32 results about "Fat distribution" patented technology

The invention relates to the technical field of rehabilitation medicine, in particular to a body carving slimming method for fat metabolism based on bioelectricity feedback and acupoint stimulation. The invention provides a body carving slimming method based on bioelectricity feedback and acupoint stimulation. The body carving slimming method comprises the four steps of obtaining, processing, acupoint stimulation and outputting. Bioelectricity signals and weight data of body parts of a user are collected through a bioelectricity and weight detection device. The muscle activity state and fat distribution are analyzed, a posture improvement value is calculated, and a personalized body carving training scheme is generated. In an acupoint stimulation link, electrical stimulation is performed on a specific acupoint according to the scheme, bioelectricity feedback is monitored in real time, and stimulation parameters are dynamically adjusted. And generating a personalized report containing the posture change and the training effect evaluation, and providing suggestions to the user. According to the method, the effect, safety and individuation are remarkably improved, and a new direction is opened up for development of the body carving and slimming field.

The invention discloses a coronary artery CTA epicardial fat automatic extraction and quantification method based on artificial intelligence, and aims to improve the accuracy and efficiency of fat extraction. The method comprises the following steps: preprocessing a coronary artery CTA image to enhance data quality; a segmentation model based on U-Net is constructed, and accurate segmentation of the heart structure is achieved; the epicardial adipose tissues in the segmented regions are automatically extracted in combination with a set CT value threshold value; quantifying the fat volume by adopting a voxel counting mode, and analyzing the density of the fat volume; a three-dimensional visual model is further generated, and the spatial relation between fat distribution and the heart structure is displayed. According to the method, the effect is verified on multiple data sets, it is shown that the method is superior to an existing method in the aspects of fat extraction precision, volume and density evaluation and model robustness, and the method has good application prospects.

This invention discloses a method for intelligent and accurate sampling inspection of beef balls based on AI visual recognition, belonging to the field of intelligent food detection technology. It includes: S1: Constructing defect data: A graph neural network is constructed using the microscopic morphology and 3D surface morphology of beef ball samples. Simultaneously, virtual beef ball defect samples are generated through multiphysics modeling, and the physical authenticity of the virtual beef ball defect samples is verified using the graph neural network; S2: Dual-channel adversarial training: The beef ball model is identified through structural and material channels, and the loss function of the beef ball model is determined; S3: Quality detection: Based on the composite loss function, the sampling rate of the beef balls is set, and a quality assessment system is constructed. This invention identifies the geometric deformation of beef balls through the structural channel and analyzes the fat distribution texture of beef balls through the material channel, thereby synergistically reducing the false judgment rate.

The invention relates to a beef surface pollution identification method and system based on machine vision, and relates to the field of computer vision, and the method comprises the steps: carrying out the identification of hidden pollution pixel points of a beef image through machine learning, and obtaining the distribution of the hidden pixel points; setting an adjacent pixel point retrieval specification according to the fat distribution data on the surface of the beef; and according to an adjacent pixel point retrieval specification, carrying out adjacent pixel point retrieval clustering on a plurality of hidden pixel points in the hidden pixel point distribution to obtain clustered hidden pixel point distribution, and carrying out pollution treatment screening to obtain a pollution identification result. The method can solve the technical problem that the traditional method is difficult to accurately distinguish the beef surface fat texture and the mould, so that the mould pollution identification accuracy and reliability are insufficient; by setting a dynamic adjacent pixel point retrieval range for pollution feature screening, misjudgment caused by texture similarity of mould and fat can be effectively reduced, and the precision, accuracy and reliability of mould pollution identification are remarkably improved.

