231 results about "Skin lesion" patented technology

The invention provides a medical image segmentation method and system based on spatial detail enhanced vision, and relates to the technical field of image processing. The method comprises the following steps: performing initial feature mapping on an input and preprocessed medical image to obtain an embedded feature map; the embedded feature map is input into an encoder for feature extraction, and multi-scale features are obtained; the encoder comprises a plurality of encoding stages, and the number of channels is doubled and the spatial resolution is halved through down-sampling operation between the encoding stages; the multi-scale features are subjected to up-sampling and spatial enhancement reconstruction step by step through a decoder, and a high-precision segmentation result is generated; wherein the decoder comprises a plurality of decoding stages, the decoding stages correspond to the encoding stages, and feature fusion is carried out between the corresponding stages of the encoder and the decoder through jump connection. According to the method, the boundary description precision and the segmentation robustness of the low-contrast image can be improved without increasing the linear complexity, and the method is suitable for medical image segmentation scenes of skin lesions, gastrointestinal polyps and the like.

The invention provides a skin lesion auxiliary detection method and system based on multi-modal information fusion, and belongs to the technical field of computer vision and application. The method comprises the following steps: firstly, acquiring and constructing bimodal data including a dermatoscope image and a text of a patient, and preprocessing the data; secondly, respectively adopting an improved convolutional neural network and a text coding model, and extracting deep and high-dimensional features from the skin disease image and the self-described text of the patient; afterwards, an improved symmetric gating cross attention fusion module is constructed, fine-grained interaction and alignment between visual and text features are realized through a bidirectional cross attention mechanism, and a gating unit is utilized to adaptively adjust a fusion weight; and finally, inputting the deeply fused multi-modal feature vector into a classifier to obtain a confidence score of each skin lesion type so as to provide reference for dermatologists. According to the method, the diagnosis accuracy, robustness and interpretability are synergistically improved, and the method has great clinical application value.

A method of operation of a compute system includes: receiving a patient image including a skin lesion and a fixed ruler, generating a correlated ruler by segmenting the fixed ruler including translating pixel-to-millimeter to the patient image, calculating a skin lesion area by segmenting the skin lesion, and generating a skin lesion output report, including an image of the skin lesion, the correlated ruler and the skin lesion area, for displaying on a device.

The invention provides a skin lesion image segmentation method and system based on multi-scale deformable aggregation, and the method comprises the steps: obtaining a skin lesion image data set, dividing the data set into a training set and a test set, constructing an improved U-shaped segmentation network model, optimizing model parameters through training, applying the trained model to the test set, and obtaining a skin lesion image segmentation result. And generating a high-precision segmented image. According to the model, an innovative convolution-parallel vision Mangbar module is adopted in an encoder, and extraction and fusion of local details and global long-range dependency of an image are realized through cooperation of a CNN and a state space model; a deformable convolution attention gate is put forward in a decoder, a key area is accurately focused by using a deformable convolution adaptive lesion shape, and cross-level feature fusion and multi-scale refining are realized. Through the multi-scale deformable aggregation mechanism, the segmentation precision and robustness of the model to complex and various skin lesions are significantly improved, and reliable assistance is provided for clinical diagnosis.

The invention relates to the technical field of skin lesion area reconstruction, in particular to a skin lesion area reconstruction system based on multi-modal image fusion. The system comprises a deep multi-scale feature extraction module, a skin thermal anomaly feature extraction module, a hemodynamic feature extraction module, a depth and boundary feature extraction module, a skin surface feature extraction module, a fluorescence intensity distribution and morphological feature extraction module, a first feature fusion module, a second feature fusion module and a lesion area reconstruction module. According to the method, appearance, heat, blood flow, structure and surface features are extracted from the multi-modal data, then the multi-modal image data are integrated, finally, comprehensive representation and reconstruction of skin lesion appearance, function and structure information are achieved according to the synergistic effect of the multi-modal information, and the accuracy and clinical reference value of lesion area reconstruction are effectively improved.

