47 results about "Digestive Tumor" patented technology

The invention relates to the technical field of medical image processing, in particular to a multimodal-based digestive tract tumor lesion image segmentation method and segmentation system. The method comprises the following steps: acquiring an alimentary canal tumor lesion image, and extracting an alimentary canal tumor ultrasonic image; evaluating the tumor invasion depth based on the digestive tract tumor ultrasonic image; performing focus three-dimensional visual modeling according to the tumor invasion depth to obtain a digestive tract tumor focus model; extracting a tumor tissue pathological image according to the digestive tract tumor lesion image; performing tumor region segmentation based on the tumor tissue pathological image to obtain digestive tract tumor region data; performing tissue arrangement anomaly detection based on the digestive tract tumor region data to obtain tissue arrangement anomaly data; and calculating a tissue arrangement disorder index according to the tissue arrangement abnormal data and the digestive tract tumor area data. According to the invention, the tumor identification accuracy and the malignant region segmentation precision are improved based on the medical image processing technology.

The invention discloses application of a gene marker in early screening of esophagus, stomach and intestine multiple cancer species, an early screening model construction method and a detection device, and belongs to the technical field of early noninvasive detection of digestive tract tumors. By analyzing the whole genome characteristics of circulating free DNA in peripheral blood, a novel multi-cancer-species screening system is established. On the basis of low-depth whole genome sequencing data, molecular markers in three dimensions, namely a genome copy number variation mode, a DNA fragment distribution characteristic with a specific length and an epigenetics signal of a transcription initiation region, are emphatically detected. An advanced converter neural network architecture is adopted, and the model can efficiently capture complex feature association in a whole genome range through a specific self-attention mechanism. The model design particularly considers the particularity of genome data, introduces an adaptive position coding system, and accurately reflects the spatial distribution relationship of DNA fragments on chromosomes. Therefore, the system can still maintain excellent detection performance under extremely low sequencing depth.

The invention provides Eubacterium mucilaginosus E11405 and an application thereof. The invention provides Eubacterium mucus E11405, which is preserved in the China General Microbiological Culture Collection Center (CGMCC), and the preservation number of the Eubacterium mucus E11405 is CGMCC No.31231. The invention further provides a preparation method of the Eubacterium mucus E11405. The inventor of the application studies the effect and mechanism of the Eubacterium mucus E11405 in relieving the mouse colorectal cancer, and the result shows that the Eubacterium mucus E11405 has a remarkable relieving effect on the mouse colorectal cancer, and can be used as a probiotic preparation for relieving the colorectal cancer. The Eubacterium mucilaginosus E11405 provides a new strategy for prevention and treatment of colorectal cancer-based digestive tract tumors, has potential clinical application prospects, and is expected to become an effective medicine for treating colorectal cancer-based digestive tract tumors.

The present application relates to the technical field of small molecule drugs, in particular to a isoquinoline drug and its application in improving or treating digestive tract tumors, and aims to provide a compound, a pharmaceutical composition containing the compound and its application in treating colorectal cancer and gastric cancer, and provides a 3,13-position substituted berberine derivative, the drug itself has less toxicity and does not affect the growth of normal human cells, and has a good application prospect in the development of novel antitumor drugs, especially in the development of anti-digestive tract tumor drugs.

The invention relates to the technical field of artificial intelligence, and provides a digestive tract tumor non-invasive evaluation system and method based on an artificial intelligence technology, and the method comprises the steps: carrying out the recognition of a lesion position and a digestive tract part of a digestive endoscopy image; guiding a confocal laser microendoscope to perform targeted biopsy on the central position and / or the edge position of the focus; lesion classification identification is carried out on the confocal endoscope image; when it is determined that the lesion exists, an ultrasonic endoscope is guided to conduct ultrasonic scanning on the lesion position; performing focus size and focus infiltration depth identification on the ultrasonic endoscope image; generating a question text based on multi-modal data according to the lesion position, the alimentary canal part, the lesion category, the lesion size and the lesion infiltration depth, retrieving an answer from a preset vector database according to the question text, filling a prompt template with a retrieval result and the question text, and inputting the retrieval result and the question text into an intelligent question and answer language model to generate an alimentary canal tumor assessment result, and non-traumatic evaluation and auxiliary diagnosis of digestive tract tumors are realized.

