14 results about "Colon polyps" patented technology

The application belongs to the field of intelligent medical computer-aided diagnosis application, and relates to a colon polyp segmentation method based on deep learning fusion and collaborative learning enhancement. The method comprises a feature extraction model, a fusion module and multi-view collaborative learning. The feature extraction model is divided into two branches. One branch uses DeiT-Small to extract global feature information and establish the correlation between each pixel. The other branch uses HardNet-MSEG to extract local feature information and obtain more low-level detail information. In order to improve the segmentation accuracy of small target colon polyp images, based on the public colon polyp image dataset and the initial deep learning single-branch segmentation method, a deep learning technology fusion method is proposed, and multi-view collaborative learning is used to enhance colon polyp segmentation. Compared with the feature extracted by a single deep learning method before improvement, the feature is richer, and the information omission defect of a single branch is compensated.

This invention belongs to the field of probiotic screening and application technology, specifically relating to a strain of *Lactobacillus paracasei* and its application in the prevention and treatment of colonic polyps and colon cancer. The *Lactobacillus paracasei*, named *Lactobacillus paracasei* V85, was deposited on January 15, 2026, at the China Center for Type Culture Collection (CCTCC), Wuhan University, China, with accession number CCTCC NO: M2026124. The *Lactobacillus paracasei* V85 provided by this invention is sensitive to common antibiotics and has good biosafety; it possesses strong antioxidant function and a strong inhibitory effect on hemolytic streptococci; it can produce a strong agglutination effect with hemolytic streptococci, which is beneficial for inhibiting the colonization of hemolytic streptococci in the intestine, reducing the risk of colonic polyps and colon cancer caused by hemolytic streptococci, and can promote the proliferation of *Akkermansia myxophilus*. It can be used to prevent and treat colonic polyps and colon cancer caused by hemolytic streptococci, and has broad application prospects.

The invention relates to a segmentation method and system for a non-significant colon polyp in a medical image, and the method comprises the steps: carrying out the collection of an endoscopic image, and obtaining a colon polyp image; performing multi-level feature extraction on the colon polyp image through a multi-branch feature fusion network, and outputting multi-scale features; adding local features in the multi-scale features by adopting a feature fusion strategy, and splicing the local features with the global features to obtain fused features; boundary refining processing is carried out on the fusion features to obtain refined features; and decoding the refined features and outputting a segmentation result graph. Complementation of local features and global features is realized through a multi-branch feature fusion network, and the feature expression ability of the non-significant colon polyp is enhanced; the expressive power and the fusion effect of the multi-scale features are improved through a feature fusion strategy; the RCF module effectively alleviates the segmentation deficiency of the traditional method under the condition of fuzzy boundary, and improves the fine-grained performance of the segmentation result.

The invention relates to the technical field of traditional Chinese medicine compounds, in particular to a compound traditional Chinese medicine preparation for preventing and treating postoperative recurrence of colonic polyp and a preparation device thereof, and the compound traditional Chinese medicine preparation comprises the following components: baked ginger, fried garden burnet, smoked plum, pomegranate rind, hairyvein agrimony, astragalus membranaceus, fried rhizoma atractylodis, coix seed, coptis chinensis, patrinia, sargentgloryvine stem, cortex moutan, elecampane, radix paeoniae alba and liquorice. The medicinal materials are compatible according to the principle of monarch, minister, assistant and guide, the compound preparation has the effects of relieving diarrhea with astringents, dispersing blood stasis, stopping bleeding, clearing heat and drying dampness, clinical experiments show that the traditional Chinese medicine compound preparation can effectively prevent postoperative recurrence of colonic polyp and improve the living quality of patients, and animal experiments show that the traditional Chinese medicine compound preparation has no toxic or side effect. The traditional Chinese medicine compound preparation can effectively improve the survival rate of colon'inflammation-cancer 'transformation model mice, reduce the number of tumors (malignant colon polyps), reduce tumor load and improve pathological changes.