The invention relates to a medical image segmentation system and method based on context and frequency guidance and a storage medium, and the system employs an encoder-decoder architecture, and integrates three core modules: a visual state space module which captures global context information with linear complexity based on a selective state space model; the frequency-guided representation module is used for explicitly separating and enhancing structure and boundary characteristics through frequency domain transformation and complex weight modulation; and the multi-scale adaptive context aggregation module is used for integrating multi-scale semantics through parallel multi-branch convolution and dual Top-K sparse attention and focusing a key region. According to the method, the technical problems that global modeling and boundary details are difficult to consider, the calculation complexity is high and the adaptability to multi-scale targets is poor in the prior art are solved, the segmentation precision and the boundary description accuracy are remarkably improved in various medical image segmentation tasks such as heart MRI, polyp, skin lesion and pathological sections, and the medical image segmentation efficiency is improved. And meanwhile, the calculation efficiency is ensured.

The invention discloses a skin lesion segmentation method and system based on dual-path perception multi-stage fusion, and relates to the technical field of medical image processing, and the method comprises the steps: carrying out the block division of a skin image, inputting into an encoder, and filtering a key lesion region through employing a region sparse attention mechanism; performing down-sampling on the feature map by using a block merging operation, and constructing a multi-scale feature pyramid; skin image features are processed by using a dual-path sensing multi-stage fusion network, deepest features generated by an encoder are processed by a spatial frequency dual-path cascade sensing module, and two-stage space-frequency collaborative optimization is executed; the method comprises the following steps: establishing jump connection between an encoder and a corresponding decoder through a space channel double-path parallel sensing module, recovering spatial resolution through block expansion operation in combination with modulated encoder characteristics, and generating a pixel-level lesion probability graph. According to the method, the context sensing capability across the space domain and the frequency domain is remarkably enhanced, and an accurate and detailed skin lesion segmentation result is obtained.

The invention discloses a hydrogel dressing for treating atopic dermatitis and a preparation method and application thereof, and belongs to the technical field of skin medical materials. The dressing is prepared by taking a glycerol / water / ethanol ternary mixed solvent as a dissolving system, dissolving polyvinyl alcohol, tannic acid and aluminum trichloride to construct a polymer skeleton matrix, and then adding traditional Chinese medicine active ingredients. The preparation does not need complex temperature control curing, the ternary solvent can realize uniform dissolution and stable dispersion of the active ingredients, the effective ingredients are prevented from being damaged by high temperature, the encapsulation efficiency of the traditional Chinese medicine extract is more than 90%, and the medicine can be slowly released for 72 hours. The dressing has a multi-target anti-inflammatory effect, can reduce the level of TNF-alpha at a skin lesion and promote proliferation of keratinocytes, is excellent in tensile and torsional stability, and can be attached to the skin for a long time in a dynamic environment. The preparation method is simple in process, controllable in raw material cost, high in production efficiency, suitable for large-scale production, good in dressing biocompatibility, high in safety, suitable for treatment of atopic dermatitis of different severity degrees and large in clinical transformation potential.

The invention discloses a skin lesion image segmentation method, which belongs to the field of medical image processing and segmentation, and comprises the following steps: preprocessing a collected skin lesion image data set, dividing the skin lesion image data set into a training set and a test set, and carrying out data enhancement processing on the training set; constructing an edge optimization segmentation model fusing double attention and dynamic multi-scale; training a segmentation model of the skin lesion image; importing a test set into the model; and generating a segmentation result. Feature extraction is realized through a U-shaped encoder decoder structure; through a multi-scale void feature fusion module, the extraction of image multi-scale features is enhanced; through a double attention module, the tiny focus effect is enhanced; and the integrity of focus information is reserved through an edge perception cross-scale feature fusion module. The method is used for improving the segmentation effect of the model on the skin lesion image.

Presented herein are systems and methods for detecting basal-cell carcinoma (BCC) in biomedical images of skin lesions. A computing system may identify, for a first subject at risk of BCC in a first lesion on a region of an epidermis: (i) a first biomedical image of an outer layer of the region on the epidermis of the first subject acquired in accordance with dermoscopy, and (ii) a plurality of second biomedical images of at least one inner layer in the region on the epidermis of the first subject acquired in accordance with reflection confocal microscopy (RCM). The computing system may apply the first biomedical image and the plurality of second biomedical images to a model architecture. The computing system may generate, based on applying to the model architecture, a score indicating a likelihood of BCC in the first lesion.

