32 results about "Cervical lesion" patented technology

The invention discloses a cervical lesion intercellular relation modeling and analysis system based on a graph neural network, and the system comprises a medical image collection module which is used for collecting a digital image of a cervical tissue pathological section or a cervical TCT slide; the cell detection and segmentation module is used for extracting spatial position information and morphological characteristics of cells; the cell feature extraction module is used for extracting and fusing the spatial position, morphology, texture and biological marker features of the cells; the cell relation graph construction module is used for constructing a heterogeneous cell relation graph with cells as nodes and inter-cell relations as edges; the graph neural network analysis module is used for carrying out feature learning and modeling on the heterogeneous cell relation graph; the intelligent auxiliary diagnosis module is used for generating auxiliary diagnosis suggestions; and the data management and automatic control module is used for realizing automatic control and case data management of the whole process of the data. The intelligent and automatic level of cervical lesion cell analysis can be comprehensively improved, and the accuracy and efficiency of diagnosis are improved.

The invention relates to the technical field of medical image processing, in particular to a gynecological endoscope image intelligent analysis and cervical lesion precise diagnosis system. Comprising an image enhancement module, a differential geometric feature extraction module, a topology preserving manifold learning module, a curvature-blood vessel correlation analysis module, a biopsy point accurate positioning module, a real-time intelligent auxiliary diagnosis module, a clinical feedback module and a self-adaptive optimization module. Micro morphological change features are extracted through multi-scale curvature analysis; a topology sensitive encoder and a manifold alignment decoder are adopted, and a key topology structure is kept; establishing a correlation model of the tissue surface curvature change and the blood vessel morphology, and analyzing differential morphological characteristics; determining an optimal biopsy position based on the comprehensive characteristics; according to the method, the diagnosis result and basis are generated, visual display is provided, the detection rate of cervical lesions, especially early minimal lesions, is remarkably increased, the missed diagnosis rate is reduced, and multi-point biopsy is reduced.

The invention relates to the technical field of image processing, and discloses a cervical lesion prediction method and device based on image processing, and the method comprises the steps: carrying out the imaging of a cervical surface through a colposcope, and obtaining a cervical surface image; analyzing the cervical surface image, and positioning a lesion area; configuring pose parameters of an ultrasonic probe according to the position of the lesion area, so that the ultrasonic probe is aligned with the lesion area for scanning, and an ultrasonic image is obtained; the ultrasonic image is analyzed, and the tissue infiltration depth and the blood flow resistance index of the lesion area are obtained; and predicting cervical lesions according to the tissue infiltration depth and the blood flow resistance index. According to the cervical lesion prediction method and device based on image processing, the colposcope and the ultrasound are combined to detect the cervical lesion in the same process, and the detection accuracy and efficiency are improved.

The invention belongs to the technical field of medical supplies, and particularly relates to an adjustable cervix uteri multi-point micro-injection device which comprises a guide cylinder, an adjusting mechanism is mounted in the guide cylinder, and an injection needle is mounted on the side, extending into a human body, of the adjusting mechanism; the other side of the adjusting mechanism is connected with the carry control mechanism, the rotation control mechanism and the deflection control mechanism through a first connecting rod, a second connecting rod and a third connecting rod. The other side of the adjusting mechanism is further connected with a connecting hose, and the other end of the connecting hose is connected with an injector. Wherein the adjusting mechanism comprises a carry mechanism, a rotating mechanism and a deflection mechanism, the situation that the device pierces other parts of the genital tract of a patient to cause injury before reaching the cervical lesion part can be avoided, and the injection needle can be deflected towards different parts through the adjusting mechanism; according to the device, the injection needle can accurately pierce a diseased region for injection under the condition that the adjustment range in the genital tract of a patient is minimum.

