175 results about "Nodular lesion" patented technology

The invention relates to the field of medical image analysis, in particular to a deep learning prediction system and method based on multi-modal thyroid cancer lymph node metastasis, and the system comprises a data collection module, a preprocessing module, a nodule segmentation module, a feature extraction module, a feature fusion module, a metastasis prediction module, an interpretability analysis module and a result display module. An ultrasonic image, an elastic imaging image, an ultra-micro blood flow image and clinical index data of a patient are integrated, an improved U-Net algorithm is used for precise segmentation of a thyroid nodule region, a multi-branch deep network is used for extracting multi-modal features, a dynamic weight fusion algorithm is used for integrating the features, and the accuracy of the thyroid nodule region is improved. According to the method, the thyroid cancer lymph node metastasis state (non-metastasis, central region metastasis or lateral neck metastasis) is predicted, meanwhile, a two-dimensional interpretability framework of Grad-CAM activation diagram and SHAP value contribution degree analysis is introduced, an intuitive prediction basis is provided for doctors, and the thyroid cancer lymph node metastasis prediction accuracy is remarkably improved.

The invention belongs to the technical field of medical image analysis, and relates to a lesion detection method and system based on multi-scan interactive deformable Mama, and the method comprises the steps: 1, image block embedding; 2, multi-scale feature extraction and interaction in the backbone network are scanned in parallel; 3, feature pyramid optimization based on dynamic weighted scanning fusion; 4, performing multi-scale fusion; according to the invention, through the adaptive scanning network and the deformable scanning mechanism, the characterization problem of the morphological heterogeneity of the oral cancer focus and the pulmonary nodule microstructure feature is effectively solved, the double breakthrough of the detection precision and the calculation efficiency is realized, and an efficient and reliable solution is provided for multi-cancer medical image analysis.

The invention relates to the technical field of artificial intelligence, and provides a gastric cancer risk quantitative scoring method, system and equipment based on artificial intelligence, and the method comprises the steps: recognizing the image type of each image frame in alimentary canal endoscope image data; for the electronic dyeing image frame, identifying a part contour region and an intestinal contour region of the feature part in the image frame, determining an intestinal epithelial metaplasia grading category of the feature part according to an area proportion of the intestinal contour region in the part contour region, and performing electronic dyeing intestinal scoring on the image data; for the white light image frame, gastroscope part types included in the image frame and focus area types of all gastroscope parts are recognized; performing atrophy scoring on the image data according to the position distribution of the focus area of the atrophy type; performing table state scoring on the image data according to whether the plica enlargement, nodular gastritis and diffuse redness focus areas exist or not; and realizing gastric cancer risk quantitative scoring according to the electronic staining intestinal scoring, the atrophy scoring and the epistatic state scoring.

The invention discloses a thyroid ultrasound diagnosis report intelligent generation method based on a multi-mode large language model, and relates to a thyroid ultrasound diagnosis report intelligent generation method. The objective of the invention is to solve the problems of lack of term standardization and insufficient complex focus feature analysis in the prior art. According to the method, a full-flow technical system of double-flow coding, cross-modal alignment, dynamic man-machine cooperation and multi-dimensional evaluation is constructed. Multi-scale feature fusion of a thyroid global form and a nodule ROI region is realized through ResNet-50 and ConvNeXt double-flow coding networks, image-text semantic alignment is optimized by adopting a CLIP symmetry loss function, and training resource consumption is reduced in combination with an LoRA parameter fine tuning technology. A dynamic man-machine collaborative closed-loop mechanism is innovatively introduced, model parameters are iteratively optimized through doctor correction data, and a four-dimensional clinical evaluation system comprising ROUGE-L, BLEU-4, CIDEr and expert blind evaluation is established. The invention belongs to the technical field of medical artificial intelligence auxiliary diagnosis.

