93 results about "Lung lesion" patented technology

The invention provides a correlation analysis method for a lung CT image, and the method comprises the steps: obtaining a lung multi-modal image which comprises a computed tomography image and a positron emission tomography image, and carrying out the denoising, enhancement and standardization preprocessing of an original image according to the imaging principles and image characteristics of different modals; extracting a lung lesion region of interest from the registered multi-modal image, sketching and segmenting the lesion, and quantitatively analyzing the volume and shape geometric morphological characteristics of the lesion; based on a curative effect result, correlation between radiomics features and patient prognosis is analyzed, recurrence and metastasis risks and lifetime under different feature expressions are estimated, a curative effect prediction model is constructed in combination with image features and clinical indexes, and long-term individualized evaluation is performed on patient prognosis.

The invention relates to a lung focus medical image segmentation method based on graphics and text information and knowledge embedding. The method comprises the following steps: acquiring a lung medical image of a patient and a corresponding clinical diagnosis report; preprocessing the lung medical image to obtain an enhanced image; inputting the lung medical image and the clinical diagnosis report into the medical visual language model to obtain a focus prompt embedding vector; and inputting the lung medical image, the enhanced image and the focus prompt embedding vector into the medical image segmentation model to obtain a lung focus region segmentation image. By adopting the method, the lung focus can be quickly positioned by the segmentation model through the focus prompt embedding vector, the interference of a non-target area is reduced, and the segmentation accuracy and the target concentration are improved.

The invention relates to a segmentation model based on a CNN and Transform parallel double-branch structure, and belongs to the technical field of medical data prediction. The method comprises the following steps: acquiring a CT image, and preprocessing the CT image by executing windowing processing and contrast limited adaptive histogram equalization; extracting features of lung lesions in the preprocessed CT image through a parallel double-branch structure; inputting the extracted features into a cross enhancement fusion module, and performing complementary fusion on the features through dynamic weight distribution to obtain fused features; the fusion features are input into a multi-scale context information extraction module, and lesion boundary sensitivity is enhanced through cavity convolution of different expansion rates; the encoder features and the decoder features are fused through jump connection, and a segmentation result is output after resolution is recovered based on up-sampling; and optimizing model training by adopting a weighted loss function. Accurate segmentation of the lung lesion in the pulmonary tuberculosis CT image is realized, and clearer and more accurate lesion area information can be provided.

The invention relates to the technical field of medical image processing, and particularly discloses a lung focus recognition method and system based on image deep learning, and the method comprises the steps: carrying out the enhancement and registration of an input lung image, and constructing a marking data set; constructing a convolutional neural network model with a multi-scale receptive field, introducing an attention mechanism to focus the model on a lesion area, coarsely and finely identifying the lesion position and estimating the size of the lesion position; further purifying a focus area and removing artifacts and noise by applying morphological filtering and connected domain analysis; and carrying out uncertainty evaluation on the identification result to obtain a focus identification result. According to the method, local details and global structure information in the lung image can be comprehensively captured, the model can be more accurately focused on the lesion area in combination with an attention mechanism, and the lesion recognition accuracy is improved. According to the invention, confidence information of an identification result is provided for doctors. And for a low-confidence result, measures such as manual judgment or re-collected data identification can be taken, so that the diagnosis reliability is improved.

The invention relates to the field of intelligent medicine, in particular to a lung injury intelligent detection system based on lung images and pathological data, which comprises a multi-modal data acquisition module, an intelligent segmentation module, a cross-modal feature fusion module and a lung injury classification detection module, a trans-attention multi-modal feature fusion method based on bidirectional gating is adopted, a lung CT image and a pathological text are coded, modal interaction is achieved through a bidirectional gating attention mechanism, a lesion area is highlighted, a channel-space attention gate is introduced, feature fusion is optimized, and accurate lung injury detection is achieved. A medical image segmentation method based on multi-layer fusion optimization and multi-layer parallel enhancement is adopted, through multi-layer feature optimization based on depth separable convolution and three-layer parallel feature enhancement based on a residual mechanism, key features, namely a focus area, are reserved, local-global features are effectively integrated while nonlinear information is captured, and the image segmentation efficiency is improved. The lung lesion area is accurately segmented, and the accuracy of lung injury detection is improved.

