76 results about "Dermatoscopes" patented technology

The invention relates to a deep learning based intelligent skin disease auxiliary diagnosis system, which comprises a classifier training unit, a language model unit and an intelligent auxiliary diagnosis unit. The intelligent auxiliary diagnosis unit comprises an image acquisition module, a voice interrogation module, a voice recognition and keyword extraction module, a probability classificationmodel, a RNN condition analysis module and a fusion classifier. The classifier training unit comprises a state diagram training set under a dermatoscope, a state standard database under skin lesion and dermatoscope, a CNN network convolution module and a sampling and classifying module. The language model unit comprises a medical term standard library, a RNN questioning management module, a RNN chief complaint management module and a skin disease medical knowledge base. The auxiliary diagnosis system has advantages that by deep learning for classifying skin lesion images, probable results areinferred, then a pre-installed dermatoscope image and histodiagnosis tag database is retrieved for doctors' reference, and accordingly accuracy in skin disease diagnosis can be greatly improved.

The invention discloses a dermatoscope image segmentation method based on a multi-branch convolutional neural network. The method comprises the following steps of 1, collecting training samples; 2, expanding the image; 3, designing a multi-branch convolutional neural network model; 4, training the multi-branch convolutional network; 5, generating a skin damage distribution probability graph; 6, obtaining a segmentation result. The method has the advantages that the training data set is effectively expanded by using the corresponding image transformation according to the data characteristics ofthe dermatoscope image, so that the network training is effective, and the generalization performance is high; the convolutional neural network comprises a plurality of branches, rich semantic information and detail information are fused, compared with a common network, the skin lesion edge can be better recovered, and a more accurate skin lesion segmentation result is obtained; the method is a full-automatic segmentation scheme, only the dermatoscope image to be segmented needs to be input, the segmentation result of the image can be automatically given through the scheme, the additional processing is not needed, and the method is efficient, simple and convenient.

An apparatus for use in examining an object, such as skin, mucosa and cervical tissues for detecting cancer and precancerous conditions therein. In one embodiment, the apparatus includes a gun-shaped housing having a handle portion and a barrel portion. The front end of the barrel portion is open, and a glass cover is mounted therein. LED's are disposed within the handle portion. A manually-operable switch for controlling actuation of the LED's is accessible on the handle portion. An optical fiber is used to transmit light from the LED's through a first polarizer in the barrel portion and then through the glass cover to illuminate a desired object. Reflected light from the object is passed through a second polarizer, which is adjustably mounted in the barrel portion and which is preferably oriented to pass depolarized light emitted from an illuminated object, and is then imaged by optics onto a CCD detector. The detector is coupled to a wireless transmitter that transmits the output from the detector to a remotely located wireless receiver.

The present invention discloses a method and a system for melanoma image tissue segmentation based on a deep neural network. A deep neural network technology is employed to solve the tissue segmentation problem of dermatoscope images of melanoma, and the method and the system for melanoma image tissue segmentation based on a deep neural network are mainly a medical image analysis processing technology. An improved deep neural network structure to perform modeling, dermatoscope images having segmentation tags are employed to train the model, and the trained model has an ability of suspicious tissues to new dermatoscope images. The method and the system are to locate suspicious areas in the melanoma dermatoscope images and to perform pixel segmentation. The method and the system for melanomaimage tissue segmentation based on the deep neural network employ a new deep learning technology, fully develop the capacity of collection of various hierarchical features of the image data, can be applied to the modeling process, can perform location and segmentation of the suspicious skin tissues and can provide good reference for further analysis by dermatologists.

A disposable tubular end cap for a dermoscope for examining the skin of an animal. The end cap has one end for receiving light from and transmitting light to the dermoscope, a removable calibration target disposed at the other end having optical characteristics similar to a standard skin type, and an identifier disposed on the end cap. The identifier uniquely identifies the end cap and associates it with both data regarding light emitted from the skin of an animal and calibration data derived from the calibration target. Animal tissue may be examined to identify lesions using a plurality of wavelengths and a plurality of polarizations.

