69 results about "Liver lesion" patented technology

Computed Tomography (CT) and Magnetic Resonance Imaging (MRI) are commonly used to assess patients with known or suspected pathologies of the lungs and liver. In particular, identification and quantification of possibly malignant regions identified in these high-resolution images is essential for accurate and timely diagnosis. However, careful quantitative assessment of lung and liver lesions is tedious and time consuming. This disclosure describes an automated end-to-end pipeline for accurate lesion detection and segmentation.

A method and system for automatically detecting liver lesions in medical image data, such as 3D CT images, is disclosed. A liver region is segmented in a 3D image. Liver lesion center candidates are detected in the segmented liver region. Lesion candidates are segmented corresponding to the liver lesion center candidates, and lesions are detected from the segmented lesion candidates using learning based verification.

The invention relates to the field of medical image processing, in particular to a method for automatically identifying a liver tumor type in an ultrasonic image. The method can provide auxiliary diagnosis when a doctor diagnoses a liver lesion according to a CEUS medical image, wherein the auxiliary diagnosis comprises the process of giving out a lesion identification result, the time when the lesion is relatively remarkable and a position where the lesion is relatively remarkable. The method specifically comprises: representing a CEUS image with a plurality of regions of interest (ROI); distinguishing different lesions by expressions and changes of the ROI in time and space; and representing a space-time relationship among the ROI by establishing models in time and space at the same time, wherein the models can determine relatively proper ROI and related parameters of the models according to existing CEUS lesion samples with an iterative learning method. After a sample is given out, the proper ROI can be determined by removing part of improper ROI in advance and a fast search method, and reference diagnosis is given out for the lesion.

The invention discloses a liver CT image multi-lesion classification method based on sample generation and transfer learning. The method mainly solves the problem that an existing method is not high in liver multi-lesion detection performance. The implementation scheme is as follows: dividing a data set; respectively constructing a liver organ segmentation network and a liver lesion detection network; based on the deep convolution generative adversarial network, constructing a liver cyst sample generation network and a liver hemangioma sample generation network, and respectively generating newliver cyst and liver hemangioma samples; constructing a liver lesion classification network; subjecting a liver CT image to be detected firstly to organ segmentation by using a liver organ segmentation network, then subjecting a segmentation result to lesion detection by using a liver lesion detection network, and finally classifying detected lesions by using a liver lesion classification network. According to the invention, imbalance of different types of sample sizes is relieved, the lesion classification performance is improved, and the method can be used for positioning and qualifying various lesions such as liver cancer, liver cyst and hepatic hemangioma existing in the liver CT image.

A method for segmenting a first object from a bounding object within a digital image identifies pixels between first and second endpoint pixels. A volume of interest is defined spanning at least a portion of the object. Pixels within the volume of interest are partitioned into a first subset of pixels that are neither the first object nor bounding object pixels and second subset of pixels that are not contained in the first subset. A spatially varying two-phase segmentation process segments the first object from the bounding object within the second subset of pixels according to the location of each subject pixel within the second subset relative to pixels in the first subset of pixels. The first object segmentation is refined according to the subject pixel location relative to the segmented bounding object and to the first subset of pixels. A segmented image is formed according to the refined segmentation.

The invention relates to an automatic segmentation method for an abdominal CT liver lesion image based on a three-stage cascade network. The method comprises the following steps: S1, acquiring three-dimensional abdominal liver CT image data; S2, preprocessing and standardizing the obtained three-dimensional abdominal liver CT image data; S3, inputting the three-dimensional abdominal liver CT imagedata after preprocessing and data standardization into AuxResUnet liver image segmentation model, and then taking 3D maximum connected region from the obtained three-dimensional abdominal liver CT image data segmentation result to exclude false positive region, so as to obtain liver VOI; S4, adopting the segmentation result of the three-dimensional abdominal liver CT image data obtained by S3 asa mask of the CT liver image data to cover the liver VOI obtain by S3; S5, inputting the covered liver VOI into AuxResUnet liver image lesion segmentation model for lesion segmentation, and obtainingthe liver image lesion segmentation result. The image segmentation method provided by the invention can realize fast and accurate segmentation of liver and liver pathological changes.