The invention discloses a chicken body fat rate phenotype determination system and a chicken selection method. The chicken body fat rate phenotype determination system comprises an eight-electrode system, a multi-channel signal receiving and transmitting module, a processor module and a power supply module, the eight-electrode system is used for sending excitation current and receiving potential difference signals, and a local closed-loop measurement loop can be formed on the same limb; the multi-channel signal receiving and transmitting module is used for controlling excitation and measurement among the electrode groups and realizing biological impedance data acquisition in multiple directions; the processor module is used for constructing data models of the upper limbs, the trunk and the lower limbs of chicken body fat distribution according to the multi-channel impedance data; the power supply module is connected with the processor module and the eight-electrode system and provides power for the system. The method adopts the bioelectrical impedance value to measure and detect the body fat rate of the live chicken, and is high in detection precision, convenient to operate, high in adaptability and convenient to popularize and apply in the field of poultry breeding.

The invention discloses a pig meat quality intelligent detection system and method, and the method comprises the steps: collecting a surface image of a snowflake pork piece, screening a boundary pixel combination located on a fat and muscle boundary according to a pixel gray value, and obtaining all muscle regions in a gray image region; calculating a fat area proportion and a fat distribution uniformity coefficient of the surface image; constructing a CNN convolutional neural network, training the CNN convolutional neural network, and outputting a convergent CNN convolutional neural network; the method comprises the following steps: acquiring surface images of snowflake pork produced on a snowflake pork production line in real time, inputting the surface images into a convergent CNN convolutional neural network, outputting a fat distribution uniformity coefficient and a fat area proportion, and evaluating the quality of the produced snowflake pork. The system comprises an image acquisition module, an image analysis and processing module and a display module. The method provides support for high-efficiency quality evaluation on the snowflake pork production line, and can realize continuous and rapid snowflake pork quality evaluation on the snowflake pork production line.

Present disclosure describes techniques for predicting diabetes risk in patients. The techniques include the step of monitoring a plurality of patient-specific characteristics comprising, at least one physiological parameter, one behavioral indicator, and one visual representation of the patient. The method further comprises extracting, using a first artificial intelligence (AI) model, a stress level of the patient based at least on behavioral indicators, historical lifestyle data, and sensor-derived physiological parameters. The method then include extracting, using a second AI model, a body mass index (BMI) or fat distribution patterns based at least on silhouette images and weight of the patient. The method finally includes predicting, using a third AI model, a blood sugar level or diabetes risk score of the patient based on outputs from the first and second AI models and the monitored characteristics.

The invention relates to an application of an Sdccag3 gene in preparation of a weight-reducing medicine for regulating obesity phenotype and glycolipid metabolism. The Sdccag3 gene is used as an action target to be applied to preparation or screening of the weight-reducing medicine for regulating obesity phenotype and glycolipid metabolism, and the nucleotide sequence of the Sdccag3 gene is as shown in SEQ ID No.1. The invention firstly verifies the influence of Sdccag3 overexpression on the weight, fat size and fat distribution of the obese mouse, and finds that the overexpression Sdccag3 can significantly improve the weight, fat size and fat distribution of the obese mouse. Then, it is found that specific overexpression of Sdccag3 in adipose tissue in a mouse can significantly inhibit increase of blood fat level, reduce fat volume of an obese mouse, reduce serum triglyceride, cholesterol and low-density lipoprotein cholesterol levels of the obese mouse, improve glucose intolerance and improve insulin sensitivity, and the Sdccag3 can be used for treating obesity. The fat phenotype and glycolipid metabolism are effectively regulated and controlled, the weight losing effect is achieved, and the composition can be used for preparing lipid-lowering and weight-losing medicines.

The utility model relates to leg shaping pants with soft supports, which comprise a pants body and a plurality of first soft supports distributed at positions corresponding to leg muscular tissues. The first soft support comprises at least two subsections with different tensile rigidities, or at least two subareas with different tensile rigidities, or at least two subsections with different flexural rigidities. According to the soft support provided by the utility model, the mechanical properties are set to be different in subsection or subarea, and different supporting effects or shaping effects can be provided at different positions; compared with a traditional soft support, the soft support provided by the invention can adapt to deformation, support or shaping requirements of different positions. According to the leg shaping pants, a designer can add the soft support at any position of the pants body according to actual requirements, or design specific segments and partitions of the soft support according to actual conditions of leg muscle distribution and fat distribution of a user, so that the effects of shaping, supporting, deformation, crease resistance, attractiveness, resilience, prolonging of the service life and the like at different positions are achieved.

