89 results about "Thyroid nodular" 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 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 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 application relates to the technical field of data processing, in particular to a thyroid nodule fine-grained automatic identification and classification system based on weak supervision learning, which comprises a server, the server is pre-set with a thyroid fine-grained identification model, the server is used for acquiring an identification image, and a fine-grained identification result output by the thyroid fine-grained identification model according to the identification image; the thyroid fine-grained identification model comprises: a feature pyramid attention module, which is used for processing the identification image according to a feature pyramid attention algorithm; a spatial attention module, which is used for acquiring a binary mask, generating an attention map according to the binary mask, and positioning and discriminating a region; and a multi-network fusion module, which is used for acquiring output results of multiple backbone networks, fusing the output results, and generating a fine-grained identification result. The scheme can solve the technical problem that, when the thyroid nodule is classified in a fine-grained manner in the prior art, the classification accuracy is low due to the multi-scale and multi-network structure of an ultrasonic image.

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 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.

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 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.

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 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.

The invention provides a traditional Chinese medicine composition for treating thyroid nodules, a pharmaceutical preparation and a preparation method thereof, and relates to the technical field of medicines. The traditional Chinese medicine composition comprises the following components: thunberg fritillary bulb, pinellia ternate, curcuma zedoary, polygonum cuspidatum, wild buckwheat rhizome, scutellaria baicalensis, cortex albiziae, honey loquat leaf, bighead atractylodes rhizome, epimedium, Chinese yam and liquorice. The traditional Chinese medicine composition and the pharmaceutical preparation provided by the invention have the effects of reducing phlegm and resolving masses, promoting blood circulation and removing blood stasis, warming and tonifying spleen and kidney, and soothing liver and soothing nerves, and have a good treatment effect on thyroid nodules.

This invention relates to the field of image analysis technology, specifically to an automatic classification method for benign and malignant thyroid nodules based on multimodal ultrasound imaging. The method involves acquiring images of thyroid nodules; given that the invasive growth of cancer cells in malignant nodules can damage cell structure and induce grayscale mutations, the nodule region is segmented and divided into sub-regions. The grayscale similarity of sub-regions is analyzed to quantify local heterogeneity, yielding spatial grayscale performance indicators; then, the correlation between these indicators and the proportion of blood flow pixels is analyzed to establish a structural-blood flow abnormality association model, obtaining the blood flow supply matching degree; further, based on shape and edge grayscale fluctuation analysis, a structural disorder index is obtained, infiltration candidate areas are located, and blood flow is analyzed to obtain peripheral invasive blood flow indicators. Combining the correlation between these two indicators with the blood flow supply matching degree, a structure-blood flow coupling coefficient is obtained; finally, multiple indicators are integrated to obtain a malignancy risk score, and a classification neural network is trained to classify the risk level of samples, assisting doctors in making refined judgments.

The application discloses a kind of based on mixed domain enhancement's thyroid nodule semi-supervised segmentation method and device, it is related to image segmentation technical field.The method includes: constructing semi-supervised segmentation model, including unified bidirectional copy and paste enhancement module, cross-teaching model, patch enhancement module based on information entropy and frequency domain enhancement module based on Fourier transform;Using labeled data and unlabeled data to train the model constructed, by unified bidirectional copy and paste, generate intermediate sample between labeled data and unlabeled data in space domain;Using the uncertainty estimation based on information entropy, exchange low-entropy patch in labeled data and high-entropy patch in unlabeled data;The low-frequency component of labeled data and unlabeled data is exchanged by fast Fourier transform, and the low-frequency prediction is supervised in consistency based on the pseudo-label generated based on full frequency;The thyroid nodule ultrasound image to be segmented is input into the trained segmentation model, and the nodule segmentation result is obtained.The present application can improve segmentation accuracy.