A system includes a device (100) for imaging a skin abnormality of a patient, and a web interface (115, 125). The imaging device has a camera (103) recording a plurality of images from locations separated by that distance, thereby obtaining a stereoscopic image of the skin abnormality. The imaging device may be configured as a handheld unit, with the camera a plug-and-play webcam and the device having a USB connection (114) to a computer (110, 120). The web interface (115, 125) links the computer (110, 120) to a web site providing access to storage of the image data. The web interface provides a patient portal for entering information regarding the skin abnormality, and a doctor portal for accessing patient medical history and entering clinical data regarding the skin abnormality. The system may further include a server (160) to receive and analyze the image data, generate 3D stereoscopic images of the skin abnormality, and compute metrics for clinical evaluation of the skin abnormality.

Methods and apparatuses are disclosed for modifying images of skin so as to reduce or enhance the appearance of component pigments, such as melanin and hemoglobin. A diffuse reflectance image of skin, such as a cross-polarized contact dermoscopy image, which conveys information regarding subsurface features of the skin, is processed so as to extract pigment distribution information, which is then used to correct the diffuse reflectance image, such as by reducing the appearance of melanin to allow better visualization of hemoglobin-related structures, such as vasculature. Alternatively, the diffuse reflectance image can be corrected so as to reduce the appearance of hemoglobin to allow better visualization of melanin-related structures.

A medical skin examination device configured to diagnose a skin lesion includes: a first storage unit configured to store an original first skin image related to a dermoscopy structure imaged via a dermoscope; an image conversion unit configured to apply High Dynamic Range (HDR) conversion processing to the first skin image and obtain a second skin image in which the dermoscopy structure is made clear and salient; a second storage unit configured to store the second skin image; and a display control unit configured execute control so as to display at least one of the first skin image and the second skin image.

The invention discloses a melanoma segmentation method based on cavity convolution and multi-scale fusion. The melanoma segmentation method comprises the steps of 1) pre-processing a medical image; 2)constructing a multi-scale aggregation network model with a flexible receptive field; 3) inputting the training set data into the model for training; and 4) performing dermatoscope image lesion region segmentation. According to the channel attention hole convolution module provided by the invention, the receptive field can be adaptively expanded according to image features, tighter context information is obtained, and the problem of insufficient features caused by a fixed receptive field is relieved; an aggregation interaction module can aggregate the features output by a coding layer and thefeatures of an adjacent coding layer to obtain multi-scale information, reduce the semantic difference between the coding layer and the corresponding decoding layer, and suppress noise caused by direct aggregation. According to the method, a dermatoscope image can be segmented accurately, and an auxiliary effect is achieved.

The invention discloses a dermatoscope image segmentation method and a segmentation device thereof, and relates to the technical field of digital image processing, and the segmentation method comprises the steps: adding gray level image information on the basis of an RGB color image of a dermatoscope image, and obtaining a preprocessed dermatoscope image; a lightweight full convolutional neural network is used as a basic framework of an image segmentation model, ResNet50 is used as an encoding stage of the lightweight full convolutional neural network, and in the process, a network structure of ResNet50 and an encoder structure of the lightweight full convolutional neural network are subjected to matching adjustment; aggregating the global information by adopting a dual attention module ina lightweight full convolutional neural network of the image segmentation model to generate a channel attention vector; constructing an adaptive weight loss module; etc. According to the method, thelesion area in the dermatoscope image can be accurately segmented.

The invention discloses a dermatoscope image retrieval method based on end-to-end depth hashing. The dermatoscope image retrieval method comprises the steps of 1, establishing a dermatoscope image database; 2, designing an end-to-end deep hash network model; 3, carrying out network training; 4, extracting a deep hash code, and constructing a retrieval database; And 5, retrieving the dermatoscope image. The method has the advantages that by designing a Res-DenseNet50 deep hashing structure, the fusion capability between high-level features and low-level features is improved, and the loss of information in the transmission process between layers is avoided. And the extracted high-level features have better separability, so that higher retrieval accuracy is achieved. The end-to-end deep hash-based retrieval method is realized. According to the method, the original image is directly learned, and the deep hash code corresponding to the input image can be directly obtained from the penultimate layer of the network, so that the dermatoscope image retrieval process is simplified, and the accumulative error between the front step and the rear step in the traditional retrieval process is avoided.

A dermatoscope or endoscope inspection device which can be calibrated at high accuracy to be able to focus at a certain depth, e.g. below the top surface of the skin. A calibration pattern is provided or can be located at a reference viewing surface of an inspection device such as a dermatoscope or endoscope. It is important for a dermatoscope to know with the best accuracy available at what absolute depth below the top of the skin the device is focused. The dermatoscope or endoscope inspection device includes focusing means and by knowing a relationship between a digital driving level which shifts the focus position of the focusing means and the corresponding absolute change in focus depth, it is possible to know how deep the device is focused in absolute terms below the top of the skin.