A cervix uteri cell image enhancement method based on a generative adversarial network comprises the following steps: carrying out statistical analysis on a cervix uteri cell image data set, and confirming that a high category imbalance problem exists; according to morphological characteristics and clinical importance of cells of different lesion categories, designing differentiated enhancement strategies and target quantities; for extremely scarce high-risk categories, a StyleGAN2-ADA model constrained by medical knowledge is adopted for generation, and for other categories, a traditional enhancement method combining CLAHE, elastic deformation and the like is adopted; and performing quality control through Masked-SSIM and Med-FID medical image evaluation indexes and pathology expert auditing to obtain a high-quality enhanced image. According to the method, the problem of class imbalance in cervical cell image data is effectively solved, the recognition performance of a deep learning model on high-risk cervical lesions is remarkably improved, and the method has important clinical auxiliary diagnosis value.

The application discloses a colposcope cervical lesion segmentation method, system, device and medium based on an aceto-white attention map, and the method comprises the following steps: acquiring a training data set and a test data set; a cervical lesion segmentation model based on a full convolutional neural network, the model comprising two inputs of an aceto-stained colposcope image and an aceto-white attention map; iteratively training the cervical lesion segmentation model based on the training data set; evaluating the cervical lesion segmentation model after training by using the test data set, and the cervical lesion segmentation model meeting the performance requirement can be used for subsequent colposcope cervical lesion area prediction. The application constructs an aceto-white attention map through a pre-aceto-stained colposcope image and a post-aceto-stained colposcope image, and filters interference information such as background in a convolutional coding block output feature map through a spatial attention mode, so that the precision of the full convolutional neural network segmentation model in the colposcope cervical lesion area segmentation task is effectively improved.

1. The name of the design product: graphical user interface of cervical image analysis system for electronic device. 2. The use of the design product: for electronic device. 3. The design points of the design product: the graphical user interface displayed on the electronic device. 4. The picture or photo that best shows the design points: front view. 5. The rear view, left view, right view, top view, and bottom view do not contain design points, and the rear view, left view, right view, top view, and bottom view are omitted. 6. The use of the graphical user interface: the graphical user interface is applied to the cervical image analysis system of the electronic device, mainly used to realize the loading, viewing, and intelligent analysis result presentation of cervical images, and assist medical personnel to quickly and accurately perform cervical lesion screening and diagnosis. 7. The human-computer interaction mode of the graphical user interface: the front view is the main interface of the cervical image analysis system by default, and its use is referred to the use state reference figure 1; the "unanalyzed" button on the main view interface is clicked to enter the change state figure 1, and its use is referred to the use state reference figure 2; the "confirm" button on the change state figure 1 interface is clicked to enter the change state figure 2, and its use is referred to the use state reference figure 3. 8. Other circumstances that need to be explained: the "X" in each view represents variable text and / or numbers, and the gray blocks in each view are content pictures or variable content.

This invention belongs to the field of medical image processing technology and discloses an automatic annotation method and system for cervical lesion areas in colposcopy. The method includes: converting the cervical RGB image to the CIELAB color space to construct an acetic acid sensitivity index map to enhance color difference contrast; inputting the sensitivity index map and the original image into a dual-stream encoding and decoding segmentation network to accurately segment the conversion area; extracting three complementary features within the conversion area: acetic acid reaction features, vascular morphology features, and iodine staining spatial features; outputting four probabilities (normal, CIN1, CIN2, and CIN3) by a multi-branch hierarchical classifier and adjusting the segmentation threshold accordingly; and marking each level of area with different colored contours and indicating the biopsy location with arrows.

1. The name of the design product: inherent fluorescence early cervical lesion diagnostic instrument. 2. The use of the design product: early cervical lesion diagnosis. 3. The design points of the design product: the combination of shape and color. 4. The picture or photo that best indicates the design points: perspective view. 5. The design claimed contains color.

The application relates to the field of synthetic MRI identification technology, in particular to a method for identifying cervical squamous cell carcinoma and cervical adenocarcinoma by using synthetic MRI. The method comprises the following steps: scanning a cervical lesion area, obtaining local gray scale tracks of structural weighted images, lesion signal weighted images and diffusion weighted images, fitting the structural weighted images and the lesion signal weighted images into nonlinear tracks, reconstructing virtual control MRI images, projecting the virtual images to the scanning area, identifying the main direction extension mode and the secondary direction distortion mode of the lesion, constructing diffusion restriction curves in combination with the diffusion weighted images, determining the multi-distribution evolution curves of the lesion, synchronously enhancing different weighted images according to the multi-distribution evolution curves, generating global enhancement MRI data, and identifying the cervical lesion area. The application realizes clearer lesion identification criteria, improves the contrast and resolution of the images, and enhances the sensitivity of the lesion detection.

