671 results about "Skin lesion" patented technology

A method of treating dermal lesions caused by envenomation comprising applying a therapeutically effective amount of an immune response modifier compound selected from the group consisting of imidazoquinoline amines, imidazopyridine amines, 6,7-fused cycloalkylimidazopyridine amines, imidazonaphthyridine amines, tetrahydroimidazonaphthyridine amines, oxazolopyridine amines, oxazoloquinoline amines, thiazolopyridine amines, thiazoloquinoline amines and 1,2-bridged imidazoquinoline amines to the site of the lesion is disclosed.

Provided herein are portable imaging systems, for example, a digital processor-implemented system for the identification and / or classification of an object of interest on a body, such as a human or plant body. The systems comprise a hand-held imaging device, such as a smart device, and a library of algorithms or modules that can be implemented thereon to process the imaged object, extract representative features therefrom and classify the object based on the representative features. Also provided are methods for the identifying or classifying an object of interest on a body that utilize the algorithms and an automated portable system configured to implement the same.

New or significantly changed skin lesions are detected by providing digital baseline image data of an area of a subject's skin by placing a calibration piece on the area and then positioning a digital camera to frame the area within a field of view of the camera and digitally photographing the area to produce a digital baseline image of the area. The digital baseline image is downloaded from the camera to a computer, which digitally filters the baseline image to produce a partially transparent baseline image scaled to fit over a viewfinder display of the camera. The filtered baseline image is printed on a transparent sheet to produce template. Substantially later, a calibration piece is placed on the area, and the template is placed over the viewfinder display of the camera. The camera is positioned to frame that area within the field of view so as to align a live image of the area with the baseline image on the template. The area is photographed to produce a digital current image thereof. The current image is downloaded to the computer, which is operated to alternately display the aligned current image data and the baseline image data to allow visual identification of lesions which changed enough in the “alternating image comparison display” to identify a new or significantly growing lesion.

An apparatus and method for determining a characteristic of a selected skin lesion. A capture device produces data representing an image of an object. A processing device processes the data to derive a three-dimensional model of the skin lesion, which is stored in a database. A reporting device indicates at least one specific property of the selected skin lesion. The processing device determines a change in at least one specific property of the skin lesion by comparing the three-dimensional model with at least one previously derived three-dimensional model that is stored in the database.

A multispectral nevoscope that uses specific wavelengths in the visible and infrared spectrum of electromagnetic radiation to transilluminate a skin-lesion or a biological tissue or specimen for imaging and maps multispectral 2-dimensional images into 3-dimensional virtual space for providing 3-D distributions of pre-defined parameters representing the characteristic properties (such as melanin, hemoglobin and deoxyhemoglobin, etc.) of a skin lesion. Methods are disclosed for analyzing and using the characteristic distributions of specific parameters for detection and management of skin-cancers, or characterization of a biological tissue or specimen.

The present invention provides a dermoscopy image automatic segmentation method based on a full convolutional neural network. The method comprises the following four steps: 1: obtaining of dermoscopy images and true value graphs; 2: performing structure design of a full convolutional neural network; 3: performing design of feature fusion and a per-pixel segmentation method; and 4: performing network training and segmentation. According to the steps mentioned above, an end-to-end depth convolutional neural network is obtained through training to perform accurate segmentation of the dermoscopy images and allow a small area skin lesion area to be effective so as to solve actual problems that the skin lesion area segmentation is not good to influence the subsequent diagnosis accuracy in the dermatology computer auxiliary diagnosis system.

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.

Methods for diagnosing skin lesions are disclosed. Generally, the method include topically administering an IRM compound to a treatment area for a period of time and in an amount effective to cause a visible change in the appearance of a skin lesion including, in some cases, causing subclinical lesions to become visible. Suitable IRM compounds include agonists of one or more TLRs.

Methods for diagnosing skin lesions are disclosed. Generally, the method include topically administering an IRM compound to a treatment area for a period of time and in an amount effective to cause a visible change in the appearance of a skin lesion including, in some cases, causing subclinical lesions to become visible. Suitable IRM compounds include agonists of one or more TLRs.