The invention relates to a skin confocal microscope suction-type scanning head and a confocal microscope imaging system. The scanning head uses a micro-air pump to extract air in a rubber outer coverand a mobile lens hood moves forward to be completely attached to human skin and then micro-imaging is preformed, so that the phenomenon of rebounding of the scanning head can be prevented in a usingprocess. The confocal microscope imaging system with the scanning head integrates a dermatoscope camera and a microscope; the accurate position of a disease position can be obtained according to images formed by the dermatoscope camera and then an XY motion mechanism drives the mobile lens hood and human skin to perform two-dimensional micro-displacement so that the microscope can be aligned to the disease position accurately; thus, large-range visual light imaging can be performed on skin of a patient and a disease position of the skin can be accurately positioned without secondary operation,and then micro-imaging can be performed on the disease position of the skin.

The invention belongs to the field of domestic health care instruments or medical instruments and in particular discloses a portable multi-spectrum dermatoscope system. The portable multi-spectrum dermatoscope system comprises a dermatoscope body; a liquid crystal display screen, a lens group, a data interface, a magnification factor adjusting button and a photographing button are arranged at the outer part of the dermatoscope body; the liquid crystal display screen and the lens group are integrally designed; an external structure of the lens group comprises a lens and a multi-spectrum light source; the lens group is further internally provided with a data acquisition module and a data processing module; the dermatoscope body is internally provided with a rechargeable battery and a wireless module. The dermatoscope system is convenient to carry and a polarized light imaging principle can be utilized very well; a clear image can be obtained without direct contact with an observed part; meanwhile, different observation results can be obtained when different light sources are used, so that the diagnosis is more accurate; moreover, the portable multi-spectrum dermatoscope system can be connected with mobile equipment, a computer, a display device and the like and can realize remote data sharing through Internet, so that the aim of remote diagnosis or remote consultation is relatively convenient to realize.

In an arrangement for detecting acne, particularly in its earliest stages before any humanly visible or palpable manifestations thereof have emerged, a green fluorescence image of skin illuminated with blue light is captured and processed to detect the presence of microcomedones. After correcting the green fluorescence image for the non-uniform distribution of excitation light on the skin, fluorescent spots are detected therein. The subset of fluorescent spots having an intensity lower than an intensity threshold and an area smaller than an area threshold are selected as representing candidate microcomedones. The subset can be further refined by eliminating fluorescent spots having irregular shapes, are associated with inflammation, or exhibit comedone features. Additional filtering can be applied by selecting those spots whose locations correspond to pore locations. A dermatoscope with a blue illumination source and a green-filtered viewer allows live imaging of skin spots indicative of acne, including microcomedones not otherwise visible.

The invention belongs to the technical field of medical medical equipment, and specifically discloses a medical multispectral dermatoscopy system, which includes a dermatoscope and an integrated design host system, the host system includes a trolley, a host, and a display, and the display is placed on the trolley At the top, the host is placed on the body of the trolley, and the dermatoscope is connected to the host through a data cable. The dermatoscope includes a front lens and a rear handle, and the lens is a multispectral light source lens. The medical multispectral dermoscopy system described in the present invention can freely switch between multispectral modes, compare the changes of skin lesions under different wavelengths of light, and perform differential diagnosis with more accurate diagnosis results; Infrared thermal imaging of damaged parts can detect the temperature changes of skin and accessory tissues before cytological changes in the skin, so that the diagnosis of malignant tumors, skin infections and other lesions can be greatly advanced, and the early detection, early diagnosis and early treatment of tumors is of great significance.

Methods and apparatuses are disclosed for capturing and analyzing images of human hair, particularly of a human scalp. Implementations described for capturing images at multiple locations on the scalp, detecting follicles and hairs, and generating a variety of measurements indicative of the condition of the hair, including the number and density of follicles, hair widths, inter-follicular distances, and the number of hairs per follicular unit, among other possibilities. Measurements can be compared among scalp locations, as well as among sequentially obtained images of the same location. A dermatoscope attachment for contact imaging of the scalp is also disclosed. The attachment may include polarizers enabling cross polarized imaging of the scalp.