The invention discloses an auxiliary method for clinical early diagnosis of digestive tract tumors, and relates to the technical field of tumor risk assessment and genome data processing, and the auxiliary method comprises the following steps: carrying out standardization, coding and missing value processing on input data, and converting gene mutation, gene expression and clinical data from different sources into a uniform format; the contribution of gene mutation to tumorigenesis is reflected by combining mutation frequency, expression quantity and nonlinear relationship; capturing an interaction effect between gene mutations to perform component analysis and dimension reduction; measuring the similarity between the genes, optimizing interaction effect calculation between the genes, and evaluating the tumor risk of the patient; and classifying the tumor risk of the patient, adaptively optimizing and dynamically adjusting a mechanism, and dividing the tumor risk. According to the method, through multi-dimensional data processing, nonlinear regression and interaction effect modeling, contribution of gene mutation to the tumor risk is accurately evaluated, the accuracy and individuation of tumor risk prediction are improved, and the method has high clinical application value.

The invention provides a digestive tract tumor detection method and system, relates to the field of medical image detection, and solves the technical problem of low accuracy of tumor boundary detection and automatic positioning in a digestive tract tumor image acquisition process in the prior art. The method comprises the following steps: taking a pan-tumor region image as a training sample of a binary decision tree algorithm, constructing an objective function based on the training sample to obtain a first objective function value, and obtaining a depth threshold value and an optimal classification point of the training sample; optimizing the optimal classification point based on the candidate feature sound to obtain a second objective function value; an unknown digestive tract tumor image is accessed, image points of the digestive tract tumor image are marked through a trained binary decision tree algorithm and a regression forest algorithm, the position distribution probability of the image points is generated, a position distribution thermodynamic diagram is generated based on the position distribution probability, and a tumor core area is obtained through mean shift. And completing the separation of the tumor region and the non-tumor region. The application is used in the digestive tract tumor detection process.

The invention discloses a diphosphonic acid manganese nanoparticle, a preparation method thereof and application of the diphosphonic acid manganese nanoparticle in tumor treatment. The preparation method comprises the following steps: dropwise adding a water-in-oil emulsion system of diphosphonate into a water-in-oil emulsion system of manganese ions in stirring to establish a coordination skeleton, curing by absolute ethyl alcohol, adding a certain proportion of fat material, performing vortex hydration by a film dispersion method, and extruding to pass through a film. The diphosphonic acid manganese nanoparticle is small in particle size and good in stability, and has a pH-sensitive release characteristic; the constructed nanoparticles have a remarkable immune regulation effect, and the ICD effect and the cytotoxic effect of oxaliplatin are enhanced by directly acting on tumor cells. The diphosphonic acid manganese nanoparticles cooperate with Oxp to effectively inhibit digestive tract tumor growth and distal metastatic tumors, the dosage of Oxp can be further reduced, and the diphosphonic acid manganese nanoparticles have good in-vivo safety.

The utility model relates to a collecting device for digestive tract tumor detection through excrement screening, which comprises a sampling tube, and a through hole is arranged at the eccentric position of the end part of the sampling tube; the pushing assembly is arranged in the sampling pipe in a sliding mode, abuts against an elastic structure installed in the sampling pipe, can be inserted into a sliding groove formed in the inner wall of the sampling pipe, and extrudes the elastic structure when moving directionally; according to the excrement collecting device, the pushing assembly is controlled to move upwards relative to the sampling pipe in the direction of the sliding groove to extrude the elastic structure, so that the excrement collecting work is completed, when the pushing piece is controlled to rotate relative to the sampling pipe in the direction of the sliding groove, the blocking piece is driven to rotate synchronously, and therefore the excrement collecting work is completed. The through hole is blocked, so that the possibility of cross infection of the collected excrement is avoided, and the position of the pushing assembly is locked under the action of the elastic structure.