This invention belongs to the field of functional probiotic screening and application technology, specifically involving a novel strain of *Lactobacillus plantarum* (…). Lactiplantibacillus plantarum The *Lactobacillus plantarum* strain was deposited on January 15, 2026, at the China Center for Type Culture Collection (CCTCC), Wuhan University, Wuhan, China, with accession number CCTCC NO: M202026133. This strain exhibits strong antioxidant capacity, significant inhibitory and flocculating effects against hemolytic streptococci, and can significantly reduce the levels of pro-inflammatory cytokines IL-6 and IL-1β induced by hemolytic streptococci while increasing the level of the anti-inflammatory cytokine IL-22. It has no toxic effects on the body, good safety profile, and can be used to prevent colonic polyps and colon cancer caused by hemolytic streptococci, showing broad application prospects.

The invention discloses a UNet-based colon polyp image segmentation system and method, and the method comprises the steps: constructing and training a colon polyp segmentation model, inputting a to-be-segmented colorectal polyp image into the trained colon polyp segmentation model, and obtaining a polyp segmentation image; the colon polyp segmentation model takes UNet as a main network, and comprises a cascade convolution module, a convolution attention module, a feature fusion module and a boundary refining module; according to the model provided by the invention, the segmentation accuracy of the colon polyp edge can be effectively improved, and meanwhile, the robustness of the network is improved.

This invention belongs to the field of functional probiotic screening and application technology, specifically relating to a strain of *Lactobacillus plantarum* with the function of preventing and treating colon polyps and colon cancer, and its application. The *Lactobacillus plantarum* was deposited on January 15, 2026, at the China Center for Type Culture Collection (CCTCC), Wuhan University, China, with accession number CCTCC NO: M202026126. This strain can significantly inhibit the growth of hemolytic streptococci that induce colon polyps and colon cancer risk, and produces a flocculation effect with hemolytic streptococci, thus having important application value for the prevention and treatment of colon polyps and colon cancer.

This invention belongs to the field of probiotic screening and application technology, specifically relating to a strain of *Lactobacillus rhamnosus* and its application in the prevention and treatment of colon polyps and colon cancer. The *Lactobacillus rhamnosus* is named *Lactobacillus rhamnosus* (…). Lacticaseibacillus rhamnosus S28, deposited on January 15, 2026, at the China Center for Type Culture Collection (CCTCC), Wuhan University, Wuhan, China, with accession number CCTCC NO: M2026129, exhibits strong inhibitory activity against *Streptococcus bovis* and demonstrates a strong agglutination effect with it. It can be used to prevent or treat colonic polyps and colon cancer caused by *Streptococcus bovis*. This invention also provides probiotic pellets containing *Lactobacillus rhamnosus* S28, which exhibit strong resistance, effectively protecting the probiotics from gastric digestion, ensuring their smooth arrival in the intestines, and achieving rapid disintegration within the intestines, showing broad market prospects.

The invention discloses a colon polyp detection method and system based on improved ResNet, and the method comprises the steps: constructing and training a colon polyp detection network, inputting a to-be-detected colorectal polyp image into the trained colon polyp detection network, and obtaining a polyp segmentation map; the colonic polyp detection network takes ResNet as a main network, adopts a PvTv2 encoder to process an input image, and comprises a local feature enhancement module, a multi-scale feature fusion module and a reverse attention module. According to the model provided by the invention, the segmentation accuracy of the polyp edge can be effectively improved, the local features and the global features are mutually supplemented, and the generalization of the network is enhanced.