The lung analysis system based on the parameter response diagram and the image generation system is realized. The system is composed of a data collection and management module, an image registration module, a controllable image generation module, a parameter response diagram analysis module and a disease course development evaluation module. The data collection and management module is in butt joint with a hospital information system and CT image collection equipment. The image registration module receives a double-phase CT scanning image of a patient to obtain a registered double-phase CT image; the controllable image generation module receives a single inspiration phase CT scanning image of a patient as input to generate a registered expiration phase CT scanning image; the parameter response diagram analysis module obtains multiple parameter response diagram analysis and evaluation results of organic lesion evaluation of the lung of the patient; the disease course development evaluation module predicts the lung function condition of the patient. Therefore, the problems that when a parameter response diagram method is used, biphasic CT collection is difficult, and the ability to evaluate the disease course development of a patient is lacked are solved.

The invention relates to a lung image data processing method and device, computer equipment, a medium and a product. The method comprises the following steps: acquiring a lung scanning image of a to-be-detected object; performing tissue segmentation processing on the lung scanning image to obtain a tissue segmentation result corresponding to the lung scanning image; performing three-dimensional reconstruction on the tissue segmentation result to obtain a three-dimensional tissue image corresponding to the lung scanning image; performing region segmentation processing on a lung region of the to-be-detected object according to the three-dimensional tissue image to obtain a region segmentation result corresponding to the lung region; and positioning a focus area in the lung area based on an area segmentation result. The method comprises the following steps: firstly, segmenting and reconstructing tissues in a lung scanning image to obtain a three-dimensional multi-tissue image, and then carrying out multi-region division on a lung region based on the three-dimensional multi-tissue image to obtain a three-dimensional lung region segmentation result, so that the three-dimensional lung region segmentation result can stereoscopically present a plurality of regions of the lung, and therefore, the lung region segmentation efficiency is improved. Fine division of lung focuses can be realized.

Techniques for segmentation include determining an edge of voxels in a range associated with a target object. A center voxel is determined. Target size is determined based on the center voxel. In some embodiments, edges near the center are suppressed, markers are determined based on the center, and an initial boundary is determined using a watershed transform. Some embodiments include determining multiple rays originating at the center in 3D, and determining adjacent rays for each. In some embodiments, a 2D field of amplitudes is determined on a first dimension for distance along a ray and a second dimension for successive rays in order. An initial boundary is determined based on a path of minimum cost to connect each ray. In some embodiments, active contouring is performed using a novel term to refine the initial boundary. In some embodiments, boundaries of part-solid target objects are refined using Markov models.

The invention relates to a double-channel lung lesion biopsy robot and a control method, and relates to the technical field of surgical instruments / minimally invasive surgery robots, the double-channel lung lesion biopsy robot comprises a first positioning mechanical arm, a second positioning mechanical arm, a first instrument driving mechanical arm, a second instrument driving mechanical arm, a bronchoscope and a puncture needle, the first positioning mechanical arm and the first instrument driving mechanical arm are used for automatically or manually positioning the bronchoscope to the focus position, and the second positioning mechanical arm and the second instrument driving mechanical arm are used for controlling the puncture needle to implement puncture biopsy through the chest wall. The problem that an existing surgical robot technology cannot be completely suitable for the whole lung when applied to lung lesion biopsy is solved, two biopsy channels are planned at the same time in a unified preoperative planning mode, and image data information obtained through a bronchial channel is used for focus position correction; and an integrated double-arm structure and a seamless switching control mode are designed, so that biopsy of the whole lung focus is completed more accurately in a one-stop mode.

The invention provides an eucheuma compound for improving lung function and a preparation method thereof. The eucheuma compound is prepared from the following raw materials in parts by weight: 25 to 35 parts of eucheuma extract, 13 to 17 parts of oyster peptide, 8 to 12 parts of fish collagen peptide, 4 to 6 parts of rhizoma polygonati, 3 to 5 parts of herba cistanche, 2 to 4 parts of semen euryales and 1 to 2 parts of longan. Secondly, the eucheuma extract rich in eucheuma polysaccharide, eucheuma polypeptide and the like is prepared through the technology. The components in the formula of the eucheuma compound have a synergistic effect, and the prepared eucheuma compound can effectively control the lung coefficient and increase of the hydroxyproline content in lung tissue and improve inflammatory infiltration and fibrohyperplasia of the lung. In addition, the compound also inhibits oxidative stress reaction and further inhibits pulmonary fibrosis; the lung lesion is effectively inhibited, the lung function is improved, and the lung health is promoted.

