60 results about "Lung tuberculosis" patented technology

The invention discloses a pulmonary tuberculosis detection method and system based on a chest X-ray image and a storage medium, and the method comprises the following steps: obtaining the chest X-rayimage, and carrying out the preprocessing of the chest X-ray image; inputting the preprocessed chest X-ray image into a trained target detection model, and obtaining a lung parenchyma segmentation region of the preprocessed chest X-ray image; performing image segmentation on the preprocessed chest X-ray image according to the lung parenchyma segmentation region to obtain a lung region image; inputting the lung region image into a plurality of trained feature detection networks to obtain a plurality of feature images; and performing weighted combination on the feature image to obtain the category of the chest X-ray image. According to the invention, the chest radiography image is processed through the target detection model and the feature detection network, the pulmonary tuberculosis probability of the chest radiography image is predicted, and the workload of medical staff in pulmonary tuberculosis diagnosis is greatly reduced. The invention can be widely applied to the field of medical image processing.

The invention relates to a pulmonary tuberculosis variation activity marker, a kit, a method and a model construction method, and the pulmonary tuberculosis variation activity marker is characterized in that the pulmonary tuberculosis variation activity marker is a plasma protein biomarker in a blood sample, and the plasma protein biomarker is a combined marker comprising one or more of C1QB protein and CCL19 (MIP3B) protein; a combined marker of C1QB and CCL19 (MIP3B) is used as a biomarker for detecting the activity of pulmonary tuberculosis for the first time, a rapid diagnosis model for detecting the activity of pulmonary tuberculosis is constructed, a new direction is provided for clinical diagnosis of tuberculosis, and as a technical conception for diagnosing the activity of pulmonary tuberculosis, the biomarker provides a new target spot for the diagnosis of the active tuberculosis; therefore, the invention overcomes the defects of low detection rate, long time consumption and the like of the existing active tuberculosis diagnosis, has the characteristics of good specificity and high sensitivity, and has good clinical application value for auxiliary diagnosis of tuberculosis activity.

The invention belongs to the technical field of medical diagnosis, and discloses a processing system and an information processing method for distinguishing pulmonary tuberculosis and tumor information. The processing system for distinguishing pulmonary tuberculosis and tumor information comprises a patient information acquisition module, a lung image acquisition module, a central control module,a lung image enhancement module, an image segmentation module, an image feature extraction module, an image retrieval module, a comparison module, a disease analysis module, a treatment scheme writingmodule, a diagnosis report generation module and a display module. Interference factors such as a human body trunk and a bed board are automatically removed through the image segmentation module, sothat a pulmonary parenchyma image can be rapidly and accurately extracted to better assist a doctor; meanwhile, through the image retrieval module, the efficiency of searching for the similar lung images by the doctor user is greatly improved, corresponding retrieval feature vectors are obtained according to different focus types contained in the to-be-retrieved images, similar sample lung imagesare retrieved based on the retrieval feature vectors, and therefore the lung image retrieval accuracy is improved.

A composite medicine in the form of injection or orally taken solid or liquid for treating asthmatic chronic bronchitis, acute bronchal asthma, lung infection, pneumonia, pneumonectasis, cardiogenic asthma, pulmonary tuberculosis, silicosis, etc is prepared from indianmulberry root or its extract and picrorhiza rhizome or its extract. Its preparing process is also disclosed.

The invention discloses an enzyme-linked immunospot test method for T lymphocytes. The method comprises the following steps: by adopting a T-SPOT.TB kit produced in British Oxford Immunotec Company, taking 5ml of sodium citrate anticoagulation venous blood, separating mononuclear cells of peripheral blood and placing the mononuclear cells on a gamma-interferon antibody coated porous plate, adding an early secretory antigenic target (ESAT-6) of tuberculosis specific antigen and a culture filtrate protein (CFP-10) to serve as stimulus antigens, culturing in an incubator for 24 hours, washing off T lymphocytes with antigen sensitization effects, adding a biotin labeled second antibody, performing enzyme linked colorimetry, forming spots at secreting positions of cell factors, and detecting the number of the T lymphocytes with the tuberculosis specific antigen sensitization effects by recording the spot number. The method disclosed by the invention contributes to early screening of culture negative pulmonary tuberculosis.

The invention belongs to the technical field of medical early warning, and discloses a pulmonary tuberculosis patient early warning system and early warning method based on electronic medical record data. The pulmonary tuberculosis patient early warning system based on electronic medical record data comprises a patient disease data acquisition module, a data preprocessing module, an electronic medical record generation module, a main control module, a detection model construction module, a medical record analysis module, a disease grading module, an information screening module, an early warning information pushing module, a cloud storage module and a display module. According to the invention, the pulmonary tuberculosis focus area can be detected more accurately through the detection model construction module; besides, missed diagnosis of pulmonary tuberculosis caused by busy work or insufficient understanding and other reasons is reduced through the screening module; and automatic pulmonary tuberculosis reporting work achieves whole-process electronization and automation, pulmonary tuberculosis diagnosis work of a non-fixed-point medical institution is all well-documented, and the defect that time and labor are consumed when tuberculosis missing report and missing registration special work is conducted, is overcome.