The invention provides a dermatoscope image segmentation method, system and device based on Mama and a medium, and belongs to the technical field of image processing and computer vision, and the method comprises the steps: obtaining an original dermatoscope image, carrying out the preprocessing of the original dermatoscope image, and obtaining a preprocessed dermatoscope image set; acquiring a skin lesion label image corresponding to the original dermatoscope image, pairing the preprocessed dermatoscope image with the corresponding skin lesion label image, constructing a dermatoscope image data set with a label, and dividing the dermatoscope image data set into a dermatoscope image training set and a dermatoscope image test set; a neural network model based on Mama is constructed; feeding the dermatoscope image training set into a neural network model in batches for training to obtain a trained neural network model; and inputting a to-be-segmented original dermatoscope image into the trained neural network model to obtain a corresponding focus region segmentation result. According to the method, the accuracy of skin lesion segmentation is remarkably improved.

The application provides a skin lesion three-dimensional reconstruction system based on a flexible electrode array. The system is characterized by comprising a measuring belt (1), an excitation generator (3), a signal processing module (4), a microprocessor (5) and an imaging module (6). The application can be used for detecting uneven skin lesion areas and constructing three-dimensional shapes of the lesions, and can be widely used in the field of uneven human subcutaneous tissue health detection.

The present application relates to polypeptides and their use in repairing mucosal damage or skin damage, the polypeptides of the present application have no homology with known polypeptides, and can stably exist in vivo and in vitro, have the effect of regulating stem cell proliferation and differentiation to repair mucosal damage or skin damage; and relate to the use of the novel polypeptides to repair mucosal damage or skin damage by regulating stem cell proliferation and differentiation, and the use for preventing, alleviating or treating gastrointestinal diseases.

The utility model relates to a hydropathic compress instrument for skin disease nursing. The hydropathic compress instrument comprises a bridle and an atomization main body, a barrel shell is mounted in the middle of the length of the bridle, a dividing disc is fixedly arranged in the barrel shell with an open structure, and the barrel shell is divided into a containing space and an atomizing space communicated with the open structure by the dividing disc; the bridle is bound on a body part of a patient, the open structure is buckled on a skin lesion part area to drive the atomization main body and the spray gun to start working, the atomization main body atomizes a solution containing a medicament into gas, the gas is sprayed to the skin lesion part area, and then skin disease wet compress nursing is achieved. By means of the structure, the situation that a spray gun is manually held by hand is avoided, a fixed structure is adopted to replace the situation that the spray gun is manually held by hand, an atomized solution can be accurately sprayed to a skin lesion part, the solution is evenly distributed, and the situation that the solution in an edge area is insufficient possibly due to manual holding is avoided.

The invention discloses a pharmaceutical composition for treating psoriasis and application thereof. The active ingredient of the composition is a combination of Mongolian medicine seven-ingredient powder soup and a horse bone extracting solution, wherein the Mongolian medicine seven-ingredient powder is prepared from radix sophorae flavescentis, elecampane, fructus chebulae, szechwan chinaberry fruit, fructus gardeniae, herba violae and rhizoma picrorhizae according to a specific proportion. The preparation method of the composition mainly comprises the following steps: respectively preparing Mongolian medicine seven-component powder soup and horse bone extracting solution, and then mixing and decocting the Mongolian medicine seven-component powder soup and the horse bone extracting solution. Through the synergistic interaction of the Mongolian medicine seven-ingredient powder decoction and the horse bone extracting solution, the composition shows a treatment effect superior to that of independent use of each component in an animal model, and can remarkably relieve psoriasis-like skin lesion and down-regulate the expression of related inflammatory factors. The invention provides an application of the composition in preparation of a medicine for treating psoriasis.