The invention relates to the technical field of medical artificial intelligence, in particular to a YOLOv8-based multi-modal colposcope image fusion and classification method, system and medium, and the YOLOv8-based multi-modal colposcope image fusion and classification method comprises the following steps: collecting three modal images from a cervical region of the same patient, size normalization and pixel value normalization preprocessing are respectively carried out on the three modal images; the three modal images comprise a collected original image, an acetic acid white image and an iodine test image; respectively and independently inputting the preprocessed three modal images into a shared YOLOv8 backbone network so as to extract depth feature vectors of corresponding modals; constructing a fusion feature vector by using the three extracted depth feature vectors; and inputting the fusion feature vector into a lightweight full-connection network, and outputting an LSIL / HSIL dichotomy probability through a Softmax activation function to complete cervical lesion classification. The technical scheme has the advantage that the cervical lesion classification accuracy is improved through multi-modal image fusion.

The invention provides a cervical lesion thermodynamic diagram prediction method and system based on pathological base model fine tuning, a storage medium and a program, and relates to the technical field of medical pathological diagnos.The method comprises the steps that S10, a pre-trained Prov-GigaPath tissue pathological base model is adopted to extract pathological feature vectors of a cervical tissue panoramic digital slice image; s20, executing dichotomy mapping according to the pathological feature vectors, and generating positive probabilities of the sub-regions; s30, generating a highly suspicious sub-region set according to the positive probability of each sub-region; and S40, executing five-classification prediction according to the height suspicious sub-region set, and generating lesion level probability distribution corresponding to each height suspicious sub-region. Compared with the prior art, the method has the following beneficial effects: 1, two-classification and five-classification tasks are decoupled, so that the model complexity is reduced; secondly, fine-grained distinguishing of CINI-III and canceration is achieved through a five-classification grading framework; thirdly, by embedding an uncertainty quantification mechanism, a lesion grading result and model confidence degree evaluation are synchronously output.

The invention discloses a marker and a probe composition for early diagnosis of high-grade cervical lesions and cervical cancer and application of the marker and the probe composition. The marker is a PDE4B gene. According to the present invention, with the application of the marker, the methylation state of the gene can be sensitively and specifically detected so as to be used for the detection of the cervical exfoliated cell DNA, and the composition is used for the screening of the asymptomatic population in the non-invasive manner so as to reduce the harm caused by the invasive detection; the composition has higher sensitivity and accuracy, and can realize real-time monitoring.

This invention discloses a method and apparatus for cervical lesion decision-making based on heterogeneous skill invocation and reinforcement learning. Its core lies in constructing a meta-controller driven by reinforcement learning and a decoupled heterogeneous intelligent agent skill library. The skill library encapsulates feature extraction and clinical logic into independent skills such as multi-instance learning visual perception, retrieval enhancement guide alignment, and safety backoff. The meta-controller models clinical reasoning as a Markov decision process, dynamically outputting skill scheduling instructions based on the slot state of the evidence graph and the model's cognitive uncertainty. This invention employs an action masking mechanism and a joint reward function including pathological consistency, multi-instance frame selection concentration, and invocation cost penalties to optimize the meta-controller's offline strategy, and introduces behavioral cloning constraints to inhibit out-of-distribution exploration. Finally, it synchronously outputs disease risk prediction and a traceable clinical evidence chain composed of structured skill invocation trajectories, achieving highly transparent and secure medical assistance decision-making.