The present invention discloses a new medicine composition for curing hepatic diseases and its preparation method. It is formed from (by weight portion) 400-10000 portions of astragalus root, 200-6000 portions of salvia root and 10-200 portions of kurarinone, and also can be made up by using 2-200 portions of astragalus total saponin or astragalus polysaccharide, 2-200 portions of salvia total phenolic acid and 10-200 portions of kurarinone. Said medicine composition can be made into various dosage forms of oral preparation, injection and others. Said medicine composition can be used for curing diseases of viral hepatitis, medicamentous liver lesion, fatty liver and alcoholic hepatitis, etc.

The invention provides gynostemma pentaphylla liver protecting and nourishing health-care tea which is characterized by comprising the following raw materials in parts by weight: 10-50 parts of gynostemma pentaphylla, 10-20 parts of glossy privet fruits, 10-20 parts of isatis roots, 10-20 parts of radix curcumae, 10-20 parts of salviae miltiorrhizae, 10-20 parts of poria cocos, 10-20 parts of notopterygium roots, 10-20 parts of capillary artemisia, 10-20 parts of radices trichosanthis, 10-20 parts of Scutellaria baicalensis, 10-20 parts of radix paeoniae alba, 10-20 parts of jasmine, 10-20 parts of loranthus parasiticus and 10-20 parts of schisandra chinensis, wherein gynostemma pentaphylla has the functions of reducing blood fat, blood pressure and blood sugar, calming, hypnotizing, resisting stress, ulcer and fatigue, prolonging lifetime of cells, enhancing appetite, enhancing resistance, promoting bowel movement, calming panting and suppressing cough, eliminating haemorrhoids, reducing weight, treating deficiency syndrome, inhibiting formation of gall-stone, preventing and treating side effects of glucocorticoid, preventing aging and the like. The tea has very high health-care effect to treat various liver diseases such as chronic hepatitis, forepart hepetocirrhosis, fatty liver, alcoholic liver and medicamentous liver lesion, and is strong in pertinence.

The invention discloses a liver tumor recognition method based on a self-supervised dense convolutional neural network. The method comprises the following steps: obtaining a liver slice data set from a magnetic resonance image of a patient, carrying out the segmentation of the slice data set, training a constructed dense convolutional network, enabling the trained dense convolutional network to serve as a coding module, constructing a self-supervised learning network, and carrying out the recognition of a liver tumor through the self-supervised learning network. Through dense connection of the coding modules, a tumor region of a part of an image in a slice data set is manually marked, then the whole slice data set is segmented, segmented image blocks are adopted to train a self-supervised learning network, and the trained self-supervised learning network is adopted to automatically identify tumors in the image. The dense convolutional neural network based on self-supervision is used for liver tumor recognition, a puzzle task is set as a self-supervision upstream training task, useful representations are learned from a large number of images which are not subjected to medical labeling and are used for learning training of downstream target tasks, and therefore the purposes of automatically expanding training data samples and improving the recognition efficiency are achieved. The dependence on expert experience and historical data is reduced, and the recognition accuracy of the liver lesion region is improved.

The invention relates to a functional feed, in particular to the functional feed for preventing and treating a white liver lesion of micropterus salmoides, and a preparation method thereof. The feed comprises, by weight percentage, 15-25% of fish meal, 20-35% of chicken powder, 16-22% of soybean meal, 8-15% of flour, 4-8% of squid extractum, 1-2% of calcium dihydrogen phosphate, 1-2% of a multi-vitamin premix, 1-2% of a multi-mineral premix, 2-4% of fish oil, 1-2% of soybean oil, 1-2% of phosphatide oil, 2-7% of corn protein powder, 0.2-0.5% of pennisetum sinese herb extract, 0.1-0.5% of mulberry leaf fermentation liquid, and 0.1-0.3% of red rooted saliva root fermentation liquid. Compared with a common puffed feed for the micropterus salmoides, a feed formula provided by the invention can meet the basic nutrient demands of juvenile fishes, medium fishes and adult fishes of the micropterus salmoides, also can effectively enhance exchangeable backflow between artery blood and vein blood in hepatic tissue blood circulation, and has a good prevention effect and a repair treatment effect on the white liver lesion and hepatic tissue hypofunction caused by the white liver lesion.