The invention discloses a composition for detecting benign and malignant thyroid nodules and a detection method thereof, and relates to the technical field of medical detection, the composition comprises the following components: a DNA / RNA extraction reagent and a fluorescent quantitative PCR reagent; by combining the DNA / RNA extraction reagent and the fluorescent quantitative PCR reagent, nucleic acid can be efficiently and accurately extracted from the thyroid nodule fine needle puncture sample, specific gene mutation and gene fusion are detected through the fluorescent quantitative PCR technology, the accuracy and sensitivity of benign and malignant judgment of the thyroid nodule are remarkably improved, and the method is suitable for clinical application. And a doctor can formulate a treatment scheme earlier and more accurately, and the prognosis of a patient is improved.

The present disclosure provides systems and methods for Al model(s) that are trained to identify characteristics associated with lesions within a blood vessel and provide a suggested procedure associated with the lesion. The Al model may receive, as input, intravascular and / or extraluminal image data associated with the blood vessel and provide, as output, characteristics, e.g., characterizations, associated with the blood vessel. The characterizations may include, for example, form or tissue nature (e.g., microcalcification, punctate, fragment, sheet, nodular, or otherwise), location within the vessel (e.g., intimal, superficial, medial, deep, etc.), size (e.g., length, depth, thickness, etc.), severity, and / or the like. The characterizations may be used as input to the same and / or a different model for providing a suggested procedure associated with the lesion. The suggested procedure may include, for example, orbital atherectomy, intravascular lithotripsy, rotational atherectomy, cutting and / or scoring balloons, and / or the like.

The invention provides computer equipment for executing a sub-solid pulmonary nodule growth prediction method based on CT imageomics, and the computer equipment comprises a memory, a processor and a computer program, and when the processor executes the program, density value extraction is carried out on a sub-solid pulmonary nodule region through multi-stage CT images, the internal structure of a nodule is segmented by adopting a convolutional neural network, and the internal structure of the nodule is obtained; obtaining nodule internal density distribution data from the segmentation result; calculating a cavity expansion rate and an edge density increase rate in unit time by combining the density amplitude data according to a focus characteristic influence degree evaluation result; according to the lesion cavity expansion rate and the edge density growth rate, the malignant progress risk level is judged, and malignant progress time window estimation is obtained; according to the malignant progress time window estimation, the matching degree between the density distribution data and the development speed index is calibrated through clinical feedback data, and sub-solid pulmonary nodule growth prediction output is obtained.

The present application relates to medical teaching aid technical field, especially intelligent feedback type thyroid ablation operation simulation training device. The model includes a simulation person, a cervical vertebra module, a thyroid module and a simulation nodule. The simulation nodule is made of a thermal response material, has a heating element inside, an ablation needle integrated with a temperature sensor, and a control unit triggers heating according to the sensor signal, so that the physical state of the nodule changes and the real ablation effect is simulated. The present application has a simple structure, can provide intuitive visual and tactile feedback, and is used for medical staff surgical skill training and objective examination.

The invention provides a papillary thyroid carcinoma neck lymph node metastasis risk prediction method and system based on blood indexes and TI-RADS grading, and relates to the technical field of medical data analysis. According to the method, an original data set is constructed by obtaining TI-RADS classification, the maximum diameter of nodules, the number of nodules, gender, age and conventional hematology indexes including apolipoprotein B and carcino-embryonic antigen of a patient, characteristic variables are screened by adopting LASSO regression, and an independent prediction risk factor model is established in combination with multi-factor Logistic regression. And further constructing a column graph model, carrying out performance verification through multiple statistical indexes, and deploying the model to a webpage calculator based on a shiyapp to realize convenient output of the individualized risk probability. According to the method, efficient and accurate prediction of the preoperative lymph node metastasis risk is realized, and reliable decision support can be provided for clinic.