The present invention discloses a data processing method and system for digestive tract tumors, which relates to the field of medical information processing technology. By collecting the patient's key physiological parameters and tumor characteristics from multiple data sources, a tumor identification data set P of the patient is formed, and through standardized preprocessing and feature vector integration, the consistency and computability of the data are guaranteed. The disease progression prediction model constructed using a machine learning method takes the patient's feature vector X as input and can efficiently predict the patient's disease progression fluctuation probability index Progress. Furthermore, combined with the correction coefficient algorithm and the set correction fluctuation threshold Cthe, the recovery period content extracted from the patient's initial medical record can be dynamically corrected to obtain the corrected recovery period Tad. Through feedback and iterative optimization, the calculation formula of the corrected survival period is continuously verified and updated, ultimately achieving the effect of improving prediction accuracy and adapting to individual differences among patients.

The application discloses 1,2,3-triazole compounds with antitumor effects and a preparation method and application thereof, and belongs to the technical field of medicinal chemistry. The application simply and efficiently synthesizes novel 1,2,3-triazole compounds, and does not involve heavy metal catalysts or microwave reactions. In vitro antitumor activity tests of the compounds show that the 1,2,3-triazole compounds have certain inhibitory effects on the growth of digestive tract tumor cells (human gastric cancer SGC7901 cells, human colon cancer HT-29 cells and human esophageal cancer EC9706 cells). The 1,2,3-triazole compounds can be used as candidate or lead compounds for further development, and are applied to the preparation of antitumor drugs, especially anti-digestive tract tumor drugs.

The invention discloses a non-coding RNA structure function analysis method based on multi-mode GAT and GAN, and the method comprises the steps: constructing graph structure data through non-coding RNA data and interaction molecular data of a digestive tract tumor patient, and carrying out the feature extraction, thereby obtaining a sequence feature, a structure feature and expression quantity distribution; calculating the similarity corresponding to the features; constructing a sequence modal diagram, a structure modal diagram and an expression modal diagram by using the similarity and the features, and then performing branch processing in a diagram attention model to obtain aggregated features; inputting the aggregated features into a cross-modal attention fusion layer to obtain second node data, and inputting the second node data into an adaptive neighbor sampling layer to obtain third node data; and acquiring fusion features through third node data, inputting the fusion features into a generator of the generative adversarial network, and acquiring a structure and function relation list, key function features and expression association features of the non-coding RNA data according to the obtained joint hidden features, a decoding module of the generator and a multi-modal fusion reasoning model.

The invention provides a digestive tract tumor course monitoring system. The system comprises a system control module, a first-stage detection module, a second-stage detection module, a third-stage detection module, a risk assessment module and an intervention decision module. The primary detection module is used for collecting tumor markers, images and clinical symptom data of a patient; the second-stage detection module is used for performing liquid biopsy, pathological biopsy and metabolic function evaluation on the first-stage positive patient; the third-stage detection module is used for carrying out micro-metastasis detection and immune microenvironment and genome analysis on a second-stage positive patient; the risk assessment module determines a patient risk level based on a detection result; the intervention decision module outputs intervention measures based on the risk level; the system control module manages and coordinates operation of all the modules. Each detection module automatically captures detection data by being connected with a hospital system, and judges an abnormal condition according to a set threshold value. According to the system, through a logic mechanism of grading detection and grading intervention, precise monitoring and early warning intervention on the disease course of the digestive tract tumor patient are realized.