The invention relates to a liver cirrhosis remote consultation system based on abdominal computed tomography (CT) image transmission. A CT instrument has a quite high tissue density resolution ratio and can be used for providing objective bases for imaging diagnosis of liver pathological changes. The liver cirrhosis remote consultation system based on the abdominal CT image transmission comprises a patient terminal collection system, a cloud computing processing center and a hospital background service management system, wherein the patient terminal collection system comprises an abdominal CT image shooting device, a medical image processing system and a data remote transmission system; the cloud computing processing center comprises an image sorting, encrypting and decoding processing module, a computer aided detection system and an expert outpatient service calling system; and the hospital background service management system comprises a case image query / storage database and diagnostic workstations. The liver cirrhosis remote consultation system based on the abdominal CT image transmission is used for diagnosis of the liver pathological changes, especially liver cirrhosis, which relate to an abdominal CT image examination, and can provide the most intuitive liver cirrhosis tissue structure images for doctors for consultation at different places; noise can be filtered when preliminary information is transmitted in a remote mode; geographical restrictions are broken; and the consultation at different places and multiple places can be realized.

The present invention relates to for treating for an individual identified as suffering from a liver lesion, preferably liver fibrosis or cirrhosis. The present invention thus relates to a method invention for implementing an adapted patient care for an individual suffering from a liver lesion, preferably liver fibrosis or cirrhosis, said method including the steps of (i) determining in the individual the presence and severity of a liver lesion, preferably liver fibrosis or cirrhosis, by carrying out at least one non-invasive test resulting in a value and positioning the at least one value in a class of a detailed classification; and (ii) implementing an adapted patient care for the individual depending on the severity of the liver lesion, preferably liver fibrosis or cirrhosis, as determined by the class of the detailed classification wherein the at least one value was positioned.

A mini-peptide and its analogs have been found to target gene products to tumors. The peptide, named Carcinoma Homing Peptide (CHP), increased the tumor accumulation of the reporter gene products in five independent tumor models, including one human xenogeneic model. A CHP-IL-12 fusion gene was also developed using CHP and the p40 subunit of IL-12. The product from CHP-IL-12 fusion gene therapy increased accumulation of IL-12 in the tumor environment. In three tumor models, CHP-IL-12 gene therapy inhibited distal tumor growth. In a spontaneous lung metastasis model, inhibition of metastatic tumor growth was improved compared to wild-type IL-12 gene therapy, and in a squamous cell carcinoma model, toxic liver lesions were reduced. The receptor for CHP was identified as vimentin. CHP can be used to improve the efficacy and safety of targeted cancer treatments.

The invention belongs to the technical field of image processing, and discloses a liver lesion image processing method and system, a storage medium, a program and a terminal. An information processingserver acquires basic information and a CT image of an examiner who has undergone chest CT from a security port; through a gRPC, the information processing server transmits the image to the algorithmserver for calculation, and an algorithm server transmits a result back to the information processing server; the information processing server writes the inspector information and the calculation result into a MySQL and MongoDB database, and a RESTful standard interface is established to expose the data; and a front-end webpage displays liver and possible focus information. On the basis of the existing classic neural network unet architecture, on the basis of continuously feeding back an increased liver lesion data set, through comprehensive improvement of the model, the liver recognition accuracy can be improved to 97%, and the liver occupation recognition accuracy is improved to 98%.