The application relates to the field of medical image assisted ablation technology, and provides a thyroid nodule ablation control system based on ultrasound contrast parameters. The system comprises an ultrasound data acquisition module, a contrast parameter analysis module, a blood supply identification module, an ablation strategy generation module, an ablation execution module, a feedback evaluation module, a closed-loop control module and an energy optimization module. By acquiring an ultrasound contrast image of target tissue, perfusion time, perfusion intensity and perfusion sequence parameters are extracted, blood supply arteries or blood supply areas are identified, and a phased ablation strategy is generated, the blood supply area is preferentially ablated, and then main ablation is carried out on the target tissue; at the same time, residual active areas are detected based on contrast feedback, and supplementary ablation is carried out through a closed-loop control mechanism; and ablation parameters are dynamically optimized in combination with a unit volume energy model. The system can improve ablation integrity, reduce the heat sink effect and the risk of intraoperative bleeding, reduce the recurrence rate, and improve energy utilization efficiency.

The invention relates to the field of medical informatics, and provides a biomarker-based thyroid nodule benign and malignant identification method and system. The method comprises the following steps: collecting a serum sample; performing quantitative detection on the multiple markers in the serum sample to obtain concentration data of the multiple markers; inputting the multi-marker concentration data into a pre-constructed probability calculation model to obtain a prediction probability value; and according to a preset diagnosis threshold value and the prediction probability value, judging whether the thyroid nodule is benign or malignant to obtain a thyroid nodule benign or malignant identification result. By integrating multi-marker information, the biological difference between benign and malignant nodules is effectively captured, and the overall efficiency of differential diagnosis is improved.

The invention provides a methylation marker combination for identifying and diagnosing benign and malignant thyroid nodules or diagnosing thyroid cancer. The methylation marker combination comprises methylation TSHR, NIS and TPO genes or fragments thereof. In addition, the invention further provides a thyroid cancer diagnosis product and device based on the methylation marker combination and application of the thyroid cancer diagnosis product and device in thyroid nodule benign and malignant identification and thyroid cancer diagnosis. Whether a thyroid tissue sample or a blood sample is taken as a detection object, the methylation marker combination can realize efficient and sensitive diagnosis of thyroid cancer, and especially has outstanding performance in early thyroid cancer diagnosis, so that the methylation marker combination has a good application prospect. And the kit has important clinical application value and practical significance for early screening and diagnosis of thyroid cancer.

This invention relates to the field of traditional Chinese medicine and natural medicines, and discloses a traditional Chinese medicine composition for treating thyroiditis, nodular goiter, and thyroid nodules, as well as its preparation method and application. The traditional Chinese medicine composition is made from raw materials in parts by weight of 1-30 parts of Prunella vulgaris, 1-30 parts of Taraxacum mongolicum, 1-30 parts of Hordeum vulgare malt, 1-20 parts of Citrus reticulata peel, 1-24 parts of Crataegus pinnatifida, and 1-24 parts of Raphanus sativus seed. It can not only significantly reduce serum TgAb and TPOAb antibody levels, inhibiting the attack of autoimmune response on the thyroid gland from the source, but also effectively reduce lymphocyte infiltration, repair damaged thyroid follicular structure and restore colloid content, thereby reversing immune damage and tissue destruction of the thyroid gland, reducing thyroid nodules, and solving the problems of existing treatments for thyroiditis, nodular goiter, and thyroid nodules that cannot reverse immune damage to the thyroid gland, destruction of follicular structure, and tissue fibrosis.

The invention discloses a combined medicine composition of a thyroid Qixia patch and a selenium yeast tablet and application of the combined medicine composition, and belongs to the technical field of medicines. The composition is composed of a thyroid and astragalus mongholicus summer patch and a selenium yeast tablet, the thyroid and astragalus mongholicus summer patch is prepared by grinding astragalus mongholicus, selfheal, radix clematidis, turmeric, airpotato yam and semen brassicae as raw materials, and adding vaseline to prepare paste. The selenium yeast tablet is used for oral administration and is matched with the thyroid qi-summer patch for external application on the neck, and the treatment course is 3 months. Clinical verifications show that the total effective rate of the composition reaches 87.80%, the composition can effectively improve symptoms such as anterior cervical mass, dysphoria, irritability and the like, reduce the level of serum TPOAb, reduce thyroid and nodule volumes and improve nodule blood flow, the safety is good, the curative effect is superior to that of pure western medicine treatment, and an effective treatment scheme is provided for related diseases.

