The application research of deep neural networks in colonic polyp segmentation Article Swipe

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Jun Li , Fang Wang , Haima Yang , Lihua Qiu , Jin Liu , Le Fu , Dawei Zhang , Weibin Hong , Yeye Song ·

YOU? · · 2022 · Open Access · · DOI: https://doi.org/10.21203/rs.3.rs-2093277/v1

Background: In the study of medical images segmentation, U-Net is a good choice with better performance. But it will cause some problems such as gradient problems or information loss. Methods: In this paper, we introduce a new model based on such an encoder-decoder structure. We mixed a full connection and encoder output in per layer and we add an axial attention to solve gradient problem and keep the connection with pixel from long distance. After pooling, we add a module which has three atrous Convolution processes with different expansion rate and a non-local Self attention to increase the feeling field and fix the problem of losing spatial information. In decoder part, we put a dual channel gate to point out 'what' and 'where' feature we need by the union of Channel Attention and Spatial Attention. Results: We use 4 public dataSets are CVC-ClinicDB, Kvasir-SEG, CVC-ColonDB and CVC-T. We compared more than 10 groups other different models with these 4 group dataSets and marked some evaluating indicators such as mIou, mDice and so on. We also did some ablation experiments to verify that our model structure is reasonable and effective. Conclusions: The comparative training of 12 models in 4 different datasets verifies the feasibility and the good effectiveness of the proposed ideas. We also did some ablation experiments to verify that our model structure is reasonable and effective. The basic structure of the encoder decoder in semantic segmentation has been greatly improved.

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Computer Science

Segmentation Fault

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Pixel

Convolutional Neural Network

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Computer science Segmentation Pooling Encoder Artificial intelligence Convolution (computer science) Feature (linguistics) Channel (broadcasting) Point (geometry) Pattern recognition (psychology) Pixel Convolutional neural network Field (mathematics) Artificial neural network Mathematics Computer network Linguistics Geometry Pure mathematics Operating system Philosophy

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Type: preprint
Language: en
Landing Page: https://doi.org/10.21203/rs.3.rs-2093277/v1
PDF: https://www.researchsquare.com/article/rs-2093277/latest.pdf
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DOI: https://doi.org/10.21203/rs.3.rs-2093277/v1

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Title: The application research of deep neural networks in colonic polyp segmentation

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Type: preprint

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Language: en

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Publication year: 2022

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Publication date: 2022-10-10

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Authors: Jun Li, Fang Wang, Haima Yang, Lihua Qiu, Jin Liu, Le Fu, Dawei Zhang, Weibin Hong, Yeye Song

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Landing page: https://doi.org/10.21203/rs.3.rs-2093277/v1

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Concepts: Computer science, Segmentation, Pooling, Encoder, Artificial intelligence, Convolution (computer science), Feature (linguistics), Channel (broadcasting), Point (geometry), Pattern recognition (psychology), Pixel, Convolutional neural network, Field (mathematics), Artificial neural network, Mathematics, Computer network, Linguistics, Geometry, Pure mathematics, Operating system, Philosophy

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