The invention discloses an intelligent and accurate beef ball spot check method based on AI visual identification, and relates to the technical field of intelligent food detection. Comprising the following steps: S1, constructing defect data: constructing a graph neural network through the microstructure and 3D surface topography of a beef ball sample, generating a virtual beef ball defect sample through multi-physics field modeling, and verifying the physical authenticity of the virtual beef ball defect sample through the graph neural network; s2, dual-channel confrontation training: identifying the beef ball model through a structure channel and a material channel, and determining a loss function of the beef ball model; and S3, quality detection: according to the composite loss function, setting a sampling inspection rate of the beef balls, and constructing a quality evaluation system. The geometric deformation of the beef balls is identified through the structure channel, and the fat distribution texture of the beef balls is analyzed through the material channel, so that the misjudgment rate can be synergistically reduced.

The invention relates to the field of polypeptides, in particular to an adipose tissue targeted MRI (Magnetic Resonance Imaging) developing agent. The invention provides an adipose tissue targeted MRI (Magnetic Resonance Imaging) developing agent, which is characterized in that the MRI developing agent has the following structure: [X]-L-P, wherein P is a polypeptide, and the polypeptide is selected from a group consisting of SEQ ID NOs: 1 to 15; l is an attachment joint, and the attachment joint comprises amino acid and / or amino acid derivatives; [X] is a paramagnetic metal complex, and the paramagnetic metal complex is composed of a chelating agent and paramagnetic metal ions. The MRI developing agent provided by the invention not only can accurately and specifically target and locate adipose tissues of a living body, but also can visualize visceral fat, so that the fat distribution condition of the living body is displayed.

The invention provides a sample grading method and device and electronic equipment. The target sample is graded by means of cooperation of a multi-mode imaging mode, namely, the X-ray image obtained based on X-ray scanning of the target sample and the at least one sample surface image, collected based on the at least one data collection module, of the surface of the target sample, so that the grading accuracy of the target sample is improved. Furthermore, the grading evaluation results of different surface areas in the target sample, such as the fat distribution characteristics of one piece of meat, are visually displayed, so that the grading evaluation results of different surface areas in the target sample, such as the fat distribution characteristics of one piece of meat, are visually displayed; and thus, finer quality evaluation of target samples such as meat is realized.

The utility model relates to a face shaping headgear with a soft support, which comprises a headgear body and a first soft support covering two cheeks and a jaw of a face, and the first soft support comprises at least two subsections with different tensile rigidities, or at least two subareas with different tensile rigidities, or at least two subsections with different flexural rigidities. According to the soft support provided by the utility model, the mechanical properties are set to be different in subsection or subarea, and different supporting effects or shaping effects can be provided at different positions; compared with a traditional soft support, the soft support provided by the invention can adapt to deformation, support or shaping requirements of different positions. A designer of the face shaping headgear can add the soft support at any position of the headgear according to actual requirements, or design specific segments and subareas of the soft support according to actual conditions of facial muscle distribution and fat distribution of a user, so that the effects of shaping, supporting, deformation, wrinkle resistance, attractiveness, resilience, prolonging of service life and the like at different positions are achieved.

The application discloses a fat injection needle assembly for facial fat transplantation, and relates to the technical field of medical devices, which comprises a needle cylinder, a needle seat is arranged at the bottom of the needle cylinder; a needle body is detachably connected to the end of the needle seat away from the needle cylinder, the needle body has a hollow inner cavity, and the end away from the needle seat is a closed end; fat outlet micro-holes are arranged on the wall body close to the closed end of the needle body, the fat outlet micro-holes are distributed along the circumference of the needle body, and the outlet direction of each fat outlet micro-hole and the axial direction of the needle body form a non-zero angle, so that the fat particles are scattered in the radial direction or the circumferential direction of the needle body when being discharged from the fat outlet micro-holes; a fat placement cylinder is arranged in the hollow structure inside the needle cylinder and in the interior of the needle cylinder, and the fat placement cylinder is communicated with the needle cylinder; the radial scattering of the fat outlet micro-holes is matched with the anti-blocking, anti-overflow and limiting structures, the local accumulation risk in the fat injection process is reduced, and the uniformity of fat distribution is improved.