A thermal imaging system includes a data processing system and a geometrical scanning system constructed to communicate with the data processing system. The geometrical scanning system is adapted to scan at least a section of a surface of a subject under observation. The thermal imaging system also includes an infrared imaging system constructed to communicate with the data processing system. The infrared imaging system is adapted to image at least a portion of the section of the surface of the subject under observation. The data processing system is configured to receive data from the geometrical scanning system and to construct a surface map of the section of the surface of the subject under observation and to identify geometrical markers on the surface map based on the data from the geometrical scanning system. The data processing system is also configured to receive data from the infrared imaging system and to construct a thermal map of the portion of the section of the surface, to identify thermal markers on the thermal map based on the data from the infrared imaging system, and to register the thermal map to the surface map based on a correspondence between at least some of the geometrical and thermal markers. The data processor is configured to correct temperatures of the thermal map based on the surface map subsequent to the registering.

The invention relates to the technical field of cosmetics, and discloses a nona-oligopeptide composition for skin repairing and application thereof. The nona-oligopeptide composition is prepared from, by weight, 1-30 parts of palmitoyl-tripeptide-1, 1-30 parts of tripeptide-1 copper, 1-50 parts of palmitoyl-tripeptide, 1-30 parts of carnosine, 1-30 parts of acetyl tetrapeptide-5, 1-30 parts of palmitoyl-tetrapeptide-7, 0.1-30 parts of acetyl hexapeptide-8, 0.1-30 parts of nonapeptide-1, and 1-30 parts of nisin. The nona-oligopeptide composition has the effect of a cell factor sample, affects the growth of skin flora, is applied to dermatology and skin beautifying, and has the effects of repairing skin lesion, adjusting metabolism and inhibiting skin condition conditioned pathogen growth.

A regulated heat source is described that can be applied to a skin lesion, such as pustular-form eruption or localized abscess, in order to accelerate the death of invading bacteria, fungi or viral particles, or to assist in the breakdown of a skin irritant and thereby speed the recovery process.

A device and method to non-invasively identify pathological skin lesions. The method and device detect and identify of different kinds of skin nevi, tumors, lesions and cancers (namely, melanoma) by combined analyses of visible and infra-red optical signals based on integral and spectral regimes for detection and imaging leading earlier warning and treatment of potentially dangerous conditions.

The invention discloses a deep-learning-based image identification method of the melanoma of a skin cancer. The method comprises: establishing a skin lesion dermatoscope image database; carrying out data preprocessing and quality assessment and screening; carrying out cascaded connection of deep convolution neural networks, and introducing transfer learning and a classifier. At a training stage, enhancement or screening is carried out on original data; and after inputting of positive and negative samples, sample expansion and overfitting prevention are carried out. At the preprocessing stage,data enhancement is added, cascaded connection of two deep convolution neural networks is carried out; transfer learning of existing pre-trained features at a natural image to an identification network is carried out; and then classification prediction is carried out by using the classifier and fine adjustment of network parameters is carried out based on network convergence and prediction situations. Therefore, the accuracy of skin lesion classification is improved; the restriction of manual feature selection is avoided; the adaptability is improved; and thus the deep-learning-based image identification method has the certain significance in a medical skin disease image analysis.

Methods and devices for the treatment of skin lesions resulting from bacterial, fungal or viral infections or from exposure to irritants are disclosed. The invention relates methods and devices for delivering a controlled dose of thermal energy to the infected or irritated tissue and thereby speed the recovery process.

A non-invasive tool for skin disease diagnosis would be a useful clinical adjunct. The purpose of this study was to determine whether visible / near-infrared spectroscopy can be used to non-invasively characterize skin diseases. In-vivo visible- and near-infrared spectra (400-2500 nm) of skin neoplasms (actinic keratoses, basal cell carcinomata, banal common acquired melanocytic nevi, dysplastic melanocytic nevi, actinic lentigines and seborrheic keratoses) were collected by placing a fiber optic probe on the skin. Paired t-tests, repeated measures analysis of variance and linear discriminant analysis were used to determine whether significant spectral differences existed and whether spectra could be classified according to lesion type. Paired t-tests showed significant differences (p<0.05) between normal skin and skin lesions in several areas of the visible / near-infrared spectrum. In addition, significant differences were found between the lesion groups by analysis of variance. Linear discriminant analysis classified spectra from benign lesions compared to pre-malignant or malignant lesions with high accuracy. Visible / near-infrared spectroscopy is a promising non-invasive technique for the screening of skin diseases.