The application belongs to the technical field of molecular biology and medicine, and discloses a methylation marker for detecting the benignity and malignancy of thyroid nodules and an application. 780 new methylation sites are identified, 273 tumor occurrence and development related genes are associated, and the Fc gamma R-mediated phagocytosis signal pathway is involved. The methylation marker for detecting the benignity and malignancy of thyroid nodules comprises multiple genes and multiple methylation sites. The methylation level of multiple genes and multiple sites is detected, the problem of low and unstable methylation signal of single gene or single site is overcome, and thus the sensitivity and specificity of detection are improved.

The invention relates to the technical field of medical teaching appliances, in particular to an intelligent feedback thyroid ablation operation simulation training device. The model comprises a simulation person, a cervical vertebra module, a thyroid gland module and a simulation nodule block. The simulation nodule is made of a thermal response material, a heating element and an ablation needle integrated temperature sensor are arranged in the simulation nodule, and the control unit triggers heating according to a sensor signal, so that the physical state of the nodule generates observable change, and a real ablation effect is simulated. The device is simple in structure, can provide visual visual and tactile feedback, and is used for surgical skill training and objective examination of medical staff.

A method for determining whether a subject is at risk for having a progressing or high-grade pre-invasive lesion, nodule or small mass, or having a solid malignant tumour is described the method comprising: (i) determining a ratio of activated and / or exhausted T cells:naive and / or resting T cells in a sample of blood obtained from the subject, wherein the determining comprises analysing T cells using cytometry to detect the presence or absence of a panel of biomarkers comprising Ki67 and CD39, or (ii) determining a ratio of activated and / or exhausted T cells:T cells which are not activated and / or exhausted T cells in a sample of blood obtained from the subject, wherein the determining comprises analysing T cells using cytometry to detect the presence or absence of a panel of biomarkers comprising Ki67 and CD39, (iii) determining a proportion of activated and / or exhausted T cells as a percentage of T cells in a sample of blood obtained from the subject, wherein the determining comprises analysing T cells using cytometry to detect the presence of a panel of biomarkers comprising Ki67 and CD39, and / or (iv) determining a proportion of activated and / or exhausted T cells as a percentage of T cells in a sample of blood obtained from the subject, wherein the T cells are CD4 T cells, and wherein the determining comprises analysing T cells using cytometry to detect the presence of a panel of biomarkers comprising FoxP3.

The invention discloses a 3D printing-based thyroid puncture model manufacturing method capable of being trained under the guidance of B-type ultrasound, and relates to the field of medical teaching model manufacturing. The core of the method is that a 3D printing technology and a traditional casting technology are fused, and firstly, a split thyroid shaping mold capable of being customized in a personalized mode is printed through digital design; then, a polyvinyl alcohol-graphite powder composite material with a specific ratio is adopted to simulate thyroid tissues and nodules respectively, so that the high simulation degree of the model on acupuncture handfeel and B-type ultrasonic images is ensured; and then through innovative two-stage casting and a special nodule fixing structure, the precise positioning problem of the suspended nodule in the model is solved. And finally, performing freeze-thaw cycle treatment to obtain a finished product. The high-simulation thyroid model manufacturing method suitable for ultrasonic guided puncture training has the advantages of being low in cost, high in simulation degree and high in individuation.

The invention discloses a marker combination for thyroid nodule risk assessment and application thereof. Based on large-sample multi-omics sequencing data, papillary thyroid carcinoma (PTC) and benign nodules are found to have a common epithelial spectrum origin, epithelial intermediate state cells (EICs) with malignant potential are found in the benign nodules, and typical molecular markers of the EICs are further identified to comprise ZCCHC12, CDLN1 and NPC2. The three genes participate in proliferation and differentiation of cells, the expression in PTC is remarkably up-regulated, and the malignant risk of the benign thyroid nodules can be evaluated by detecting the expression level of the markers in a biological sample. According to the method, a means for recognizing the high-risk benign nodules before malignant transformation occurs is provided for the first time, risk perspectiveness is achieved, and higher specificity and sensitivity are possibly achieved for recognizing the benign nodules with malignant potential.