The invention relates to the technical field of medical imaging, and discloses a peripheral lung cancer pleural invasion evaluation system based on ultrasonic targeted radiography, comprising: a double-frequency ultrasonic probe configured to independently work at different frequencies to realize depth imaging and high-resolution imaging of lung tissues and suitable for different types of lung lesions; the signal processing module can receive, analyze and process echo signals transmitted by the ultrasonic probe, generate images in real time and extract feature information; and the dynamic motion compensation module is used for automatically adjusting the emission time sequence and parameter setting of the ultrasonic signal based on the real-time breathing motion state of the patient. By adopting the design of the double-frequency ultrasonic probe and the core-shell structure, high-resolution imaging and depth detection of lung tissues are realized. By dynamically adjusting the thickness of the probe shell to be matched with the frequency, the system can adapt to complex tissue environments under different physiological conditions, and image definition and stability are ensured.

The invention discloses application of a neutralizing antibody of oncostatin M in preparation of a medicine for treating bronchial pulmonary dysplasia. The application proves that the intrauterine inflammation can cause BPD-like lung lesion to the filial generation mouse, and the OSM expression level in the mouse lung tissue one day after the intrauterine inflammation filial generation is grown is obviously higher than that of a control group; the OSM level of the BPD group is higher than that of the non-BPD group in the umbilical blood sample of the premature infant; in-vitro experiments show that the OSM treatment can cause lung epithelial cell injury; by dripping a recombined OSM neutralizing antibody into the nose of a newborn mouse, down-regulation of the OSM level in the lung of the mouse is realized, filial generation lung injury induced by the intrauterine inflammation can be repaired, and the OSM can be used as a treatment target of the BPD caused by the intrauterine inflammation.

The present invention provides a flexible biopsy forceps with a hollow channel for real-time biopsy of lung lesions, comprising an insertion portion having a hollow channel capable of accommodating a medical device for image-guided imaging; a gripping portion disposed at the distal end of the insertion portion, comprising a first metal groove and a second metal groove capable of interlocking to form a space for accommodating a biopsy specimen, while forming an opening at the distal end to allow the medical device to pass through; an operating portion disposed at the proximal end of the insertion portion and connected to the gripping portion via a connecting device; the operating portion capable of driving the first and second metal grooves to pivot. The present invention can meet the needs of real-time lung biopsy under the guidance of radial bronchial ultrasound or confocal laser endoscopic probes, improve the diagnosis rate of peripheral lung lesions, avoid radiation exposure of medical workers and patients, and provide high-quality pathology / microbiology test samples for later treatment.

The invention relates to the technical field of image processing, and provides a CT image clear processing method, system and equipment for pulmonary infectious diseases, and the method comprises the steps: screening out the edge pixel points of all pulmonary blood vessels according to an authenticity evaluation coefficient, and obtaining the edge pixel points of the pulmonary blood vessels; according to the gray level distribution condition of the pixel points in each lung blood vessel edge area and the authenticity evaluation coefficient, obtaining a frosted shadow feature value of each lung blood vessel edge area; obtaining a lung attrition lesion area; according to a difference condition of gray values of pixel points between the lung attrition lesion area and the surrounding lung attrition lesion area, obtaining a window width adjustment amplitude of the lung image of the patient; and performing window width adjustment on the lung image of the patient according to the window width adjustment amplitude to obtain the adjusted lung image of the patient. According to the invention, more detailed and clearer position and form of the lung lesion area can be provided through the adjusted lung image of the patient.