The invention provides a fat transplantation survival rate prediction system based on transfer learning and biomechanical simulation. Comprising an image data acquisition module, a fat distribution density prediction module, a cell integrity information acquisition module, a cell survival rate prediction module, a temperature image acquisition module, a blood supply state prediction module, a model fusion module, a transfer learning module and a survival rate output module. According to the system, by integrating multi-source data of preoperative MRI images, intraoperative pressure sensing and postoperative infrared thermal imaging, three prediction models of fat distribution density, cell survival rate and blood supply state are established and fused, animal experiment data knowledge is migrated to a human body for application in combination with a transfer learning technology, accurate prediction of the survival rate after fat transplantation is achieved, and the survival rate of fat transplantation is accurately predicted. The prediction accuracy rate reaches 85% or above, and scientific decision support is provided for clinic.

The invention discloses a stable oil-carrying amino acid surfactant composition and a preparation method thereof, the composition can improve the stability of an oil-containing personal care product, can construct a stable liquid crystal structure, and can enhance the system adaptability and anti-interference capability through the cooperation of a plurality of amino acid surfactants, so that the stability of the oil-containing personal care product is improved. A stable and fine emulsion structure can still be formed under severe storage conditions, so that the grease is uniformly dispersed and has high emulsifying performance, grease molecules are wrapped by a liquid crystal structure, and grease distribution and release can be optimized by matching with different fatty acids; according to the present invention, the inorganic salt-free or extremely low inorganic salt design is adopted, the low-irritation amino acid surfactant is adopted as the main material, the inorganic salt-free or extremely low inorganic salt content is controlled, the environmental protection problem caused by the desalination process is avoided, the application range of the formula is expanded, and the formula is flexible and has wide adaptability.

The invention relates to a fat distribution determination method and device, computer equipment and a storage medium. The method comprises the following steps: acquiring an in-phase image and an anti-phase image of a detection object; obtaining a water distribution image and a fat distribution image of the detection object according to the in-phase image and the reverse-phase image; determining fat parameters of the detection object according to the water distribution image and the fat distribution image; and obtaining a fat distribution result of the detection object according to the fat parameters. By adopting the method, the fat distribution of the detected object can be accurately determined.

The invention relates to the technical field of food processing, in particular to a non-fermentation whole cheese processing technology which comprises the steps of whole milk pretreatment, direct heating curdling, curdling cutting and whey discharging, high-temperature quick setting and high-pressure squeezing, forming and air drying, manual cutting and packaging and the like. By optimizing the technological process and adopting a raw milk heating fast acid curd method and a high-pressure squeezing technology, the risk of microbial contamination caused by fermentation is avoided, the whey separation efficiency and the fat distribution uniformity are improved, and natural nutritional ingredients in the raw materials are reserved; the stability of the milk fat is remarkably improved, the surface of a finished product is fresh and cool, no greasy feeling exists, and the product quality and consumer acceptability are improved.

The utility model belongs to the field of underpants, and discloses three-dimensional shaping underpants which comprise an underpants body, and the underpants body is provided with an abdomen shaping area and a hip shaping area. The fabric of the belly shaping area is of a breast raising weave structure or a false rib weave structure formed by weaving warp yarns and weft yarns; the hip shaping area comprises a first hip bearing area or a second hip bearing area, the first hip bearing area is of a smooth transition X-shaped structure so as to mainly bear the hip from the inner side of the hip, and the second hip bearing area is of a smooth transition W-shaped structure so as to mainly bear the hip from the lower portion of the hip. The first hip bearing area is of a plain weave structure or a mesh weave structure formed by weaving warp yarn and weft yarn, and the fabric of the second hip bearing area is of a breast raising weave structure or a false rib weave structure formed by weaving warp yarn and weft yarn. Based on fat distribution and pressure conditions, different textile weave structures are adopted for supporting and shaping, so that shaping is more accurate, and the problem that a single material is insufficient in elasticity or uneven in elasticity distribution is solved.