Disclosed is a method for analyzing a lesion based on a medical image performed by a computing device. The method may includes generating, by using a pre-processing module, an input image of a pre-trained detection module from the medical image. The method may include generating, by using the detection module, a probability value regarding a presence of a nodule in at least one region of interest and first location information about the at least one region of interest, based on the input image. The method may include determining, by using a post-processing module, second location information about a suspicious nodule present in the medical image from the first location information, based on the probability value regarding the presence of the nodule.

The application relates to the technical field of ultrasonic image analysis, and discloses a thyroid nodule evaluation system based on ultrasonic images. The system obtains medical record data and medical examination data of a patient through a multidimensional acquisition module, classifies and forms a data set, analyzes the thyroid function state of each patient through an intelligent evaluation module, generates a function coefficient, analyzes the picture quality of each group of ultrasonic images again, generates corresponding detection data group Jcsj, establishes a unified evaluation standard, quickly screens out key frames from a large amount of ultrasonic image data, has high multidimensional integration efficiency, sets a fixed range threshold value for the intelligent evaluation module, analyzes and generates a nodule volume and a nodule score in combination with a medical data set, and in combination with the function coefficient, the detection data group and the nodule score, evaluates the risk grade of the thyroid nodule and the picture quality of the ultrasonic image of the patient, screens out key frames of the ultrasonic image, and outputs a treatment suggestion; and the intelligent evaluation has high precision.

This application provides a method, system, device, storage medium, and product for assisted localization of pulmonary nodules, relating to the field of pulmonary nodule localization technology. The method includes constructing a preoperative virtual lung model of the patient; acquiring images of the lesion via thoracoscopy; generating an intraoperative dynamic 3D model based on the preoperative virtual lung model and the lesion images; acquiring real-time intraoperative images via thoracoscopy; and combining the intraoperative dynamic 3D model with the real-time intraoperative images to assist in predicting the location of pulmonary nodules in the patient's solid lung, thereby improving the accuracy of pulmonary nodule localization.

This invention provides a method for analyzing the radiomics characteristics of medullary thyroid carcinoma based on ultrasound, relating to the field of image or video recognition or understanding technology. The method includes: obtaining data from thyroid surgeries at various target hospitals to form a backup dataset; filtering the backup dataset to obtain a target dataset; labeling the data in the target dataset with Regions of Interest (ROIs); performing feature extraction and feature filtering on the data in the target dataset to obtain training and validation sets; constructing a target radiomics feature model; calculating radiomics feature scores based on the target radiomics feature model; obtaining a clinical feature model, an ultrasound feature model, a comprehensive model, and a scoring model based on logistic regression analysis; and performing radiomics feature analysis based on the clinical feature model, ultrasound feature model, comprehensive model, and scoring model. This invention solves the problems of low diagnostic accuracy and high requirements for experience of image interpreters in existing technologies for thyroid nodules.

The invention relates to the technical field of thermal ablation, in particular to a thyroid nodule ultramicro-invasive ablation precise puncture positioning method, which comprises the following steps of: acquiring continuous gray frames and extracting tissue gray to complete normalization and phase demodulation to generate phase time data; detecting a brightness peak value according to phase time data to obtain a tip echo, calculating a phase gradient in a neighborhood by using a fixed window to generate a stable domain data set, calculating a spatial range according to a stable domain, extracting a phase change signal along with time, and completing frequency domain dominant frequency extraction and period analysis to generate a period consistent region; according to the method, the continuous image phases are extracted, the time sequence is combined, the needle point recognition stability is enhanced, the echo region is restrained through the brightness peak value and the phase gradient, and the accuracy of positioning is improved. Position judgment is enhanced through spatial range and period analysis, and the guiding precision is improved by combining a three-dimensional distance and a symbol sequence.