This disclosure relates to an in vivo treatment of a skin lesion of a mammal comprising application of electrical energy to the skin lesion in a form of electrical pulses. At least one electrical pulse is applied. The pulse duration may be at least 1 nanosecond at the full-width-half-maximum. This treatment may prevent at least growth of the lesion.

An ultrasonic instrument for treating the lesion of gynopathy and dermatopathy is composed of a cooling water tank, a therapeutic gun, a host containing control unit, power supply and power amplifier, a front panel with indicating circuit, and a circulating pump for the said cooling water tank. The ultrasonic wave with good focusing and penetrating performance act on the lesion tissue to fastly raise its temp., resulting in improved edema and microcirculation. Its advantages are high curative effect and no damage to skin.

This invention discloses isolated short peptides comprising the amino acid sequence Cys-Glu-Phe-His (CEFH) and analogs thereof as well as compositions comprising CEFH peptides and analogs thereof. The CEFH peptides disclosed herein are effective in mediating the denitration of 3-nitrotyrosines (3-NT) in cellular proteins thereby preventing tissue damage associated with excess nitric oxide (NO) and its reactive species. The CEFH peptides disclosed herein are useful in the treatment of ischemia / reperfusion (I / R) injury of various tissues (e.g., I / R injury of heart muscle associated with heart attack or cardiac surgery, I / R injury of brain tissue associated with stroke, I / R injury of liver tissue, skeletal muscles, etc.), septic shock, anaphylactic shock, neurodegenerative diseases (e.g., Alzheimer's and Parkinson's diseases), neuronal injury, atherosclerosis, diabetes, multiple sclerosis, autoimmune uveitis, pulmonary fibrosis, oobliterative bronchiolitis, bronchopulmonary dysplasia (BPD), amyotrophic lateral sclerosis (ALS), sepsis, inflammatory bowel disease, arthritis, allograft rejection, autoimmune myocarditis, myocardial inflammation, pulmonary granulomatous inflammation, influenza- or HSV-induced pneumonia, chronic cerebral vasospasm, allergic encephalomyelitis, central nervous system (CNS) inflammation, Heliobacterium pylori gastritis, necrotizing entrerocolitis, celliac disease, peritonitis, early prosthesis failure, inclusion body myositis, preeclamptic pregnancies, skin lesions with anaphylactoid purpura, nephrosclerosis, ileitis, leishmaniasis, cancer, and related disorders.

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 automated skin lesion assessment system may automatically assess a suspect skin lesion. An electronic image library may contain diagnosed skin lesion image data representative of images of a plurality of diagnosed skin lesions and, for each, a diagnosis of the skin lesion. An image capture system may capture an image of the suspect skin lesion. A computer processing system may compare the image of the suspect skin lesion with the diagnosed skin lesion image data and, based on this comparison, identify one or more diagnosed skin lesions which match the suspect skin lesion. A user interface may report the diagnoses of the diagnosed skin lesions that match the image of the suspect skin lesion.

The invention aims to solve problems of poor effect, small quantity of training samples, large difference among samples of a traditional extracted feature resorting method due to large difficulty in melanoma skin lesion segmentation and provides a multi-scale deep learning recognition system based on expansion and convolution. The system includes performing data enhancement and normalization processing on training samples and training an extracted expansion and convolution based multi-scale feature learning neural network, performing multi-threshold segmentation based on an obtained predictionprobability map, and thus implementing segmentation of a melanoma skin lesion image. Finally, the segmentation accuracy is improved.

A method and system can provide a way for a person to objectively screen himself or herself for increased skin cancer risks using ABCD parameters in conjunction with a digital photograph and a computer. A digital photograph of a skin lesion can be obtained and the lesion can be segmented from the image. Next, several features of the lesion can be measured and these measurements can be displayed graphically in a manner which is understandable to a user who may not have any medical training.

Serum compositions for application to skin are described which contain an amniotic fluid extract in combination with embryonic stem cells. Formulations containing the serum composition are also described. The serum compositions and formulations may be applied to skin for treatment of symptoms of aging, wounds, burns, scars or other skin lesions. Methods of preparing the serum compositions and formulations are also disclosed.