Embodiments of the present application relate to the technical field of examination result analysis, and provide a cervical lesion related examination result analysis method and apparatus, a device, and a medium. The method comprises: receiving a case report picture uploaded by a current user terminal, and reading case data in the case report picture; acquiring prediction result information corresponding to the case data on the basis of a current prediction model, and selecting optimal expert information on the basis of the prediction result information; pushing the case data and the prediction result information to an expert terminal corresponding to the optimal expert information, and receiving a final clinical analysis result fed back by the expert terminal; and sending the final clinical analysis result to the current user terminal corresponding to a current user. The present application sends a final clinical analysis result to a current user terminal, so that a current user can conveniently check the final clinical analysis result, and choose whether to perform further pathological examination on the basis of the final clinical analysis result, so that the rationality of medical resource use is improved.

This invention discloses a portable colposcope device for cervical lesion screening, belonging to the field of medical device technology. It includes a multi-axis support assembly, a colposcope assembly, a support assembly, and a mobile PC platform. The multi-axis support assembly achieves precise positioning of the colposcope assembly throughout space through five-axis coordination. The support assembly achieves stable fixation through a combination of mechanical limiting and vacuum adsorption. The colposcope assembly is equipped with an electric telescopic rod for fine-tuning the focus. The mobile PC platform features a centralized control device and uses an AI analysis module combined with a case database to assist in diagnosis. This device features a modular design for easy assembly and disassembly, good portability, simple operation, and high diagnostic efficiency and accuracy, making it suitable for various scenarios such as primary healthcare and portable screening.

The application relates to an image language fusion prediction learning method for cervical cytology unbalanced data, and relates to the technical field of computers. The method comprises the following steps: acquiring a cervical cytology whole slice image, and cutting the cervical cytology whole slice image into a plurality of patch images; detecting the plurality of patch images to screen a plurality of suspicious positive cell images from the plurality of patch images; acquiring clinical text corresponding to the cervical cytology whole slice image; extracting a plurality of second image features related to the clinical text from first image features of the plurality of suspicious positive cell images; fusing the plurality of second image features and text features of the clinical text to obtain image language fusion features, and predicting a cervical lesion category to which the cervical cytology whole slice image belongs based on the image language fusion features. The method can improve the prediction accuracy of the cervical lesion category.

The invention relates to the field of molecular biological detection, in particular to the field of cervical cancer detection. The invention provides a composition for detecting cervical cancer and high-grade cervical lesions. The composition comprises a detection reagent for detecting the methylation level of the following regions: a region shown as SEQ ID NO: 1 in a ZNF671 gene; the OTX1 gene is a region as shown in SEQ ID NO: 2. Meanwhile, the invention further provides a kit comprising the composition and application of the composition, and the composition and the kit can be used for clinically detecting cervical cancer and cervical high-grade lesions with high sensitivity and high specificity.

The application discloses a cervical cell detection method based on multi-scale space information and relates to the technical field of medical images. The application combines the advantages of high speed and high precision of Sparse R-CNN, the extraction ability of a multi-scale space information extraction branch and a channel attention module for space features and channel features, and better detection performance is obtained, so that the problem of insufficient detection precision of existing cervical lesion cells is solved.

The invention discloses a cervical lesion auxiliary diagnosis method, device and equipment and a storage medium. The method comprises the following steps of physical perception data preprocessing, heterogeneous double-flow feature coding, evidence uncertainty quantification, uncertainty gating fusion, boundary perception decoding and reconstruction and intelligent diagnosis result output. According to the cervical lesion auxiliary diagnosis system, the leading edge evidence theory, the heterogeneous neural network architecture and the advanced geometric constraint loss are fused, substantive theoretical innovation is achieved on the algorithm level, the safety of clinical diagnosis can be remarkably improved, and the tiny focus detection rate is increased.