The invention discloses a Chinese herbal medicine feed additive with a liver protecting effect for snakehead. The feed additive is prepared from a component A and a component B, wherein the componentA is prepared from the following raw materials in parts by mass: 9-10 parts of stringy stonecrop herb, 7-8 parts of Chinese thorowax roots, 7-8 parts of isatis roots, 5-6 parts of radix codonopsitis,5-6 parts of milkvetch roots, 4-5 parts of radix salviae miltiorrhizae, 4-5 parts of Chinese magnoliavine fruits, 3-4 parts of Sichuan lovage rhizome and 3-4 parts of white peony roots; and the component B is prepared from the following raw materials in parts by mass: 10-12 parts of cuttlefish visceral meal, 10-12 parts of shrimp shell powder, 9-11 parts of peanut bran powder and 6-7 parts of beeryeast powder. By adjusting and compounding all raw material ingredients in the component A and the component B, the feed additive disclosed by the invention has the effects of nourishing and protecting the liver for snakehead, promoting healthy growth, enhancing body immunity and disease resistance and increasing the survival rate, especially has excellent prevention and treatment effects on hepatobiliary necrosis, fatty liver and other diseases of the snakehead, and has a good recovery effect on liver lesion.

The invention particularly relates to a device (100) for calculating a score (205) reflecting a state of liver damage, said calculating device (100) being designed to calculate a score (205) using the following physical parameters: a parameter corresponding to inflammation and / or fibrosis; and a parameter corresponding to steatosis.

The invention belongs to the field of traditional Chinese medicine production and relates to an application of Cordyceps sobolifera water extract in preparation of an acute liver injury preventing and treating drug. Based on D-galactosamine / lipopolysaccharide induced acute liver injury model experiments, results prove that the Cordyceps sobolifera water extract can relieve lipid peroxidation and oxidative stress injury of liver cells by reducing transaminase (AST and ALT) and alkaline phosphatase (ALP) in serum, remarkably relieves infiltration of inflammatory factors of the liver and improves liver lesion obviously, meanwhile, the Cordyceps sobolifera water extract can relieve infiltration of neutrophils in the liver, inhibit transcription and expression of related inflammatory mediators, reduce inflammation induced inflammatory factor and NO release and inhibit MAPK (mitogen-activated protein kinases) pathway activation. The Cordyceps sobolifera water extract can be used for preparing the acute liver injury preventing and treating drug and is used for protecting liver function and relieving liver inflammation.

The invention discloses a system for identifying focal liver lesions based on contrast-enhanced ultrasonography. The system includes a video acquisition module, an image extraction module, an image pre-processing module, a classification labeling module, a feature extraction module, a data processing module, and a data output module, a mode based on combination of edge enhancement and color balance is used firstly for performing denoising and enhancement processing on a contrast image to enhance useful information of the image while retaining the color of the contrast image, then based on a gray level histogram of the image, feature extraction is performed on the contrast image to obtain reasonable quantitative parameters, so that the diagnostic errors caused by probe movement and lesion movement caused by breathing movements of a patient can be inhibited to the greatest extent, so that the features of the lesion is reflected scientifically, objectively, clearly, and effectively, so that accuracy rate and efficiency of feature identification of the focal liver lesions by a contrast-enhanced ultrasonography technology is improved, and thus a novel way is provided for the faster andbetter development of the contrast-enhanced ultrasonography technology.