The invention discloses a pulmonary tuberculosis judgment method and device, computer equipment and a storage medium, and relates to the technical field of artificial intelligence. The pulmonary tuberculosis judgment method comprises the following steps: acquiring a to-be-classified chest X-ray film image; converting the chest X-ray film image to be classified into a target image to be classifiedaccording to a preset image processing step, the resolution and dimension of the target image to be classified being the same as those of a target image sample for training a pulmonary tuberculosis classification model; and inputting the to-be-classified target image into the pulmonary tuberculosis classification model to obtain a prediction probability, the prediction probability being a probability of predicting pulmonary tuberculosis to be positive, and when the prediction probability is greater than a preset threshold, determining that pulmonary tuberculosis exists in the to-be-classifiedchest X-ray film image corresponding to the to-be-classified target image. By adopting the pulmonary tuberculosis judgment method, the pulmonary tuberculosis can be quickly judged on the premise of ensuring relatively high accuracy.

The invention provides a pulmonary tuberculosis intelligent identification method based on conventional test data, which is characterized in that the conventional test data and test index data of laboratories including blood routine examination, biochemical examination, urine routine examination and the like are used, and a machine learning method is used for training one or more classifiers to intelligently recognize whether a patient suffers from pulmonary tuberculosis or not; and the classifiers are deployed to a hospital lis system for receiving real-time inspection data to complete intelligent identification of pulmonary tuberculosis. The method aims to solve the problems that an existing pulmonary tuberculosis diagnosis method is low in disease recognition efficiency and accuracy and high in cost and experience dependence, and cannot meet pulmonary tuberculosis prevention and treatment requirements under the current situation that medical resources are unbalanced.

The invention relates to a traditional Chinese medicine detection method, and discloses lung benefiting tablets prepared from bulbus fritillariae ussuriensis and milkvetch roots and identification and content determination methods .The lung benefiting tablets prepared from bulbus fritillariae ussuriensis and milkvetch roots are used for phthisis and are specially applicable to secondary pulmonary tuberculosis qi consuming and yin injuring syndrome .Radix stemonae, herba houttuyniae, rhizoma bletillae and radix notoginseng are selected as identification items, testing and screening are conducted through parameters, and the advantages of being good in chromatographic condition, good in specificity and reproducibility, rapid, economical and practical are achieved .A milkvetch root content determination method is selected, so that the method is high in specificity, high in accuracy and capable of effectively improving the product quality and better ensuring the curative effect of a product .The technology and detection method are reasonable, applicable and effective.

The invention discloses an intelligent pulmonary tuberculosis detection method and system based on images and clinical data. The method comprises the following steps: acquiring a medical image and clinical data of a to-be-processed target; the clinical data comprises medical history data and biochemical data; encoding the medical history data and the biochemical data to obtain a medical history data vector and a biochemical data vector; performing multi-modal data coupling on the medical image, the medical history data vector and the biochemical data vector to obtain a multi-dimensional feature map sequence group; inputting the multi-dimensional feature map sequence group into a self-attention network, and superposing the output of the self-attention network to obtain feature data; and according to the feature data, obtaining a pulmonary tuberculosis detection result of the to-be-processed target. According to the method, the features of the image data and the clinical data are well fused, the method is used for achieving intelligent detection of the pulmonary tuberculosis, the detection precision of the pulmonary tuberculosis can be remarkably improved, diagnosis work can be assisted to be completed, and the workload of doctors is relieved. The method can be widely applied to the technical field of medical image processing.

The invention discloses a DR image pulmonary tuberculosis intelligent segmentation and detection method based on deep learning, and the method comprises the steps: extracting a mask from an original DR image, filtering a small-area region, carrying out convex hull operation, and carrying out texpansion operation of the mask after the convex hull operation, and obtaining a lung effective region; labeling the original DR image, and labeling the position of a lesion area of the DR image with pulmonary tuberculosis expression; sending the masked image and the annotation information containing thepulmonary tuberculosis change area position into a deep neural network for training, and learning features of the pulmonary tuberculosis image; and using the trained model to predict the untrained DRimage, outputting the position of the pulmonary tuberculosis change area, and giving the probability of the pulmonary tuberculosis change area. According to the invention, the detection rate of pulmonary tuberculosis is greatly improved, the position of a pulmonary tuberculosis change area is accurately output, and reliable and efficient reference is provided for screening and treatment of pulmonary tuberculosis.

The invention discloses application of miR-31-5p and miR-99a-5p in distinguishing active tuberculosis and latent tuberculosis infection. Substances for detecting the expression quantity of miR-31-5p comprise a reagent and an instrument which are used for detecting the expression quantity of the miR-31-5p by using quantitative PCR (polymerase chain reaction) and a reagent and an instrument which are used for detecting the expression quantity of the miR-31-5p by using an RNA-Seq; and substances for detecting the expression quantity of miR-99a-5p comprise a reagent and an instrument which are used for detecting the expression quantity of the miR-99a-5p by using the quantitative PCR and a reagent and an instrument which are used for detecting the expression quantity of the miR-99a-5 by using the RNA-Seq. The AUC of the miR-31-5p and the miR-99a-5p which are used for distinguishing an active tuberculosis patient and a latent tuberculosis infection patient is greater than 0.8, and the specificity is high; and the miR-31-5p and the miR-99a-5p can be used for distinguishing the active tuberculosis and the latent tuberculosis infection.