The invention discloses a lung nodule diagnosis method based on plasma DNA methylation characteristics and application, and the method comprises the following steps: S1, collecting peripheral blood of a subject in a special cfDNA preservation tube, carrying out centrifugal separation to obtain plasma, extracting cfDNA by adopting an optimized paramagnetic particle method or column extraction method, carrying out quality control on the cfDNA, then carrying out thorough hydrosulphite conversion treatment on the cfDNA, and carrying out purification treatment on the cfDNA to obtain the plasma; unmethylated cytosine is converted into uracil, and methylated cytosine is kept unchanged. The invention is derived from the selection of an early and stable epigenetic marker of DNA methylation, and replaces traditional dependent clinical parameters or mutation signals appearing at a late stage. According to the method, the problem of insufficient discrimination capability (AUClt; 0.60) caused by limited input information of an existing clinical prediction model (such as a MayoClinic model) is directly solved.

This invention relates to the technical field of ultrasound image feature extraction for thyroid nodules, specifically to a method and system for ultrasound image feature extraction of thyroid nodules. The method includes the following steps: acquiring an ultrasound image containing thyroid nodules; performing multi-scale image analysis on the ultrasound image to construct a multi-scale image representation of the ultrasound image; using the multi-scale image representation to identify low-echo regions in the ultrasound image, and combining feature analysis, judgment correction, and spatial relationship verification to determine the acoustic shadowing region in the ultrasound image; performing suppression processing on the acoustic shadowing region, wherein the suppression processing includes unifying the signal within the acoustic shadowing region and softening the boundary of the acoustic shadowing region to obtain an optimized image; identifying the contour of the thyroid nodule based on the optimized image; and quantifying the morphology and internal structure of the thyroid nodule based on its contour. This application can effectively identify and suppress acoustic shadowing regions in ultrasound images.

The present application relates to the technical field of medical data processing, in particular to a kind of lung nodule preoperative virtual positioning system assisted by augmented reality glasses, including memory and processor, the processor executes the computer program stored in the memory, to realize: the construction of lung lobe tubular structure lung lobe tubular structure chart;According to the distance distribution between nodes and blood vessel attribute information, the basic attribute parameter of each edge is obtained, the current surface gripping point and lesion center point are acquired;Obtain transverse attenuation factor and axial projection factor, determine the deformation resistance weight of each edge in combination with basic attribute parameter;According to the deformation resistance weight of the edge accumulated between the nodes corresponding to the current surface gripping point and lesion center point, the deep displacement transmission degree is obtained;According to deep displacement transmission degree and the pulling direction of surgical instrument, the lesion center point position is corrected to obtain the corrected lesion position.The present application ensures that the virtual nodule rendered in AR glasses is accurately matched with the position of deep real lesion.

The invention provides a thyroid nodule auxiliary diagnosis model construction method and system based on multi-modal data and a storage medium. The method comprises the following steps: acquiring multi-modal thyroid nodule medical data; performing classification processing on the thyroid nodule medical data of each mode by using a single-mode classification model to obtain each thyroid nodule intermediate classification result corresponding to the thyroid nodule medical data of each mode; and carrying out weighted fusion on all the thyroid nodule intermediate classification results to obtain thyroid nodule benign and malignant classification results based on the multi-modal thyroid nodule medical data. According to the embodiment of the invention, the single-mode classification model is adopted to perform classification processing on the medical data of each mode, so that the step of converting the multi-mode data into the structured data is omitted, and the data processing efficiency is higher; in addition, the thyroid nodules can be diagnosed, monitored and treated, clinicians are assisted in improving the diagnosis efficiency of the thyroid nodules, and clinical burdens are reduced.

1. The name of the design product: neck protection (graphene). 2. The use of the design product: the design product is used for the treatment of cervical spondylosis and thyroid nodules. 3. The design points of the design product: in shape. 4. The picture or photo that best indicates the design points: perspective view.