The application relates to the technical field of image processing, in particular to a colon polyp image determination device based on a parameterized algorithm. A processor in the device is used to execute the following steps: obtaining a plurality of initial polyp images in a complex plane parameterized image of the inner wall surface of a colon; the complex plane parameterized image is an image of the inner wall surface of the colon after conformal parameterization; intercepting a three-dimensional polyp curved surface piece of each initial polyp image in the three-dimensional curved surface of the inner wall surface of the colon; and determining a target polyp image from the plurality of initial polyp images according to the geometric features of the three-dimensional polyp curved surface piece corresponding to each initial polyp image. The application can determine the colon polyp image, considers the global curvature of the inner wall surface of the colon to be detected, avoids the problems of detection errors caused by uneven CT density in the polyp and missed detection of the polyp image caused by the shielding of the wrinkle, and improves the accuracy of determining the colon polyp image.

The application belongs to the field of computer vision, and discloses a bidirectional enhancement network system for colon polyp segmentation and a colon polyp segmentation method. The system comprises: a backbone network module for extracting low-level features including first and second low-level features and high-level features including first and second high-level features; an edge highlighting module for generating first and second guided low-level features by using the two high-level features to bidirectionally guide the low-level features through a double guide submodule; a first detail-context extraction submodule for extracting the inner boundary details and the inter-feature context information of the two guided low-level features respectively to generate first and second re-extracted features; a self-adaptive gating mechanism submodule for adaptively fusing the two features to output first and second boundary features; a salient edge generation module for fusing the two boundary features with the two high-level features respectively through a second detail-context extraction submodule to generate first and second enhanced high-level features; and a decoding segmentation module for fusing the boundary features and the enhanced high-level features to decode a polyp segmentation map.

The invention discloses a colon polyp segmentation method and system based on prototype memory and feature enhancement, and belongs to the field of computer-aided medical diagnos.The method comprises the steps that an edge feature map of a colonoscope image is input into an image segmentation model to be processed, and a segmentation result is obtained; the image segmentation model comprises an input layer, a multi-branch feature enhancement fusion module, a segmentation head and a boundary head which are connected in sequence, the segmentation head and the boundary head are parallel, and the multi-branch feature enhancement fusion module comprises a plurality of branches. Each branch comprises a backbone network, a receptive field module, a discrete wavelet conversion module, a semantic prototype memory bank module and a decoder module which are connected in sequence, and is constructed as follows: transmitting an edge feature map into a multi-branch feature enhancement fusion module to obtain a final fusion feature; and transmitting the final fusion feature into the segmentation head and the boundary head to obtain a segmentation result. A semantic prototype memory bank module and uncertainty estimation are innovatively constructed, the feature storage and utilization capability is improved, and boundary detection is optimized.

This invention belongs to the field of probiotic screening and application technology, specifically relating to a strain of *Bifidobacterium longum* subsp. *longum* and probiotic pellets containing this strain, as well as their applications. The *Bifidobacterium longum* subsp. *longum* has the accession number CCTCC NO: M2026130 and can significantly inhibit the growth of *Streptococcus pyogenes*, and can efficiently flocculate with *Streptococcus pyogenes*. The probiotic pellets provided by this invention have strong acid resistance, enteric solubility, and storage stability, and can be widely used for the prevention or treatment of *Streptococcus pyogenes*-induced colonic polyps and colon cancer, showing broad prospects.

This invention belongs to the field of probiotic screening and application technology, specifically relating to a strain of *Lactobacillus plantarum*, probiotic pellets containing this strain, their preparation method, and applications. The *Lactobacillus plantarum*, isolated from the feces of healthy infants, has preventative and antagonistic effects against *Streptococcus bovis* infection in the intestines. It was deposited on January 15, 2026, at the China Center for Type Culture Collection (CCTCC), Wuhan University, China, with accession number CCTCC NO: M2026125. This strain exhibits strong tolerance to the digestive tract environment, antioxidant properties, and significantly promotes the proliferation of beneficial intestinal bacteria such as *Lactobacillus acidophilus*, *Lactobacillus casei*, and *Lactobacillus rhamnosus*. It has broad prospects for use in the prevention or treatment of *Streptococcus bovis*-induced colonic polyps and colon cancer.