The application discloses a thyroid nodule image classification method based on ultrasound and infrared thermal image multimodal images. The application is based on ultrasound and infrared thermal images, combined with a multimodal learning method, and provides a self-adaptive multimodal hybrid model, which is composed of an intra-modal mixed encoder, a self-adaptive cross-modal encoder and a classification head. The intra-modal mixed encoder can model global features while extracting local features; the self-adaptive cross-modal encoder can formulate personalized modal weights according to different cases, and simultaneously perform information interaction and fusion of inter-modal features; and the classification head classifies the obtained fusion features. The method automatically classifies the thyroid nodule images of a subject based on ultrasound and infrared thermal images of the subject by using an AmmH model, and provides objective and accurate classification results for doctors, so that auxiliary diagnosis is realized.

The invention discloses application of daphnetin in thyroid nodule treatment medicines, relates to the field of medicines, in particular to the technical field of new application of medicines, can be used for thyroid nodule treatment, and has a wide application prospect.

The invention discloses a wearable neck patch device based on thyroid nodule patient noninvasive monitoring, and relates to the technical field of thyroid nodule patient treatment, the wearable neck patch device comprises a monitoring arc plate, the monitoring arc plate is internally provided with a control cavity, one side of the inner surface of the control cavity is fixedly connected with a circuit board, the circuit board is electrically connected with a curved surface display screen, and the curved surface display screen is electrically connected with the control cavity. By means of the device, a thyroid nodule patient can be noninvasively monitored in real time, targeted treatment can be adopted in time when the illness state of the patient changes, the patient does not need to go to a hospital repeatedly for reexamination, even when the patient works, the patient can wear the device to work and conduct monitoring at the same time, and auxiliary rehabilitation treatment can be selectively conducted in a targeted mode; after the thyroid gland patient is recovered, the patient can still use the device, the patient can feel more comfortable, and after relevant health preserving medicine and liquid medicine are placed in the heating cavity, the patient can be helped to preserve health, and the patient can be healthier.

The invention provides a thyroid nodule ultrasonic image feature extraction method and system, and the method comprises the steps: extracting nodule contours of a to-be-processed thyroid nodule ultrasonic image in different receptive fields, and determining the recognition ambiguity of each nodule contour; extracting dominant nodule contours of the thyroid nodules based on the nodule contours under different receptive fields, and constructing identification guide coefficients of implicit nodule edges in the thyroid nodules by combining contour salient points in the dominant nodule contours with all identification ambiguity; a thyroid nodule area in the thyroid nodule ultrasonic image is segmented into a radial segmentation feature map in the radial direction according to the recognition guide coefficient and the visual target spot of the dominant nodule contour; based on the radial segmentation feature map, edge enhancement is carried out on the recessive nodule contour in the thyroid nodule, and the fine-grained contour feature of the thyroid nodule is obtained. According to the technical scheme provided by the invention, the detail contour features of the thyroid nodule in the thyroid nodule ultrasonic image can be extracted under the influence of the recessive edge contour with weak contrast.

The present application relates to the technical field of traditional Chinese medicine, and in particular, to a traditional Chinese medicine composition, a method for preparing same, and use thereof in preparing a medicament for preventing and treating a thyroid disease. The traditional Chinese medicine composition consists of Ranunculi Ternati radix, Taraxaci herba, Cyperi rhizoma, and Semiaquilegiae radix. The method comprises: mixing and crushing formulation amounts of Ranunculi Ternati radix, Taraxaci herba, Cyperi rhizoma, and Semiaquilegiae radix; or extracting formulation amounts of Ranunculi Ternati radix, Taraxaci herba, Cyperi rhizoma, and Semiaquilegiae radix. The compounding of the four traditional Chinese medicines, Ranunculi Ternati radix, Taraxaci herba, Cyperi rhizoma, and Semiaquilegiae radix, can significantly treat hypothyroidism, thyroid nodules, and the like caused by insufficient thyroid hormones. Compared with the prior art, the traditional Chinese medicine composition features clear ingredients, good safety, and better therapeutic effects, providing technical support for the treatment of thyroid diseases with traditional Chinese medicines.