The invention provides an oral medicine formula for treating psoriasis, and relates to the field of traditional Chinese medicine formulas. The oral medicine for treating psoriasis is prepared from the following raw materials by weight: 10 g of astragalus membranaceus, 50 g of rhizoma smilacis glabrae, 10 g of salvia miltiorrhiza, 10 g of cassia twig, 10 g of cicada slough, 10 g of ligusticum wallichii, 30 g of angelica sinensis and 10 g of honey-fried licorice root. Salvia miltiorrhiza, ligusticum wallichii, angelica sinensis and other medicines have the effects of promoting blood circulation to remove blood stasis, can improve the blood circulation state of skin and promote repair of skin lesions, and have a certain curative effect on blood stasis type psoriasis patients; cassia twig and cicada slough have the effects of dispelling wind and arresting itching, can relieve the symptom of skin itch, and improve the life quality of patients; astragalus membranaceus, angelica sinensis and honey-fried licorice root have the effects of reinforcing qi and nourishing blood, can improve the overall physique of a patient, enhance the immunity of the body and contribute to disease recovery, the clinical effective rate reaches 70% or above, one treatment course lasts for three months, and the cure rate can reach 40% or above.

The invention belongs to the technical field of dermatoscope image analysis, and relates to a pathological space diagram modeling system and method for skin lesion intelligent diagnosis, the system comprises four parallel deployment visual representation learning and topological structure modeling, the modeling comprises a saliency map embedding layer and a plurality of pathological space diagram blocks, the pathological space graph block is sequentially composed of a pathological feature point digger, a layered graph connector and a geometric distribution learner; the method comprises the following steps: constructing a multi-scale saliency block embedding layer to extract initial visual representation, introducing a pathological feature point digger to realize intelligent identification of sparse key pathological points, constructing a hierarchical graph connector to organize a multi-scale topological relation, realizing hierarchical topological reasoning and vector distillation of a geometric distribution learner, and constructing a geometric distribution learner. Defining an attention fusion mechanism and a classification head to realize topological guidance diagnosis; according to the method, the defects in the aspects of structural modeling, calculation distribution, graph representation and the like in the prior art are overcome, and the diagnosis accuracy, robustness and clinical interpretability are remarkably improved.

This invention relates to a vulnerary multifunctional composition, based on unripe coffee cherries (peel, mucilage, beans and silverskin), seed extract of Trigonella foenum-graecum, with one or more tissue-inducing molecules derived from the secondary metabolites of both plants. The unexpected and surprising ability of this new composition to solve the problems of chronic non-healing wounds addresses a long felt unmet need in the medical arts. Through a multifaceted approach, it combats microbial infections, reduces chronic inflammation, counters oxidative stress, enhances immune responses, promotes angiogenesis, regulates protease activity, stimulates collagen deposition, increases growth factor availability, facilitates cell migration, and prevents persistent infections. These novel integrated therapies represent a breakthrough in addressing macroscopic wound healing while targeting the underlying microscale mechanisms. This invention also relates to methods for preparing, using, and administering the multifunctional composition for timely healing in mammals with various skin lesions.

The application provides a skin lesion image segmentation method and system based on multi-scale deformable aggregation, including: acquiring a skin lesion image dataset, dividing the dataset into a training set and a test set, constructing an improved U-shaped segmentation network model, optimizing the model parameters through training, applying the trained model to the test set, and generating high-precision segmentation images. Among them, the model adopts an innovative convolution-parallel visual mamba module in the encoder, cooperates with CNN and state space model, realizes extraction and fusion of local details and global long-range dependence of the image; a deformable convolution attention gate is proposed in the decoder, which uses deformable convolution to adaptively focus on key areas and realize cross-level feature fusion and multi-scale refinement. Through the above multi-scale deformable aggregation mechanism, the segmentation accuracy and robustness of the model for complex and diverse skin lesions are significantly improved, providing reliable assistance for clinical diagnosis.