The utility model relates to the technical field of medical instruments, in particular to a cervix uteri medicine applying device which comprises a syringe, a protective tube, a spray head, a liquid inlet tube, a piston, a push rod and an operating ring, a through hole is formed in one side of the syringe, the protective tube is detachably connected with the syringe and located in the through hole, the spray head and the protective tube are integrally designed, spray holes are evenly distributed in the spray head, and the liquid inlet tube is connected with the piston. The liquid inlet pipe is communicated with the syringe and located outside the syringe, the piston is slidably connected with the syringe and located in the syringe, the push rod is arranged on the side, away from the protective pipe, of the piston, and the operation ring is arranged at the end, away from the piston, of the push rod. The detachable protective tube is arranged in the through hole of the syringe, and the protective tube and the spray head are integrally designed, so that after medicine application is completed, the protective tube only needs to be detached from the through hole of the syringe to be discarded, the whole medicine application device does not need to be discarded together, and the use cost of the medicine application device is reduced.

The present invention relates to the field of image processing technology, and more specifically to a method for grading and discriminating cervical lesions based on deep learning, comprising: obtaining a plurality of lesion representation areas from a collected cervical image; analyzing the degree of irregularity and edge abruptness to obtain a reflective interference index for each lesion representation area; dividing each lesion representation area to obtain an internal closed area; analyzing the tubular appearance to obtain blood shape diffusion; obtaining blood accumulation appearance based on grayscale uniformity; obtaining a blood interference index for each lesion representation area based on the blood shape diffusion and blood accumulation appearance; constructing a multidimensional feature vector for each lesion representation area; and training a deep learning model to perform cervical lesion grading and discrimination. The present invention aims to address the problem of errors caused by reflection and blood interference in cervical images when training a cervical lesion grading and discrimination model using deep learning, thereby improving the recognition accuracy of the model.

The invention discloses a cervical lesion cast-off cell or mass detection method based on a YOLOv10 network model, and relates to the technical field of artificial intelligence and medical image processing. According to the method, the detection capability of multi-scale targets is enhanced, the features of cells of different sizes can be captured at the same time through a simplified global pooling information extraction module, and the recognition robustness of pathological cells of different shapes and sizes is remarkably improved; through a multi-scale space attention module guided by a channel, key features are dynamically enhanced, background interference is inhibited, the features of overlapped cells are effectively'decoupled ', and the missing detection rate and the false detection rate in a dense area are remarkably reduced; core modules of the model all adopt lightweight design, the detection performance is improved on the premise that the calculation cost and the parameter quantity are not remarkably increased, and the method is suitable for clinical screening scenes needing high-throughput processing and has clinical popularization potential.

The invention relates to the field of molecular biological detection, in particular to the field of cervical cancer detection. The invention provides a composition for detecting cervical cancer and high-grade cervical lesions. The composition comprises a detection reagent for detecting the methylation level of the following regions: a region shown as SEQ ID NO: 1 in a ZNF671 gene; the NPY gene is a region as shown in SEQ ID NO: 2. Meanwhile, the invention further provides a kit comprising the composition and application of the composition, and the composition and the kit can be used for clinically detecting cervical cancer and cervical high-grade lesions with high sensitivity and high specificity.

The invention relates to the technical field of medical sampling, and discloses a sampling device for gynaecology and obstetrics, which comprises a suction tube, a piston is slidably arranged in the suction tube, the top of the piston is connected with a piston rod, the piston rod penetrates out of the top of the suction tube, a suction handle is fixed at the free end of the piston rod, the bottom of the suction tube is communicated with a suction tube, and a sleeve is sleeved outside the suction tube. The inner wall of the top of the sleeve is slidably connected with the suction cylinder, a vertical sample suction channel is arranged at the bottom of the sleeve, the bottom end of the suction pipe is slidably connected into the sample suction channel, a sample outlet handle is arranged at the top of the sleeve, and cutters are horizontally slidably arranged at the positions, on the two sides of a port of the sample suction channel, of the bottom of the sleeve and connected with a driving assembly. According to the invention, the problem that the sample is easy to pollute and drop in the existing sampling mode of vulva lesions and cervical lesions can be solved.