The present application relates to the technical field of biological medicine, and discloses inhalable aptamer modified molybdenum disulfide nanoflower compound and application thereof.The compound comprises a molybdenum disulfide nanoflower core, a dendritic polylysine modification layer attached to the surface of the molybdenum disulfide nanoflower, doxorubicin loaded on the molybdenum disulfide nanoflower and / or the dendritic polylysine modification layer, and AS1411 aptamer combined on the outer surface of the dendritic polylysine modification layer by electrostatic assembly.The compound can be delivered to a lung lesion by atomization inhalation or aerosol inhalation, and undergoes responsive structural change under the action of hydrogen peroxide in a tumor microenvironment, generates active oxygen, and promotes the release of doxorubicin, so as to realize the synergistic antitumor effect of chemotherapy and chemical dynamic therapy.The compound has good colloidal stability, drug loading capacity, active targeting ability and lung local delivery potential, and can be used for preparing inhalation preparations or local administration preparations for treating lung cancer.

The invention provides a novel vaccine adjuvant and application of the novel vaccine adjuvant in preparation of the vaccine adjuvant. The BCG-PSN and vaccine induced RBD specific IgG antibody and neutralizing antibody level are equivalent to those of an aluminum adjuvant, the BCG-PSN and vaccine induce Th1 biased T cell reaction, the induced T cell response level is obviously higher than that of the aluminum adjuvant, and K18-hACE2 mice are protected from being affected by Delta variant induced lung lesions. As a vaccine adjuvant, BCG-PSN has wide compatibility and safety, and has no toxic or side effect.

The invention discloses an exosome atomized preparation as well as a preparation method and application thereof, and belongs to the technical field of exosome technology and respiratory disease treatment. The problems that antibiotics and anti-inflammatory drugs adopted in the prior art have the defects of drug resistance, large side effects and the like in lung inflammation are solved. The exosome is derived from stem cells which are subjected to gp96 pretreatment and overexpress gp96 antigen information, the gp96 activates antigen presenting cells, the delivery efficiency of immunomodulatory factors (such as IL-10 and TGF-beta) carried by the exosome is enhanced, proinflammatory factors (such as TNF-alpha and IL-6) are inhibited, and in combination with the administration mode of an atomized preparation, through aerosol inhalation, the exosome can be used for preparing the immunomodulatory factor immunomodulatory agent. The exosome can directly reach a lung lesion area, so that the local drug concentration is improved, and the systemic side effects are reduced.

A passive lung simulator device is provided. It includes a casing or box that includes a first lung simulator balloon; an air collector coupled to one end of the first balloon; a first set of servo valves, arranged in series, connected to the air collector via air flow conduits; and a connection element for a mechanical ventilator. The servo valves are configured to independently recirculate the air flow passing through them to the air collector, expanding the balloon. It also includes a first set of cams to be actuated by a servomotor to modify the compliance or capacity of the balloon simulator through the rotation of the first set of cams; and a communications module connected to the first set of servo valves and the first set of cams, with wireless connection to a remote computing device to receive instructions to simulate different pulmonary pathologies.

The application provides a deep granular unsupervised learning method for long-tailed distribution lung cancer subtype identification, comprising the following steps: S10, preprocessing lung lesion image data set, and generating two different enhanced views for each sample to obtain two sample image data sets; S20, using a pre-trained deep neural network to extract and normalize features of the two sample images to obtain sample feature vectors; S30, training using deep granular unsupervised learning, and unsupervised optimizing features based on the granular structure to improve feature separability under long-tailed distribution; and S40, obtaining final clustering results using the Kmeans method after training. The scheme is suitable for long-tailed distribution situations with significant differences in the number of samples of each subtype in the lung cancer subtype identification task, can improve the deep clustering effect for long-tailed distribution data, and provides reliable classification basis for the auxiliary diagnosis of lung cancer subtype identification.

Disclosed is a vaccine for non-human animals, which vaccine enables effective immune induction in non-human animals such as livestock or poultry. The vaccine for non-human animals of the present invention comprises liposomes each comprising an antigen molecule(s) bound to the surface thereof, the antigen molecule(s) being derived from a pathogen infectious to the non-human animals. The non-human animals are, for example, livestock or poultry. One most preferred example of the vaccine according to the present invention is an infectious bronchitis virus (IBV) vaccine, which is effective against various isolated IBV strains, and which is expected to be sufficiently applicable even to cases where a mutant strain appeared. Another preferred example of the vaccine according to the present invention is a PRRSV vaccine, which was confirmed to have an effect that reduces fever, lung lesion development, and the like caused by the infection. The present invention enables development of liposome vaccines effective for prevention of infections caused by various non-human animal pathogens including PRRSV as well as IBV.