Method and device for water-fat separation of image, computer apparatus, and computer-readable storage medium. The method includes: obtaining plurality of echo images of a target object; obtaining an initial water and fat distribution image of the target object; determining a first error phasor candidate and a second error phasor candidate, the first error phasor candidate being used to characterize an error phasor of each element corresponding to water occupying a major constituent, and the second error phasor candidate being used to characterize an error phasor of each element corresponding to fat occupying a major constituent; determining an initial-guess of error phasor corresponding to each element in the plurality of echo images among the first error phasor candidate and the second error phasor candidate based on the initial water and fat distribution image; determining an optimal error phasor based on the initial-guess of the error phasor; and acquiring a water image and a fat image of the target object from the plurality of echo images according to the optimal error phasor.

The utility model discloses a pair of multifunctional leggings, which belongs to the technical field of underwear and comprises a trouser waist. The trouser body is arranged at the bottom of the trouser waist, the trouser body is provided with a first area and second areas, the two second areas are arranged in the width direction of the first area, the first area corresponds to the buttocks of the human body, and the second areas correspond to the crotch of the human body; the two trouser legs are arranged at the bottom of the trouser body; the crotch enlarging pad is arranged on the side, facing the human skin, of the pants body, and at least part of the projection of the crotch enlarging pad in the thickness direction is located in the second area. According to the multifunctional leggings designed by the utility model, the crotch enlarging pad fills up the recess of the crotch caused by muscle relaxation or fat distribution change, recovers a more natural and attractive curve, and can help a wearer to feel better and be willing to try different clothes styles by improving the appearance of the crotch.

The technical scheme of the utility model discloses a 3D perforated cotton mold cup and a gathering comfortable bra with the 3D perforated cotton mold cup. The mold cup is a 3D three-dimensional mold cup formed by integral molding of perforated cotton, and air holes are distributed on the surface and inside of the mold cup for circulating air. The inner side of the mold cup is concave inward and a hollow part for wrapping the wearer's chest is formed corresponding to the middle and lower part of the mold cup. The bottom edge of the hollow part extends in a spoon-shaped curve. The mold cup is provided with a support part formed integrally with the mold cup and arranged corresponding to the wearer's breast root below the hollow part, and the support part extends in an arc along the bottom edge of the mold cup. The perforated cotton mold cup can not only use its own 3D three-dimensional structure to guide the distribution of the wearer's chest fat and provide stable gathering and supporting strength through the hollow part of the mold cup and the support part below the hollow part, but also the perforated cotton cloth is provided with air holes, so that the 3D perforated cotton mold cup and the bra with the 3D perforated cotton mold cup have both gathering effect and wearing comfort, and long-term wearing is helpful for chest correction and breast health.

The invention provides a krill oil soft capsule as well as a preparation method and application thereof, and belongs to the technical field of development of marine resource health-care food, the krill oil soft capsule is prepared by adopting a specific formula and a specific process, the activity of components in a product can be effectively reserved, all the components have a synergistic effect, and the effect of improving the quality of the product is achieved. The soft capsule provided by the invention can significantly improve atherosclerosis related pathological states, effectively reduce serum total cholesterol, triglyceride and low density lipoprotein cholesterol levels, reduce atherosclerosis indexes, significantly inhibit aortic plaque formation and liver lipid deposition, and maintain stable weight and fat distribution. The product can be used as a health-care food for preventing and assisting in improving atherosclerosis.

Provided is a method and apparatus for measuring fat content using a computed tomography (CT) image. The fat content measurement apparatus trains a fat prediction model by using learning data including a CT image or noise image for learning and generates a fat distribution image to be used for fat content measurement by the fat prediction model having completed learning upon receiving a CT image for diagnosis.