The invention provides a pulmonary tuberculosis positioning and screening device and a computer device, and relates to the field of medical image processing. A method comprises: obtaining a to-be-processed orthotopic chest radiography image through the chest radiography image processing module; preprocessing the chest radiography image to obtain a target chest radiography image; extracting a lungfield foreground image from the target chest radiography image by adopting a lung field segmentation model through a lung field image extraction module; then, using a pulmonary tuberculosis segmentation screening model in a lung field distribution area of the lung field foreground image through a pulmonary tuberculosis screening module; positioning and segmenting a lesion area of the suspected pulmonary tuberculosis; calculating the diagnosis probability that the corresponding lesion area is screened as pulmonary tuberculosis; obtaining the pulmonary tuberculosis screening heat map and the pulmonary tuberculosis diagnosis probability, so that the pulmonary tuberculosis screening operation of the to-be-processed orthotopic chest radiography image is completed through the computer device, the pulmonary tuberculosis missing detection phenomenon in the pulmonary tuberculosis screening process is improved, the manual participation degree in the tuberculosis screening process is reduced, andthe pulmonary tuberculosis screening efficiency is improved.

The invention discloses a formula of a traditional Chinese medicine for treating bronchitis, pulmonary tuberculosis and early lung cancer. The medicine comprises the following components of flos lonicerae, herba houttuyniae, rhizoma polygonati, radix angelicae sinensis, semen lepidii, semen perillae acutae, semen brassicae, bulbus lilii, radix rehmanniae, radix scrophulariae, radix glycyrrhizae preparata, radix platycodonis, radix ophiopogonis, radix asparagi, radix paeoniae alba, radix asteris, radix adenophorae, radix peucedani, poria cocos, pericarpium citri reticulatae, rhizoma atractylodis macrocephalae, radix scutellariae, bulbus fritillariae cirrhosae, tuber bletillae, colla corii asini, radix panacis quinquefolii and cornu saigae tataricae. The medicine is simple in process, convenient to prepare, convenient to carry, few in treatment course and remarkable in curative effect, and can be taken only by grinding.

The invention provides a pulmonary tuberculosis identification method based on SE-ResNet, and the method comprises the steps: obtaining a real pulmonary tuberculosis image, generating a pulmonary tuberculosis image through employing a DCGAN network, and constructing a matrix pulmonary tuberculosis image data set based on the real pulmonary tuberculosis image and the generated pulmonary tuberculosis image; preprocessing the pulmonary tuberculosis image data set, wherein preprocessing comprises data reading and data normalization processing; dividing the pulmonary tuberculosis image data set into a training set and a test set; constructing an SE-ResNet network based on a ResNet50 network and an SENet module, pre-training the network by using ImageNet data, initializing network parameters, and training the network by using a training set; and analyzing and identifying the pulmonary tuberculosis image to be identified by adopting the trained SE-ResNet network to obtain a corresponding analysis and identification result. According to the identification method, the pulmonary tuberculosis X-ray chest radiograph can be intelligently identified without manual intervention, the identification speed is high, and the precision is high.

The invention discloses traditional Chinese medicine condensed decoction with a cough relieving function and a preparation method thereof. The formula comprises bulbus fritillariae cirrhosae fluid extract 1%-5%, lotus leaf extracting solution 10%-25%, fermented Chinese caterpillar fungus powder 5%-15%, menthol and almond essence 0.05%-0.1% and honey 55%-84%. According to the condensed decoction, the dosage form is honey-refined condensed decoction, the condensed decoction has good mouth feeling and is a good lung moistening and cough relieving product for treating in consideration of health care, and the condensed decoction is capable of tonifying lung and kidney, is used for treating cough caused by yin deficiency, chronic cough, fatigue, excessive use of throat, excessive smoking and thelike and can also be used as an adjuvant drug for chemotherapy for tuberculosis and lung cancers.

The invention discloses an interpretable pulmonary tuberculosis classification network identification method based on a CT image, and the method comprises the following steps: obtaining a CT image of the lung of a to-be-detected person, and carrying out the normalization processing and zooming of a pulmonary parenchyma image; establishing and training an interpretable pulmonary tuberculosis classification network, wherein the interpretable pulmonary tuberculosis classification network is established by taking a residual network as a basic network and adding a Dense thought and an improved attention mechanism; and sending the lung parenchyma image which is normalized and scaled to the size of 512 * 512 into the trained interpretable pulmonary tuberculosis classification network, and obtaining and outputting a classification result of the pulmonary tuberculosis of the to-be-detected person and a corresponding class activation thermodynamic diagram in an upper computer. According to the CT image of the to-be-tested person, the classification result of the pulmonary tuberculosis of the to-be-tested person can be obtained, and the corresponding class activation thermodynamic diagram can be output.