The invention provides a dermatoscope capable of detecting bloodstream. The dermatoscope comprises a dermatoscope probe and a processing unit connected to the dermatoscope probe, the dermatoscope probe comprises a light source component, first polarizing film located in front of the light source component and an imaging optical path arranged next to the light source component, the imaging optical path comprises second polarizing film and an imaging component, the imaging component comprises an imaging lens, a filter switch device and a photoelectric detection chip, the light source component comprises the two light sources of a broadband spectrum light source and a laser light source, the broadband spectrum light source is used for the dermatoscope probe to obtain skin morphology information, the laser light source is used for the dermatoscope probe to obtain a laser speckle image to detect skin bloodstream information, and the combination of the skin morphology information and the skin bloodstream information can synchronously provide structure information and function information of skin. The dermatoscope capable of detecting bloodstream not only is applied to skin disease diagnosis, bu also has an important effect on therapeutic effect evaluation.

A standardized, quantitative risk assessment method and apparatus for noninvasive melanoma screening. The apparatus and methods generate a melanoma Q-Score which calculates and displays a probability that a skin lesion is melanoma.

The invention discloses a visual skin wrinkle assessment method and system and belongs to the field of skin detection technology. The method comprises the steps that an image collection device is adopted to shoot face images associated to the same face, and a dermatoscope sends the face images into a cloud server; the cloud server obtains unit normal vectors of all pixel points through photometricstereo processing and obtains surface depth information of all the pixel points through processing to form a face stereo image of the face; and then a pre-trained formed skin wrinkle assessment modelis adopted to make a judgment on the face stereo image so as to obtain skin wrinkle assessment results corresponding to different face positions in the face stereo image, the skin wrinkle assessmentresults are associated to corresponding face positions in a display template to form graphical wrinkle assessment results, and the graphical wrinkle assessment results are output. The visual skin wrinkle assessment method and system have the advantages that a user can view the wrinkle assessment results of different face positions in the face stereo image more directly in a user terminal and thenadopt pertinent skin care.

A one-piece hand-held dermatoscope have two magnifier lenses, a larger rectangular-shaped lens between two and three times magnification power, and a smaller circular lens between eight and 15 times magnification power. A polarizer is position between the lens and a patient's skin. In one embodiment, the polarizer is radial, such that cross-polarization is achieved when the light reflect off the skin and passes through it a second time. In another embodiment, the portion of the polarizer through which the light passes to the skin is linear in a first direction, and the portion through which the light passes back from the skin is linear in a second direction that is perpendicular to the first direction, enabling cross-polarization.

The invention provides a dermatoscope image recognition method and device, and the method comprises the steps: obtaining two dermatoscope images, which are obtained by enabling a same testee to receive dermatoscope examination for melanoma at different time, and contain a same interested target; obtaining a difference image according to the two dermatoscope images; identifying the two dermatoscopeimages and the difference image by using a machine learning model, wherein the model comprises two neural networks, the first neural network is used for carrying out feature extraction on the two dermatoscope images to obtain a first recognition result and determining feature difference data in the feature extraction process, and the second neural network is used for obtaining a second recognition result according to the difference image and the feature difference data; and determining whether the target of interest is an identification result of melanoma according to the first identificationresult and the second identification result.

The invention discloses a dermatoscope image enhancement and classification method based on DCNNs and GANs. The dermatoscope image enhancement and classification method comprises the following steps of S1, constructing and training a U-Net segmentation network; S2, constructing an image synthesis network based on the pix2pixHD; S3, training an image synthesis network; S4, constructing a multi-stage skin lesion classification framework based on DCNNs and GANs; S5, training an SE-Net classification network; S6, obtaining dermatoscope images to be classified; S7, preprocessing the dermatoscope images to be classified; and S8, inputting the preprocessed to-be-classified pictures into a multi-stage skin lesion classification framework for analysis. According to the invention, segmentation, synthesis and classification of dermatoscope images can be realized; according to the method, a U-Net and pix2pixHD method is adopted, the influence of useless background information and insufficient training data on the classification task performance is reduced, and the method has good practicability.

Disclosed is a content-based image retrieval (CBIR) system and related methods that serve as a diagnostic aid for diagnosing whether a dermoscopic image correlates to a skin cancer type. Systems and methods according to aspects of the invention use as a reference a set of images of pathologically confirmed benign or malignant past cases from a collection of different classes that are of high similarity to the unknown new case in question, along with their diagnostic profiles. Systems and methods according to aspects of the invention predict what class of skin cancer is associated with a particular patient skin lesion, and may be employed as a diagnostic aid for general practitioners and dermatologists.