The present invention relates to a guide sheath for peripheral bronchial lesion treatment, comprising a side tube for saline infusion, and injects physiological saline, which has been injected for peripheral bronchial dilation and access, through the side tube so that the physiological saline can efficiently reach a peripheral lung lesion as the physiological saline is injected through the side tube without insertion and removal of the guide sheath as in a conventional procedure, such that the precision and efficiency of a bronchoscopy procedure for diagnosing the peripheral lung lesion can be improved. In a conventional procedure, cold physiological saline or epinephrine for hemostasis could be administered after removal of the guide sheath and biopsy forceps, but the side tube of the guide sheath can administer a solution that assists hemostasis immediately after biopsy such that reduced side effects after the procedure and improved safety for the patient can be expected.

The invention provides a traditional Chinese medicine composition for treating cough variant asthma and application thereof, and belongs to the field of traditional Chinese medicine preparations. The traditional Chinese medicine composition is prepared from radix bupleuri, herba ephedrae, herba schizonepetae, semen armeniacae amarae, radix platycodonis, fructus aurantii immaturus, exocarpium citri grandis, rhizoma phragmitis, rhizoma pinelliae, rhizoma belamcandae, the traditional Chinese medicine composition can obviously improve the condition of weight loss of guinea pigs after combined molding of ovalbumin and capsaicin, reduces the cough frequency and the lung focus area, effectively inhibits inflammatory factors, and can reach the treatment level equivalent to that of montelukast sodium.

The invention discloses a lung rehabilitation respiratory training device combining traditional Chinese medicine and western medicine, relates to the technical field of rehabilitation training equipment, and aims to solve the problems of insufficient collaboration, deficiency of individualization and low system integration degree in the prior art. The device comprises a seat, a pedaling piece, a pushing and lifting rod and a breathing assembly, the breathing assembly comprises a traditional Chinese medicine box arranged on a seat backrest through a connecting rod, a breathing mask is arranged above the traditional Chinese medicine box, and a breathing mouth piece is arranged on the inner side of the breathing mask; the sealing connecting pipe is arranged between the traditional Chinese medicine box and the breathing mask; the respiratory capacity display tube is connected to the sealing connecting tube and connected with the traditional Chinese medicine box through a linkage assembly. According to the device, through a mechanical linkage structure, the inspiration action and the medicine mist release of a patient are accurately synchronized in time, it is ensured that quantitative traditional Chinese medicine mist is released at the moment that the inspiration force of the patient is maximum and the lung is expanded most sufficiently, medicine can directly reach the focus of the lung along with deep inspiration airflow, and the synergistic effect that most effective treatment is conducted at the best time is achieved.

The utility model relates to a medical auxiliary instrument. The utility model aims to provide a 3D printing type lung model for doctor-patient communication. The 3D printing type lung model comprises a lung model main body formed through 3D printing according to lung data of a patient; the lung model main body comprises a hollow lung lobe body formed by splicing two mold flaps, a trachea body formed on the lung lobe body in a heterochromatic 3D printing manner, and a focus body formed on the lung lobe body and / or the trachea body in a heterochromatic 3D printing manner; the lung lobe body is further provided with at least one hollow observation opening used for observing a focus body. According to the utility model, actual lung data 3D printing forming of a patient is adopted, the lung focus space structure of the patient can be fully and visually displayed, and accurate communication between a doctor and the patient is facilitated; 3D printing is conducted on the lung lobe body, the trachea body and the focus body through different colors, and the whole lung and the structure of the lung of the patient can be displayed in a layered mode more clearly.

The present invention relates to a lesion recognition and segmentation method and system based on lung CT images, which obtains three-dimensional lung CT image data of a patient, cuts them into several two-dimensional lung CT image pictures and adds serial numbers; performs image preprocessing on several two-dimensional lung CT image pictures, and uses a specified image feature extraction algorithm to extract image features from the preprocessed images; further detects the lesion edge of the extracted two-dimensional lung CT image lesion feature data; based on the edge detection results of the two-dimensional lung CT image pictures, segment the lung lesions and normal tissues to generate several two-dimensional lung lesion pictures with only lesion tissues; based on the added serial numbers, the two-dimensional lung lesion pictures are image-fused according to a specified spacing, and the lesion areas between the specified spacings are filled to obtain a complete three-dimensional lung lesion image. The lesions in the medical images of patients are accurately and efficiently identified and segmented in three-dimensional space.