The utility model discloses a cervical lesion positioning device which comprises a positioning needle and a sleeve. The sleeve is movably arranged on the positioning needle in a sleeving mode, a plurality of piercing parts are arranged at the end, away from the tip end of the positioning needle, of the sleeve in the circumferential direction, and an inclined face is arranged at the end, close to the tip end of the positioning needle, of the sleeve. The upper end of the positioning needle extends to the outer side of the sleeve, and the upper end of the positioning needle is sleeved with a needle cap extending to the piercing part. The positioning device is simple in structure and convenient to use, sampling operation can be facilitated by puncturing the positioning device into cervical tissue, meanwhile, the cervix sampling position can be identified, and the accuracy of case detection results is improved.

The invention discloses an HPV therapeutic apparatus for cervical lesions, and relates to the technical field of medical instruments, the HPV therapeutic apparatus comprises a therapeutic apparatus body, and an anti-HPV gel storage tank for storing anti-HPV gel is fixedly mounted on the therapeutic apparatus body; the therapeutic apparatus body and the anti-HPV gel storage tank are connected with an injection connector used for injecting anti-HPV gel into a cervix area through an image wire, a heating wire and a gel conveying hose respectively, the injection connector comprises an injection module, and the injection module is sleeved with a protection module used for protecting the injection module. During use, body fluid of a patient can be effectively isolated through the closed matching of the gluing elbow and the dustproof groove of the elbow of the protective sleeve in the pretreatment stage of the injection joint and the sealing effect of the water retaining ring between the glue injection sleeve and the protective sleeve, and the patient can be prevented from falling off. The injection part is prevented from being polluted and the medicine outlet is prevented from being blocked.

The invention relates to the technical field of synthetic MRI identification, in particular to a method for identifying cervical squamous cell carcinoma and cervical adenocarcinoma through synthetic MRI. The method comprises the following steps: scanning a cervical lesion area, obtaining local gray tracks of a structure weighted image, a lesion signal weighted image and a diffusion weighted image, fitting the structure weighted image and the lesion signal weighted image into a nonlinear track, reconstructing a virtual contrast MRI image, projecting the virtual image to the scanning area, and obtaining a non-linear track. The method comprises the following steps of: identifying a main direction expansion mode and a secondary direction distortion mode of a focus, constructing a diffusion limited curve by combining diffusion weighted images, determining a multi-distribution evolution curve of the focus, synchronously enhancing different weighted images according to the multi-distribution evolution curve, and generating global enhanced MRI (Magnetic Resonance Imaging) data so as to identify a cervical focus area. According to the invention, a clearer lesion identification reference is realized, the contrast ratio and the resolution ratio of the image are improved, and the sensitivity of lesion detection is enhanced.

The invention relates to the technical field of virus infection treatment, in particular to a traditional Chinese medicine preparation for treating cervical high-risk HPV persistent infection and application of the traditional Chinese medicine preparation. The traditional Chinese medicine composition comprises the following components in parts by weight: 6-30 parts of radix aconiti carmichaeli (black prepared common monkshood daughter root) (decocted first), 3-15 parts of ginseng, 9-60 parts of polyporus umbellatus, 6-30 parts of fructus cnidii, 6-30 parts of fried semen brassicae, 6-30 parts of notopterygium root, 6-24 parts of radix bupleuri, 6-30 parts of fried green tangerine peel, 6-30 parts of motherwort and 6-30 parts of angelica sinensis. According to the constitution and syndrome differentiation of high-risk human papilloma virus (HR-HPV) persistent infection patients, a traditional Chinese medicine prescription is prepared on the basis of the traditional Chinese medicine yang-warming, cold-dispelling and dampness-eliminating theory, the yang-warming, cold-dispelling and dampness-eliminating treatment prescription is used for treating the persistent HPV infection and mild cervical lesion patients, and the traditional Chinese medicine composition can be used for treating the persistent HPV infection and mild cervical lesion patients on the basis of improving the internal environment of the body of the patient and boosting the healthy qi (autoimmunity). Therefore, evil (pathogenic microorganisms) are driven out.

The invention provides an application of human serum apolipoprotein D in cervical lesion screening, provides an application of a reagent for detecting the human serum apolipoprotein D in preparation of a cervical lesion diagnosis or screening kit, and improves the screening rate and popularization rate of cervical lesion screening.