The application discloses a kind of gene markers in esophagus, stomach, intestine multiple cancer early screening application, early screening model construction method and detection device, belong to the early non-invasive detection technical field of digestive tract tumor.It establishes a new type of multiple cancer screening system by analyzing the whole genome characteristics of circulating free DNA in peripheral blood.Based on low-depth whole genome sequencing data, three dimensions of molecular markers are detected: genome copy number variation pattern, DNA fragment distribution characteristics of specific length and epigenetic signals of transcription initiation region.Advanced converter neural network architecture is used, and the model can efficiently capture the complex feature correlation in the whole genome range through its unique self-attention mechanism.The model design specially considers the particularity of genomic data, and introduces an adaptive position coding system to accurately reflect the spatial distribution relationship of DNA fragments on the chromosome.The system can still maintain excellent detection performance at very low sequencing depth.

The invention discloses a digestive tract tumor early screening system based on multi-omics data fusion, and relates to the technical field of tumor screening, the system comprises a double sample collection module, a synchronous detection module, a database support module, a fusion analysis module and a visual output module; according to the method, the accuracy and comprehensiveness of early screening of digestive tract tumors are improved through multi-omics data fusion, multi-dimensional data of fecal microbial genome DNA, metabolites, blood ctDNA and protein markers are integrated, biological information of four levels of florae, metabolism, genes and proteins is covered, and the accuracy and comprehensiveness of early screening of digestive tract tumors are improved through a three-level cross validation mechanism. According to the method, flora-metabolite synergy abnormality and gene-protein synergy abnormality can be recognized, the tumor risk value is calculated and the risk level is set in combination with positive threshold values and clinical weights in a multi-omics feature database, the detection rate of early tumors is increased, and the method has higher sensitivity especially for early digestive tract tumors without obvious symptoms.

The application discloses a molecular marker and MRI image fusion tumor early detection method and system, first collects serum molecular marker detection data and multi-sequence MRI image data of a digestive tract tumor screening object, constructs a molecular feature vector and extracts high-dimensional MRI image features respectively; a tumor prior probability is calculated through a molecular pre-screening deep neural network, and an adaptive spatial attention guide weight is generated; the weight is weighted and fused with the MRI image features to realize fine feature enhancement of a high-risk area and accurate lesion detection; based on a Bayesian evidence fusion reasoning framework, molecular detection evidence and image detection evidence are combined to update a posterior probability, and finally, a lesion positioning, detection confidence and visual detection report are output. The application realizes efficient complementation of molecular evidence and image evidence, greatly improves the accuracy, sensitivity and specificity of early detection of digestive tract tumors, and is suitable for non-invasive accurate screening of high-risk groups in clinical practice.

The invention relates to the technical field of medical instruments, and particularly discloses an intelligent navigation and real-time monitoring system for a minimally invasive surgery under a digestive tract tumor endoscope, which is characterized in that a real-time endoscope video sequence and intraoperative high-resolution image data are synchronously acquired; processing the video sequence to construct and update in real time an initial three-dimensional expression reflecting the spatial topology of the surgical region; performing spatial correlation registration on the intra-operative image data and the corresponding video frame, and calculating the position and direction of the intra-operative image data relative to the initial three-dimensional expression; according to the spatial relationship, performing dynamic fusion weight-based adaptive fusion and optimization on anatomical details contained in the intraoperative image and the initial three-dimensional expression to generate a composite data expression named as an incremental dynamic navigation structure; on the basis of the structure, augmented reality navigation information which is matched with the current endoscope visual field and comprises virtual perspective superposition of the tumor and the blood vessel network is calculated and generated in real time; according to the invention, the accuracy, robustness and safety of navigation in a complex dynamic operation environment are improved.