The invention discloses a technical method for treating leucoderma based on hair follicle melanocyte stem cell transplantation. The technical method includes the following steps of extraction of hairfollicles, wherein a hair follicle unit is extracted by using an FUE technology; separation of the hair follicles, wherein individual follicalar units are separated from the hair follicle unit under an electron microscope; in-vitro culture of the hair follicles, wherein the extracted and separated individual follicalar units are cultured in a special culture medium for use to improve the survivalrate of the hair follicles; inactivation of the hair follicles, wherein the hair follicles before transplantation are inactivated with the help of a dermatoscope and a hair follicle inactivating needle; transplanting of the hair follicles, wherein a special planting needle is used for planting the inactivated hair follicles in a specific area of leukasmus. Through the hair follicle in-vitro culture technology, the FUE technology is used for extracting and separating the individual follicalar units, then the individual follicalar units are placed in the special culture medium for culture, and the inactivation of the hair follicles is achieved through the hair follicle inactivation technology. After an operation, the hair follicles only turn black and do not grow hair, the point-like multiple hair follicles can restore original color through precise planting, and the purpose of fast removing the leukasmus is achieved.

Hyperspectral dermoscopy images obtained in N wavelengths in the 350 nm to 950 nm range with a hyperspectral imaging camera are processed to obtain imaging biomarkers having a spectral dependence. Machine learning is applied to the imaging biomarkers to generate a diagnostic classification.

The invention relates to a dermatoscope which comprises an observation system and an illumination system. The illumination system comprises at least one luminous body and a rotary plate capable of rotating around the optical axis of the observation system. The rotary plate is provided with multiple windows. When the rotary plate rotates and is switched in place, luminous light of at least one luminous body illuminates the work face of the dermatoscope through at least one window. The dermatoscope is compact in structure, multifunctional, stable in performance and convenient to assemble, adjust, use and maintain.

The invention discloses a skin CT large-field-of-view image splicing method and system with high reliability and fault tolerance, and the method comprises the steps: 1), manually determining the starting point and size of a splicing region, setting M rows * N columns of skin CT images needing to be spliced according to the shape of a grid, and guaranteeing that the left and right adjacent images and the upper and lower adjacent images have an overlapping region; and 2), enabling an objective lens of a dermatoscope to sequentially scan each grid in the first row from left to right from the starting point of the splicing area, then changing to the next row and performing reverse movement, repeating the steps, completing scanning of all grids along the S-shaped track, and performing splicing while obtaining images. According to the method, a fault-tolerant mechanism is introduced, so that the situation that overall splicing fails due to local image splicing errors in the large-view-field splicing process is avoided, an error area is limited in a local small range, and the robustness and efficiency of large-view-field image splicing are improved.

The invention provides a dermatoscope image recognition method based on StyleGANs and decision fusion. The method comprises: firstly, utilizing StyleGANs to carry out data enhancement, and then utilizing a plurality of intervention training convolutional neural networks to carry out feature learning on an image; and then putting a plurality of convolutional neural networks into a plurality of blocks, calculating the softmax average value array of the convolutional neural networks in each block, and selecting the maximum value in the array for voting; and finally, summarizing the voting resultsof the plurality of blocks, and selecting the maximum value of the voting results as a classification prediction result. According to the method, the factors of large intra-class difference, small inter-class difference, insufficient data sets and uneven distribution of the data sets under the condition of various dermatoscope images are fully considered, and the dermatoscope images can be accurately recognized.

An analysis method and a diagnostic device, enabling one to determine whether a longitudinal melanonychia is caused by a malignant melanoma or a benign nevus by correcting color variation in a dermoscopic image through standardization of color balance without depending on an imaging device or an operator; and a computer program for allowing a computer to function as the diagnostic device. Proposed is a structure including: an image reading step of reading a color image of a longitudinal melanonychia or an affected skin site of a subject as a digital color image; an image processing step involving an image size conversion step of converting the whole size of the digital color image into a preset size through pixel size conversion, and a region of interest (ROI)-extraction step of extracting an ROI required for the diagnosis from the digital color image; a chromatic adaptation transformation step of controlling the color balance of the digital color image data through chromatic adaptation transformation; and a discrimination index (DI) calculation step of determining a DI value using the image after the chromatic adaptation transformation.