The application provides a thyroid nodule clinical feature filling and benign and malignant prediction optimization method and device, including the following steps: obtaining initial binning results by binning each kind of thyroid clinical feature based on a decision tree; obtaining optimal binning results by rebinning each kind of thyroid nodule clinical feature; taking the malignant thyroid nodule prevalence rate in each bin as a bin element feature, taking the bin element features of all kinds of thyroid nodule clinical features of multiple patients as a training sample set, training a preset nodule prediction architecture by using the training sample set to obtain a nodule prediction model; and predicting the malignant thyroid nodule prevalence probability of a patient to be tested by using the nodule prediction model. The importance parameters of different thyroid nodule clinical features are used for optimal binning, so that the data complexity is reduced, the key information is highlighted, and the malignant thyroid nodule can be more accurately predicted.

The invention discloses a three-dimensional positioning method for an ultrasonic medical diagnosis position. The three-dimensional positioning method comprises the following steps: S1, establishing a three-dimensional coordinate system taking a neck anatomical mark as a reference; s2, multi-plane ultrasonic image acquisition and nodule feature point extraction; s3, reconstructing a nodule three-dimensional model through coordinate registration; s4, recognizing the puncture needle in real time and calculating the three-dimensional coordinates of the needle tip; s5, a safe puncture path is planned, and deviation is corrected in real time; and S6, determining that the needle tip is in place and completing positioning. By establishing a neck fixing three-dimensional coordinate system, adopting three-plane ultrasonic image registration to reconstruct a nodule three-dimensional form, tracking the three-dimensional position of a puncture needle in real time, automatically planning a safe path and correcting deviation, precise puncture is achieved, an expensive volume probe is not needed, the positioning precision is high, operation is easy, safety is high, and the method is suitable for popularization and application. The thyroid nodule puncture success rate can be remarkably improved, complications are reduced, and clinical wide popularization is facilitated.

The present technology relates to methods for determining whether a patient having thyroid nodules with indeterminate cytology will benefit from diagnostic surgery, e.g., lobectomy. These methods are based on screening a patient's thyroid nodules and detecting alterations in target nucleic acid sequences corresponding to a specific set of thyroid cancer-related genes. Kits for use in practicing the methods are also provided.

The application provides a kind of construction and application of thyroid nodule benign and malignant classification model based on mask guide, the present application simultaneously inputs thyroid ultrasound original map, lesion mask and patient clinical structured information, designs anatomical boundary enhancement network, generates lesion anatomical boundary graph by mask inflation, erosion operation, adopts double-branch deep convolution to strengthen internal and boundary features of nodule respectively;Propose mask conditional attention mechanism, fuse three types of channel descriptors to weaken irrelevant background interference, and build BRM bidirectional mutual feedback modulation module, realize image and structured feature adaptive mutual calibration fusion through bidirectional gate weight, can accurately extract nodule boundary key diagnostic features, improve the defects of low contrast of ultrasound image, multi-modal information fusion imbalance, improve the accuracy of nodule benign and malignant identification.

This article discloses a method for identifying the nature of thyroid nodules, including detecting the DNA methylation level in a sample selected from the following regions (1) and (2): (1) fragments of one or more of the following genes: COL23A1, ILDR2, DHRS3, KIF1A, GDNF, TBX18, and (2) nucleic acid regions within 10 kb upstream and downstream of the genes (1).

The current disclosure provides, inter alia, method of determining benign nodules from thyroid cancer in a subject that is found to have a thyroid nodule, method of treating thyroid cancer in a subject detected to have thyroid cancer by the method of the current disclosure, compositions for determining benign nodules from thyroid cancer in a subject, and kits including reagents and composition for determining benign nodules from thyroid cancer in a subject.