without contacting the one or more target regions. The extracted test set of features is compared to the reference set of features, and, based on the comparison, a speech output is generated, that includes the articulated words of the test subject.

The utility model discloses a skin beautifying device, and relates to the technical field of beautifying instruments, and the skin beautifying device comprises a controller, an ultrasonic transmitter and a radio frequency transmitter; the controller controls the ultrasonic transmitter and the radio frequency transmitter to work at the same time according to the control signal generated by the operation of the user, so that the ultrasonic transmitter sends ultrasonic energy to the deep skin tissue of an area designated by the user when receiving the control signal, and the deep beautifying effect is achieved; meanwhile, when the radio frequency transmitter receives the control signal, radio frequency energy is transmitted to skin superficial layer tissue of another user designated area, so that the superficial layer beautifying effect is achieved. According to the technical scheme, two beautifying modes can be carried out on the skin area designated by the user in a time-space superposition mode by sliding on the skin, the overall effect is better, meanwhile, radio frequency energy can be fed back to the user in a heat mode, the user is more comfortable in the using process, and the sensory experience of the user is improved.

The invention discloses a phototherapy mask treatment method, device and equipment based on deep learning. Comprising the steps of collecting a face image of a target user, and performing segmentation and classification on the face image based on a deep learning model to generate a visual result; performing statistical analysis on the visualization result to generate a skin analysis result, and determining a target phototherapy mode according to the skin analysis result; and starting a phototherapy mask to treat the target user based on the target phototherapy mode. Personalized analysis can be carried out according to the skin features of the target user through the deep learning model, pertinence is better, different skin areas and features are distinguished through segmentation and classification, a visualization result has higher reference value, and skin problems can be visually presented to the user. Finally, based on a quantized skin analysis result, the most suitable target phototherapy mode can be accurately matched according to specific skin problems and grades of different users, the accuracy and effectiveness of treatment are improved, and the user experience is improved.

The utility model discloses a beauty instrument, which comprises a main control module; the contact detection module is electrically connected with the main control module, and the contact detection module is used for detecting whether a nursing head of the beauty instrument is in contact with the skin or not so as to feed back a corresponding detection signal to the main control module; the timing module is electrically connected with the main control module; the skin care module is electrically connected with the main control module and used for caring the skin area in contact with the care head; the reminding module is electrically connected with the main control module; when the contact detection module detects that the nursing head is in contact with the skin, the main control module controls the skin nursing module to work and controls the timing module to time, and when the timing duration of the timing module reaches a timing threshold value, the main control module controls the reminding module to work. According to the technical scheme provided by the utility model, the hidden danger that the beauty instrument is easy to scald a user due to non-standard operation of the user is effectively eliminated.

A method of skin microstructure texture filtering for facial animation includes obtaining a plurality of one-dimensional (1D) filtered tiles corresponding to a plurality of filter axis angles and a plurality of filter parameters applied to a neutral tile, and at runtime, for each pixel representing a region of human skin, determining a principal direction of deformation, a principal filter parameter corresponding to the principal direction of deformation, and a secondary filter parameter corresponding to a secondary direction of deformation orthogonal to the principal direction of deformation, and selecting a first 1D filtered tile among the plurality of 1D filtered tiles, the first 1D filter tile corresponding to the secondary direction of deformation and the secondary filter parameter, and generating a respective two-dimensional (2D) filtered tile by convolving the first 1D filtered tile with a second 1D filter kernel corresponding to the principal direction of deformation and the principal filter parameter.