The invention provides an analysis method of a digestive tract tumor micro-ecosystem based on a digital pathological section. The analysis method comprises the following steps: firstly, accurately extracting a foreground region of gastric cancer tissues by using an Otsu algorithm; then predicting cancer and non-cancer regions based on a convolutional neural network (CNN); a CRF algorithm is used to determine a junction area of the cancer area and the non-cancer area, and cell categories of the cancer area and the junction area are accurately predicted by means of a HoverNet model; and finally, quantitatively evaluating the survival and recurrence risk of the patient according to the characteristics extracted from the gastric cancer cells by applying a Cox proportional risk model and combining a lasso-cox method. The method has the advantages that the gastric cancer pathological image can be analyzed in an omnibearing and multi-level mode, and the technical bottlenecks that when a traditional algorithm is used for processing a complex pathological image, precision is insufficient, and judgment on the cancer area boundary and the cell category is not accurate are broken through; key data support can be provided for a doctor to formulate a personalized treatment scheme and accurate prognosis evaluation, and the scientificity and effectiveness of gastric cancer diagnosis and treatment are improved.

The present invention discloses a soft antenna for digestive tract tumor ablation with negative pressure positioning, which relates to the field of medical devices and is composed of a cavity component, a mounting frame, a laparoscope, an input component, and mounting screws. The present invention has a reasonable design, a simple structure, and is easy to use. Through the vacuum suction function of the cavity at the front end of the soft antenna, the vacuum negative pressure is used to attract the tumor tissue into the cavity and contact it with the ablation electrode on the cavity. The high-voltage electric pulse electric field is then transmitted to the target tumor tissue through the ablation electrode, thereby achieving high-voltage steep pulse ablation of the tumor tissue of the digestive tract cavity organ; and a temperature measuring probe is provided in the cavity at the front end of the soft antenna, which has the function of detecting the temperature of the tumor tissue, and can effectively avoid over-ablation caused by the high-voltage steep pulse and cause thermal ablation of the tumor tissue.

The application provides a microorganism marker group, a tumor prognosis prediction model establishment method and application thereof, and relates to the technical field of biomedicine. The microorganism marker group is related to a preset total survival time. Based on the microorganism marker group obtained from tumor tissues and paracancer normal tissues, the prognosis prediction accuracy and sensitivity of a digestive tract tumor can be effectively improved.

The embodiment of the invention provides a PCR primer probe combination for digestive tract tumor gene methylation detection and application of the PCR primer probe combination. The PCR primer probe combination comprises a PCR primer probe combination for SGIP1 methylation detection, a PCR primer probe combination for CCNA1 methylation detection and a PCR primer probe combination for EYA4 methylation detection. According to the embodiment of the invention, a primer probe combination with a specific sequence is designed according to the gene methylation state of a specific site, a specific primer for detecting liver cancer, a specific primer for detecting esophageal cancer and a specific primer for detecting gastric cancer are integrated into the same kit, and the primers do not interfere with one another in a system and are compatible; through highly specific gene amplification, early diagnosis of liver cancer, esophageal cancer and gastric cancer is realized. The PCR primer probe combination provided by the embodiment of the invention can realize high-efficiency cooperative detection of specific primers of liver cancer, esophageal cancer and gastric cancer in a single kit.

The invention belongs to the technical field of medicines, and particularly relates to application of UCM05 (naphthalene-1, 3-diyl di (3, 4, 5-trihydroxy benzoate) with the molecular formula of C24H16O10, the molecular weight of 464.38 and the CAS number of 1094451-90-7) in the aspect of inhibiting growth of gastrointestinal tumors. Through cell proliferation and clone formation experiments, it is verified for the first time that UCM05 can effectively inhibit growth of human esophageal cancer, colorectal cancer and gastric cancer cells. In a 4-nitroquinoline-1-oxide induced esophageal cancer Scyl2 knockout mouse model, the UCM05 is proved to be capable of remarkably inhibiting the progress of the esophageal cancer, and the inhibiting effect of the UCM05 is weakened under the SCYL2 gene knockout condition. The invention provides a new candidate drug and basis for clinical research, treatment and prevention of digestive tract tumors.