This invention relates to a phototherapy device for skin diseases, comprising a base unit, several adjustment units, several mounting units, several phototherapy units, and several covering units. Its advantages include: the base unit provides a mounting foundation, allowing for placement in homes or community medical institutions, overcoming the location limitations of whole-body phototherapy devices that can only be used in specific hospital departments; the sliding cooperation between the adjustment units and the base unit enables the horizontal reciprocating movement of the mounting units, allowing adjustment of the phototherapy unit's position according to the patient's needs; and the detachable connection between the phototherapy units and the mounting units facilitates the replacement of phototherapy units of different sizes according to the area of ​​skin lesions. Patients can complete treatment independently at home without frequent trips to the hospital, reducing time costs and the burden of treatment cycles. It also avoids the embarrassment of full-body exposure in public places like hospitals, alleviating situations where patients interrupt treatment due to privacy concerns.

The application belongs to the technical field of traditional Chinese medicines, and particularly relates to a traditional Chinese medicine composition for treating psoriasis, a preparation method and application thereof. The raw material composition comprises, in mass parts, 10-30 parts of schizonepeta, 10-30 parts of moxa leaf, and 10-30 parts of rhizoma alocasia. Animal experiments show that the traditional Chinese medicine composition can promote the repair of skin barrier function and reduce the skin lesion symptoms of psoriasis-like mice, which indicates that the traditional Chinese medicine composition has a good therapeutic effect on psoriasis.

The invention discloses a herpes zoster skin lesion staging evaluation method and system based on AI image recognition, and relates to the technical field of herpes zoster skin lesion staging evaluation, and the method comprises the following steps: collecting herpes zoster skin lesion image data continuously recorded in multiple periods, synchronously embedding a time identifier in the collection process, and carrying out the time identification; recording the shooting moment, the illumination state and the shooting angle information of each frame of image in a unified manner to form an original image sequence; and based on the original image sequence, according to the progressive sequence of the time identifiers, performing adaptive sorting adjustment on the time intervals between the adjacent frames. According to the method, a stable skin lesion time evolution track is constructed through time identification and a continuous processing flow, so that staging reverse judgment caused by frame order disorder is avoided, and the continuity and reliability of herpes zoster skin lesion staging evaluation are improved; and meanwhile, color, area and texture changes are uniformly incorporated into natural time rhythm constraints, so that a staging result better conforms to a clinical disease course rule, and the safety of remote follow-up visit and intelligent evaluation is improved.

The invention relates to the technical field of medicines, and particularly discloses a polypeptide Loni-P extracted from traditional Chinese medicine honeysuckle, and the amino acid sequence of the polypeptide Loni-P is SEQ ID No.1. The polypeptide can be prepared from honeysuckle through the steps of ultrasonication, enzymolysis, purification and the like. Experiments show that the inhibition rate of Loni-P to malassezia under the concentration of 2 mu g / mL reaches 86 + / -5.29%, which is similar to that of positive control ketoconazole (92 + / -9.17%). The invention further provides a medicated bath component containing Loni-P. The medicated bath component is composed of polypeptide, beta-cyclodextrin, chitosan, fumaric acid, sodium hydroxide and other auxiliary materials and is matched with 200 L of medicated bath water. Clinical experiments show that the medicated bath can remarkably relieve itching, skin lesion area and shape of a chronic eczema patient, and after 30 days of treatment, the score of an experimental group is reduced from 7.93 to 4.0 (a control group has no remarkable change). The polypeptide is natural in source and high in safety, and a new strategy is provided for eczema treatment.

This invention provides a skin condition detection method and system based on image recognition. The method includes acquiring a skin image to be analyzed and related textual metadata; inputting the preprocessed image into a trained skin lesion segmentation model and outputting the segmentation result of the lesion region; automatically extracting the size information and at least one morphological quantitative feature of the skin lesion based on the segmentation result, and integrating the size information and the morphological quantitative feature as supplementary features into the textual metadata to form enhanced metadata; assigning appropriate weights to the image features and the textual features based on the mutual information between the image features and the textual features, and dynamically weighting and concatenating them to form a fused feature vector; inputting the fused feature vector into a classifier and outputting the classification result of the skin condition, which significantly improves the model's ability to distinguish similar skin diseases, especially early malignant lesions, and improves the classification accuracy.