The invention relates to an improved hepatoprotective capsule. The powdery content of the capsule is the mixture of the following decoction pieces in parts by weight: 1-2 of Herba Artemisiae Capillaris, 1-1.5 of Prunella vulgaris, 0.3-0.8 of wine-processed Rhizome coptidis, 0.5-1 of Pericarpium Citri Reticulatae Viride, 1-1.5 of Salvia miltiorrhiza, 1-1.5 of Radix Curcumae, 1-2 of Astragalus membranaceus, and 0.3-1 of Rhizoma Cyperi. Besides, the following materials can also be added: Angelica sinensis, processed Radix Paeoniae Alba, Rhizoma Ligustici Chuanxiong, Pueraria flower, Placenta Hominis, Eucommia ulmoides, Herba Epimedii, Lycium barbarum fruit, Semen Allii Tuberosi, Radix Morindae Officinalis, Cuscuta chinensis seed, Cornus officinalis fruit and charred hawthorn fruit. The improved hepatoprotective capsule has a curative effect on hepatitis B, hepatitis A, liver injury, alcoholic liver injury and fatty liver. The use of charred hawthorn fruit and processed Radix Paeoniae Alba is not found in the prior art. The improved hepatoprotective capsule has significant effects of improving alcohol-decomposing capability of the liver, promoting qi and blood flow, rapidly recovering liver lesions and restoring liver functions; is particularly suitable for preventing and treating liver diseases in people who have many dinner parties and drinkers. The capsule has no toxicity or side effect.

The invention discloses an ultrasound contrast video data analysis method based on a composite neural network. The method comprises the following steps: acquiring ultrasound contrast multi-stage videodata of a to-be-analyzed liver lesion; extracting a plurality of ultrasonic contrast time sequence units from the multi-phase video data; marking a plurality of ultrasonic contrast time sequence units; extracting comprehensive information of each time sequence unit through a composite neural network; performing subsequent network training according to the comprehensive information of each time sequence unit; obtaining a parameter weight for liver lesion judgment, constructing a liver lesion analysis model according to the network parameter and the parameter weight, finally inputting ultrasound contrast multi-stage video data of a to-be-analyzed liver lesion into the liver lesion analysis model, and outputting the analysis result of the to-be-analyzed liver lesion. By adopting the embodiment provided by the invention, the CEUS time sequence information can be fully utilized, and the computer computing power requirement for video analysis is reduced, so that the liver lesion to be analyzed can be quickly analyzed.

The invention belongs to the technical field of healthcare food, and particularly relates to a liver-benefiting polypeptide composition. The composition is mainly prepared from medlar and lamb liver polypeptide. The invention further provides application of the liver-benefiting polypeptide composition for preparing liver protection healthcare products. According to the liver-benefiting polypeptidecomposition, the lamb liver polypeptide and medlar are adopted as raw materials, the lamb liver polypeptide contains the liver cell hepatic stimulator substance (HSS), the HSS can stimulate liver cells to synthesize DNA and has the effect of promoting liver cell regeneration, the liver detoxification function is enhanced, metabolism of the liver is promoted, liver lesion cells are repaired, ironelements are abundant, the cell hemachrome can be remarkably improved, and the blood enriching function is achieved; the medlar can nourish the liver and the kidney, strengthen muscles and bones, nourish blood, improve the eyesight, moisten the lung to arrest cough; the lamb liver polypeptide and the medlar are combined for use, the liver function can be promoted, and the protection effect is achieved under the condition that the liver is damaged.

A method computerized optically analyzes methods of conventional, preferably non-contrast-enhanced, MR (magnetic resonance) images of the liver. The method enables the detection of steatohepatitis by NASH-MRI and significant fibrosis by Fibro-MRI in patients suffering from NAFLD. The method enables forecasting the rate of disease progression, to support therapeutic decision-making, and to monitor potential therapeutic effects.

The invention relates to a traditional Chinese medicine compound oral liquid with the effects of clearing heat and promoting diuresis, which comprises three medicines of radix isatidis, virgate wormwood herb and liquorice. The compound oral liquid is suitable for liver lesions caused by livestock escherichia coli, salmonella and the like; meanwhile, in combination of the special physical structure that the poultry genital tract is short, and the wood fiber cannot be digested, the medicament is prepared into the oral liquid, and quickly dispersed in fodder water, so that diseased livestock takes the medicine through drinking the water, so that the oral liquid is convenient and favorable for absorption, thereby achieving the quick effect.