The invention discloses a digestive tract tumor recognition method and system and a medium, and relates to the technical field of medical image processing.According to the method, the step length and the layer number of Z-axis sampling are dynamically optimized according to the calculated tangent plane inclination angle, and on the premise that it is guaranteed that a complete glandular tube three-dimensional structure is collected, the number of layers of Z-axis sampling is increased; the problems of local defocus and form distortion caused by tissue beveling are effectively avoided, and the definition of the image and the interlayer registration precision are remarkably improved. In addition, a virtual vertical section reconstruction strategy is introduced, geometric deformation can be corrected in a three-dimensional voxel space, an observation view meeting a standard anatomical view angle is provided, and therefore interference of film production artifacts on diagnosis is eliminated. And through distinguishing the mucous membrane layer and the non-mucous membrane layer and applying a differentiated scanning strategy, while the data quality of a key region is improved, the scanning time and data redundancy of a non-diagnosis region are greatly reduced, dual optimization of scanning precision and efficiency is realized, and the accuracy and robustness of automatic recognition of digestive tract tumors are remarkably improved.

The invention discloses a digestive tumor inflammation pathology dynamic detection and targeted therapy method, and relates to the technical field of biological sample detection analysis, and the method comprises the following specific steps: 1, collecting tissue samples and blood samples from digestive tumor inflammation patients, non-tumor inflammation patients and healthy people, the method has the advantages that tissue and blood samples are collected from a large number of digestive tumor inflammation patients, non-tumor inflammation patients and healthy people, the specific recognition molecules are specifically combined with the digestive tumor inflammation specific markers in the samples, and the signal intensity is detected through the fluorospectro photometer; according to the method, the content of the marker is obtained through comparison with a standard curve, the illness state is judged according to a threshold value, the whole process is linked with one another, specific recognition and combination of unique biomarkers related to digestive tumor inflammation are achieved from sample collection to result judgment, false positive results are effectively reduced, and the accuracy of clinical diagnosis is remarkably improved.

This application relates to the fields of bioinformatics and medical big data technology, specifically disclosing a digestive tumor risk assessment system based on multi-omics data. The system includes: a multi-source heterogeneous data acquisition terminal, a data standardization preprocessing module, a broad-spectrum digestive system risk assessment engine, an organ-specific feature decoupling module, a multimodal cross-omics fusion reasoning module, and a clinical decision support and early warning terminal. This solution simultaneously acquires ctDNA methylation, serum indicators, and clinical phenotype data, uses the assessment engine to evaluate overall risk, and extracts tissue-specific features through methylation map comparison. Combined with a dynamic weight allocation model, it outputs the targeted risk probabilities for the esophagus, stomach, and colorectal region. This application improves screening sensitivity through multi-dimensional data fusion, solves the problems of reliance on a single data source and inability to locate lesions, and achieves accurate organ-specific analysis and early warning.

The present invention discloses a carbon glycoside compound, a preparation method thereof and an application in anti-tumor drugs, and belongs to the field of carbohydrate drug synthesis. The structure of the carbon glycoside compound is shown in general formula (I) or (II). The present invention uses fully acetylated rhamnose, glucose, mannose and the like as raw materials, and can efficiently obtain unprotected rhamnose, glucose, mannose and other free radical precursors with excellent reactivity and stability by preparing them into benzyl glucosinolates and removing the ester group in two steps. Under the conditions of visible light, photocatalyst, phosphine reagent, alkali and solvent, they undergo Giese reaction with olefin receptors connected to different drugs, and can directly obtain α-carbon glycosides with novel structure and single configuration. The carbon glycoside compound showed good activity in the inhibitory activity assay on human ovarian teratoma cells (PA-1) and digestive tract tumor cells (KYSE-510), and is expected to be further developed into an anti-tumor drug.