The application belongs to the technical field of medical image processing, and particularly relates to a human limb skin disease area evaluation method, device and system. The method comprises the following steps: collecting multi-view images of a target limb, adjacent view angles of the multi-view images containing overlapping areas; generating a three-dimensional point cloud of the target limb based on the multi-view images; constructing a cylindrical model with a radius changing along a limb axis based on the three-dimensional point cloud; projecting the multi-view images to the cylindrical model, and selecting pixels projected to the same position of the model based on an evaluation function, so that the model surface is attached with image texture; and unfolding the cylindrical model with the texture into a two-dimensional plane image for evaluating the skin disease area. The application realizes high-precision and high-fidelity lesion area evaluation without expensive three-dimensional scanning equipment.

This invention relates to the field of asiaticoside technology, and discloses asiaticoside liposome compositions, preparation methods, and applications. Specifically, based on molecular design principles, monoprotonated tertiary amine permeation enhancers and diprotonated tertiary amine permeation enhancers are synthesized. Using egg yolk lecithin, cholesterol, monoprotonated or diprotonated tertiary amine permeation enhancers, and asiaticoside as raw materials, asiaticoside liposome compositions are prepared by thin-film dispersion. The liposome composition exhibits a transdermal permeability of >90% after 48 hours, demonstrating excellent transdermal performance, and also possesses excellent encapsulation and drug loading properties, making it suitable for preparing gel formulations for treating skin lesions.

The utility model provides equipment for treating private parts of patients with skin diseases with skin lesions, and solves the problems that existing equipment is unstable in fixation, poor in air permeability and insufficient in comfort level. The device comprises a breast support and a scrotum support, the breast support adopts a half-bowl-shaped hollow supporting part and is composed of an inner layer and an outer layer, air holes are arranged in a staggered mode, and the ventilation effect is ensured. Connecting buckles are arranged on the two sides of the supporting part and used for being connected with shoulder straps, the tightness of the shoulder straps is adjusted through sliding sleeves and sliding buckles, and equipment stability is guaranteed. The scrotum support is composed of bent wedge-shaped separation ribs, the front side is arc-shaped, the rear side is linear, and the scrotum support has good supporting and air permeability. The fixing belt is fixed through the waist buckle and the hook-and-loop fastener and can be flexibly adjusted. The breast support comprises a left supporting part and a right supporting part which are connected through a middle belt to achieve stable supporting. The device design has good adaptability, air permeability and comfort, and is suitable for long-term nursing of skin disease patients.

This invention discloses a medical image segmentation method based on enhanced attention. The method acquires a medical image, preprocesses it, and inputs it into an encoder to output a multi-scale feature map of the medical image. The encoder includes N cascaded multi-dimensional attention modules. Each multi-dimensional attention module extracts multi-scale features through dual-channel convolution and residual connections, and performs feature recalibration using an attention enhancement module. The output multi-scale feature map is then fused by a multi-scale dilated fusion attention module to obtain the feature map output by the encoder. The feature map output by the encoder is input to the decoder, where it is combined with high-resolution feature maps of the corresponding levels passed from the encoder via skip connections. Through progressive upsampling and feature fusion, a reconstructed feature map is obtained. The reconstructed feature map output by the decoder is used to generate a medical image segmentation mask through 1×1 convolution and a sigmoid activation function to complete the segmentation of diseased tissues. This invention significantly improves the boundary segmentation accuracy for knee joints, breast tumors, and skin lesions.

The application relates to a skin lesion area rapid detection and segmentation method, which comprises the following steps: given an input X element R C×H×W , which becomes Y element R C×HW after remodeling operation, and 4 times expanded attention map Att element R 4C×HW is obtained by calculating the relevance of the query vector and the memory unit; given an input feature map X and a randomly initialized learnable tensor P; the size of the tensor P is adjusted by using bilinear interpolation to match the size of the X, and a depth separable convolution is used on the P; the feature map is uniformly cut into four parts X1, X2, X3 and X4 along the channel dimension. The application improves and introduces Hadamard product attention module to extract multi-angle pathological features of different shaft groupings of the feature map, fuses multi-scale context information, aggregates cross-dimension information, improves the representation ability of the model, designs a new boundary loss function, and puts the boundary information into the model learning process, encourages the model to pay attention to the boundary details, is excellent in various segmentation performance indexes, and can accurately extract a lesion area.