The invention relates to a method for preparing dehydrodiconify alcohol or an ethyl acetate extract of semen hertospermi with dehydrodiconify alcohol as the main active ingredient and application thereof in hepatoprotective drugs for preventing or treating liver damage. The extraction method includes the following steps that pulverized semen hertospermi is pulverized and extracted with ethanol, the extract is extracted with ethyl acetate, and concentration under reduced pressure is conducted to form the extract. It is found through experiments that dehydrodiconify alcohol can significantly reverse the increase of liver function levels such as ALT and AST in the serum of ANIT-induced cholestasis SD rats, the decrease of bile flow and liver lesions, and has a significant anti-liver damage protective effect; dehydrodiconify alcohol acts mainly by modulating downstream gene expression based on activation of an FXR target. The application range of dehydrodiconify alcohol and the ethyl acetate extract of semen hertospermi is broadened, and the method for preparing dehydrodiconify alcohol or the ethyl acetate extract of semen hertospermi with dehydrodiconify alcohol as the main active ingredient and the application thereof in the hepatoprotective drugs for preventing or treating liver damage have important application value and economic benefit for the development of FXR agonistic drugs and anti-liver damage protective drugs.

The invention relates to a feed additive for preventing and treating ascites disease of bullfrogs as well as a preparation method and application of the feed additive. The feed additive comprises the following components in parts by weight: 15-30 parts of fructus forsythiae, 15-30 parts of radix bupleuri, 1-2 parts of allicin, 2-4 parts of bile acid, 15-25 parts of lactobacillus acidophilus freeze-dried powder, 15-25 parts of bacillus subtilis freeze-dried powder and 10-20 parts of corn starch. According to the invention, allicin is compatible with forsythia suspensa and bupleurum chinense to enhance the drug effect, and bile acid is combined with forsythia suspensa and bupleurum chinense to more effectively improve the liver function and reduce the liver lesion probability; besides, the lactobacillus acidophilus and the bacillus subtilis are adopted, regulation and inhibition of flora in digestive tracts such as intestinal tracts are facilitated, pathogenic bacteria in water are inhibited, absorption of animals to nutrient substances is promoted, and the feed conversion rate is increased; finally, traditional Chinese medicines and beneficial bacteria are combined, so that side effects are avoided, ascites diseases can be prevented and treated. According to the invention, the feed coefficient is reduced, the weight gain rate is increased, the effects are remarkably enhanced through combination of the traditional Chinese medicines and the beneficial bacteria, and economic benefits are increased.

The invention discloses preparation of a hepatic fibrosis antibody protein chip and an application of the hepatic fibrosis antibody protein chip in fibrosis diagnosis staging. The method comprises thefollowing steps: establishing a sample library of serum biomarkers of liver fibrosis patients with different causes, screening biomarkers with higher sensitivity and specificity, preparing antibody protein chips for liver tissue biopsy staging, establishing a liver fibrosis marker protein antibody chip detection system, and applying the method to the fields of medical research and clinical medicine. According to the invention, the cause of liver fibrosis can be rapidly and efficiently detected by only taking peripheral blood of a patient, so the detection cost is reduced, the detection time is shortened, the requirement of liver lesion biopsy is reduced, the sampling difficulty is reduced, and the pain of the patient caused by sampling is relieved.

The invention provides a liver focus diagnosis method and device based on a CT image. The method comprises the following steps: finding an image belonging to the same lesion in three phases through liver lesion matching on the three phases of plain scanning, artery and vein of a CT image of the same case; respectively determining a three-dimensional space occupied by each focus on three phases, and if one phase lacks an image of a certain focus, determining a three-dimensional space occupied by the focus on the phase based on the three-dimensional spaces occupied by the focus on other phases; digging the focus down from each phase and scaling to the same target size; and respectively carrying out focus feature extraction on each phase, fusing the focus features extracted from the three phases, and inputting the fused features into a classifier to obtain the category to which each focus belongs. The invention can make full use of the expressions and signs of the lesion in multiple phases for lesion diagnosis, and improves the accuracy of lesion diagnosis.