The invention relates to the technical field of small molecule drugs, in particular to an isoquinoline drug and application thereof to improvement or treatment of digestive tract tumors. The invention aims to provide a compound, a pharmaceutical composition containing the compound and application of the compound in treatment of colorectal cancer and gastric cancer, and provides a 3, 13-substituted berberine derivative which is low in toxicity, does not affect growth of human normal cells, and has a wide application prospect in development of novel anti-tumor drugs and application of the 3, 13-substituted berberine derivative in treatment of colorectal cancer and gastric cancer. Particularly, the compound has a very good application prospect in the aspect of development of anti-digestive tract tumor drugs.

The present invention discloses the application of a derivative with simultaneous substitution at the meso-position and 2-position of hypocrellin as a photodynamic drug in the photodynamic therapy of various tumors. The maximum absorption wavelength of such derivatives is around 630 nm, and the molar extinction coefficient can reach 20,000 - 40,000 M-1 cm-1, showing strong light absorption ability in the phototherapy window; under photosensitizing conditions, it can efficiently generate reactive oxygen species such as singlet oxygen. Such derivatives can efficiently kill a variety of tumor cells, such as esophageal cancer, gastric cancer, lung cancer, liver cancer, cholangiocarcinoma, and colon cancer cells related to digestive tract tumors; brain cancer, head and neck cancer, tongue cancer, nasal cancer, oral cancer, and glioblastoma cells related to head and neck tumors; basal cell carcinoma, squamous cell carcinoma, cutaneous T-cell lymphoma, and melanoma cells related to skin tumors; prostate cancer and bladder cancer cells related to genitourinary tumors. At the same time, such derivatives have good enrichment effects in various tumor cells, can specifically accumulate in tumor cells or tissues, and can locate the position of tumor tissues through the self-fluorescence of the photosensitizer, for fluorescence-guided surgical resection of tumors. Under the same conditions, the derivatives in the present invention have higher photodynamic effects in treating tumors than commercial porphyrin-based photosensitizing drugs.

The present application relates to the technical field of image semantic segmentation, in particular to a digestive tract tumor lesion image segmentation method and system based on multi-modal fusion technology, comprising the following steps: collecting CT and EUS sequences to generate an organ surface three-dimensional triangular mesh model, mapping anatomical markers and constructing a dual-mode lumen manifold surface geodesic distance topological atlas, calculating the connection edge difference and the total amount of elastic potential energy, and generating a digestive tract tumor lesion pixel-level segmentation mask. In the present application, the organ physical form is restored by constructing a covering tube wall triangular mesh reducer, the path length is accurately quantified by using the manifold surface geodesic distance instead of the straight line distance, the potential energy gradient is calculated to drive the nodes to converge in the energy descent direction, the non-rigid mapping field conforming to the anatomical constraint is generated to offset the endoscope compression distortion, the EUS texture is accurately mapped to the CT coordinate system under the premise of maintaining the topological integrity, the multi-modal feature deep fusion is realized, and the soft tissue lesion segmentation accuracy is improved.

The invention discloses a C-glycoside compound, a preparation method thereof and application of the C-glycoside compound in antitumor drugs, and belongs to the field of synthesis of carbohydrate drugs. The structure of the carbon glycoside compound is shown as a general formula (I) or (II). According to the preparation method, peracetylated rhamnose, glucose, mannose and the like are taken as raw materials, unprotected free radical precursors with excellent reaction activity and stability, such as rhamnose, glucose, mannose and the like can be efficiently obtained through two-step reaction of benzyl thioglycoside preparation and ester group removal, and the free radical precursors are synthesized under the conditions of visible light, a photocatalyst, a phosphine reagent, alkali and a solvent. The alpha-C-glycoside with a novel structure and a single configuration can be directly obtained by carrying out Giese reaction on the alpha-C-glycoside and olefin receptors connected with different drugs. The carbon glycoside compound shows good activity in inhibition activity determination of human ovarian teratoma cells (PA-1) and digestive tract tumor cells (KYSE-510), and is expected to be further developed into antitumor drugs. # imgabs0 #