The application discloses a lung three-dimensional reconstruction method and device, a terminal equipment and a readable storage medium. The method comprises the following steps: acquiring N two-dimensional images of a lung; generating a tubular organ overall point cloud based on the N two-dimensional images by using a first generator; generating an artery point cloud, a vein point cloud and a trachea point cloud based on the N two-dimensional images by using a second generator; generating a lung segment point cloud based on the N two-dimensional images by using a third generator; and three-dimensionally reconstructing the lung by using the tubular organ overall point cloud, the artery point cloud, the vein point cloud, the trachea point cloud and the lung segment point cloud. The application can quickly provide a three-dimensional image of the lung as a diagnosis basis for inexperienced doctors, effectively avoids the influence of the lung lesion diagnosis process on the doctors' subjectivity, improves the lung lesion diagnosis efficiency and the accuracy of the lung lesion diagnosis.

The invention relates to the technical field of medical artificial intelligence, in particular to an acute respiratory failure prediction method based on a mamba architecture, and the method specifically comprises the following steps: obtaining original image data from an existing Lung Phantom Dataset lung lesion data set, constructing a data set # imgabs0 #, and then dividing the data set # imgabs1 # into a training set # imgabs2 # and a test set # imgabs3 #; an acute respiratory failure prediction model based on the mamba architecture is constructed, the model comprises three feature encoders, an attention module, a feature mapping layer, three feature decoders and three mamba modules, original image data in a training set # imgabs4 # are input into the modules, and a prediction result is obtained; and carrying out optimization training on the acute respiratory failure prediction model based on the mamba architecture, and then inputting original image data in the test set # imgabs5 # into the optimized model to obtain a final prediction result. According to the method, the precision of respiratory failure prediction is improved through the efficient mamba architecture, and the method can be used in the field of medical image analysis and prediction.

A radial endobronchial ultrasound system providing localization of visualized lung lesions or nodules in the airways of a patient is provided herein. The system has three, main components: a guide sheath with a distal end, a flexible bronchoscope with a tip, and a radial endobronchial ultrasound probe. The guide sheath directs insertion of the bronchoscope into the patient, with the tip of the bronchoscope extending beyond the distal end of the guide sheath. The bronchoscope has an echogenic discrete marker formed inside and proximate its tip and a working channel configured to include and direct the probe. The probe is configured for insertion into the airways of the patient where the probe rotates to capture a 360-degree circumferential image perpendicular to the probe itself. The echogenic discrete marker on the bronchoscope provides a reference point for localization of the lung lesions or nodules visualized by the image.

A passive lung simulator device is provided. It includes a casing or box that includes a first lung simulator balloon; an air collector coupled to one end of the first balloon; a first set of servo valves, arranged in series, connected to the air collector via air flow conduits; and a connection element for a mechanical ventilator. The servo valves are configured to independently recirculate the air flow passing through them to the air collector, expanding the balloon. It also includes a first set of cams to be actuated by a servomotor to modify the compliance or capacity of the balloon simulator through the rotation of the first set of cams; and a communications module connected to the first set of servo valves and the first set of cams, with wireless connection to a remote computing device to receive instructions to simulate different pulmonary pathologies.

The invention belongs to the technical field of biology, and particularly relates to application of an Mgst2 gene serving as a target to preparation of a product for treating rheumatoid arthritis related interstitial lung diseases. According to the invention, it is found for the first time that Mgst2 can be used as a biomarker for treatment of rheumatoid arthritis related interstitial lung diseases, targeted knock-down is carried out on Mgst2 in neutrophils through an AAV9-shRNA vector (AAV9-shRNA-Mgst2) driven by a Cd11b promoter, and lung lesion progress can be effectively relieved by inhibiting NET formation. The Mgst2 inhibitor provided by the invention can directly intervene in the occurrence and development process of diseases from a molecular level, and has the advantages of accurate effect, remarkable curative effect, low side effect and the like. Compared with a traditional non-specific treatment mode, the product takes effect only aiming at specific molecular targets, damage to normal cells and tissues is remarkably reduced, and therefore the risk of toxic and side effects is reduced.