The present application provides a sample grading method, apparatus and electronic device. The present application grades a target sample by means of a multimodal imaging method, that is, an X-ray image obtained by scanning the target sample based on X-rays and at least one sample surface image of the surface of the target sample collected by at least one data acquisition module, so as to improve the accuracy of grading the target sample. Further, in this embodiment, by visually displaying the grading evaluation results of different surface regions in the target sample, such as the fat distribution characteristics of a piece of meat, the grading evaluation results of different surface regions in the target sample, such as the fat distribution characteristics of a piece of meat, are intuitively displayed, and then a more refined quality evaluation of the target sample, such as meat, is realized.

The invention relates to the field of polypeptides, in particular to a PET developing agent for positioning adipose tissue. The invention provides a PET (Polyethylene Terephthalate) developing agent for positioning adipose tissue, which is characterized in that the PET developing agent comprises polypeptide labeled by radionuclide, and the polypeptide is selected from the group consisting of SEQ ID NOs: 1-15; the radionuclide comprises one or more of < 18 > F, < 64 > Cu and < 68 > Ga. The PET developing agent provided by the invention not only can accurately and specifically target and locate adipose tissues of an organism, but also can visualize subcutaneous fat and visceral fat, so that the fat distribution condition of the organism is displayed.

The present application relates to a kind of beef surface pollution identification method and system based on machine vision, it is related to computer vision field, including: using machine learning to carry out implicit pollution pixel point identification to beef image, obtain implicit pixel point distribution;According to the fat distribution data of beef surface, set adjacent pixel point search specification;According to adjacent pixel point search specification, carry out adjacent pixel point search clustering to multiple implicit pixel points in implicit pixel point distribution, obtain clustering implicit pixel point distribution, carry out pollution processing screening, obtain pollution identification result.The present application can solve the technical problems that traditional method is difficult to accurately distinguish beef surface fat texture and mould, leading to the accuracy and reliability of insufficient mould pollution identification;By setting dynamic adjacent pixel point search range to carry out pollution feature screening, can effectively reduce the misjudgment due to the similarity of mould and fat texture, significantly improve the precision, accuracy and reliability of mould pollution identification.

The invention relates to the technical field of feed processing, and provides a preparation method of high-fat and high-emulsibility corn enzymolysis protein for feeds, which comprises the following steps: S1, weighing corn protein raw materials, adding water, uniformly stirring, heating, adjusting the pH value to 8.5-9.5, then adding alkaline protease, and carrying out enzymolysis at a certain temperature for a period of time to obtain corn protein enzymolysis liquid; s2, fat is added into the corn protein enzymatic hydrolysate treated in the step S1, stirring continues for a period of time, and turbid liquid is obtained; s3, homogenizing the turbid liquid treated in the step S2 through a high-pressure homogenizer to obtain emulsion with finer particles; and S4, carrying out spray drying on the emulsion obtained in the step S3 to obtain the high-fat and high-emulsibility corn enzymolysis protein. The preparation method disclosed by the invention can be used for solving the problems of excessive external fat addition, processing difficulty, non-uniform fat distribution, fat leakage and the like in the feed processing process.

The invention relates to the technical field of breast augmentation, in particular to a multi-layer three-dimensional fat breast augmentation method which comprises the following steps: S1, pre-operation planning and preparation: deeply communicating with a patient to know the breast augmentation expectation, medical history and the like, and carrying out comprehensive body and breast specialized examination and imaging examination to provide a basis for an operation scheme; s2, fat acquisition and treatment: selecting a donor area according to fat distribution of a patient, evaluating an available amount, marking a suction range, and cleaning the donor area for skin preparation; the three layers under pectoralis major, breast and subcutaneous are respectively filled with a proper amount of refined and pure fat, so that the fat can be more uniformly paved on each layer. The uniform distribution provides a wider nutrient acquisition way for fat cells, the contact area of fat and surrounding tissues is increased, so that the survival rate of fat is remarkably improved, compared with a traditional method, the phenomena of fat absorption and liquefaction are greatly reduced, large nodules after filling are avoided, and the breast enlarging effect is more durable and stable.