Sparse angle CT image artifact suppression method based on structure enhancement and artifact estimation
The invention discloses a sparse angle CT image artifact suppression method based on structure enhancement and artifact estimation, and belongs to the technical field of computed tomography. The method comprises the following steps: constructing a structure enhancement artifact suppression network f...
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| creator | SUN YU YAN YUHAO LIU JIN KANG YANQIN WU FAN LIU TAO |
| description | The invention discloses a sparse angle CT image artifact suppression method based on structure enhancement and artifact estimation, and belongs to the technical field of computed tomography. The method comprises the following steps: constructing a structure enhancement artifact suppression network for sparse angle CT image processing, wherein the structure enhancement artifact suppression network mainly comprises an artifact feature extraction sub-network and a structure feature extraction sub-network which have the same network architecture; constructing an image restoration loss function and a structure loss function, jointly training each sub-network, and forming a trained structure enhancement artifact suppression network; and finally, inputting a sparse angle CT image to be processed into the trained structure-enhanced artifact suppression network by a user, and outputting a CT image after artifact suppression. Aiming at the problems that sparse angle CT image artifacts are complex and organization struc |
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The method comprises the following steps: constructing a structure enhancement artifact suppression network for sparse angle CT image processing, wherein the structure enhancement artifact suppression network mainly comprises an artifact feature extraction sub-network and a structure feature extraction sub-network which have the same network architecture; constructing an image restoration loss function and a structure loss function, jointly training each sub-network, and forming a trained structure enhancement artifact suppression network; and finally, inputting a sparse angle CT image to be processed into the trained structure-enhanced artifact suppression network by a user, and outputting a CT image after artifact suppression. 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The method comprises the following steps: constructing a structure enhancement artifact suppression network for sparse angle CT image processing, wherein the structure enhancement artifact suppression network mainly comprises an artifact feature extraction sub-network and a structure feature extraction sub-network which have the same network architecture; constructing an image restoration loss function and a structure loss function, jointly training each sub-network, and forming a trained structure enhancement artifact suppression network; and finally, inputting a sparse angle CT image to be processed into the trained structure-enhanced artifact suppression network by a user, and outputting a CT image after artifact suppression. Aiming at the problems that sparse angle CT image artifacts are complex and organization struc</description><subject>CALCULATING</subject><subject>COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS</subject><subject>COMPUTING</subject><subject>COUNTING</subject><subject>IMAGE DATA PROCESSING OR GENERATION, IN GENERAL</subject><subject>PHYSICS</subject><fulltext>true</fulltext><rsrctype>patent</rsrctype><creationdate>2023</creationdate><recordtype>patent</recordtype><sourceid>EVB</sourceid><recordid>eNqNjDsOwjAQBdNQIOAOywEokqBQowhERUP6aLFfPlLsWN71_XGBREv1NNKb2RbTK3AUEPtxAbUdzY7HjFHngY2SpBAiRObVk4NOq6U3CyxlFo3JaIog-Im9gYPXXLI_HaI5qNneF5uBF8Hhu7vieL917eOEsPaQwAYe2rfPsmzqc3Wpmmv9z-cDEfpAqQ</recordid><startdate>20230627</startdate><enddate>20230627</enddate><creator>SUN YU</creator><creator>YAN YUHAO</creator><creator>LIU JIN</creator><creator>KANG YANQIN</creator><creator>WU FAN</creator><creator>LIU TAO</creator><scope>EVB</scope></search><sort><creationdate>20230627</creationdate><title>Sparse angle CT image artifact suppression method based on structure enhancement and artifact estimation</title><author>SUN YU ; YAN YUHAO ; LIU JIN ; KANG YANQIN ; WU FAN ; LIU TAO</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-epo_espacenet_CN116342726A3</frbrgroupid><rsrctype>patents</rsrctype><prefilter>patents</prefilter><language>chi ; eng</language><creationdate>2023</creationdate><topic>CALCULATING</topic><topic>COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS</topic><topic>COMPUTING</topic><topic>COUNTING</topic><topic>IMAGE DATA PROCESSING OR GENERATION, IN GENERAL</topic><topic>PHYSICS</topic><toplevel>online_resources</toplevel><creatorcontrib>SUN YU</creatorcontrib><creatorcontrib>YAN YUHAO</creatorcontrib><creatorcontrib>LIU JIN</creatorcontrib><creatorcontrib>KANG YANQIN</creatorcontrib><creatorcontrib>WU FAN</creatorcontrib><creatorcontrib>LIU TAO</creatorcontrib><collection>esp@cenet</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>SUN YU</au><au>YAN YUHAO</au><au>LIU JIN</au><au>KANG YANQIN</au><au>WU FAN</au><au>LIU TAO</au><format>patent</format><genre>patent</genre><ristype>GEN</ristype><title>Sparse angle CT image artifact suppression method based on structure enhancement and artifact estimation</title><date>2023-06-27</date><risdate>2023</risdate><abstract>The invention discloses a sparse angle CT image artifact suppression method based on structure enhancement and artifact estimation, and belongs to the technical field of computed tomography. The method comprises the following steps: constructing a structure enhancement artifact suppression network for sparse angle CT image processing, wherein the structure enhancement artifact suppression network mainly comprises an artifact feature extraction sub-network and a structure feature extraction sub-network which have the same network architecture; constructing an image restoration loss function and a structure loss function, jointly training each sub-network, and forming a trained structure enhancement artifact suppression network; and finally, inputting a sparse angle CT image to be processed into the trained structure-enhanced artifact suppression network by a user, and outputting a CT image after artifact suppression. Aiming at the problems that sparse angle CT image artifacts are complex and organization struc</abstract><oa>free_for_read</oa></addata></record> |
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| subjects | CALCULATING COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS COMPUTING COUNTING IMAGE DATA PROCESSING OR GENERATION, IN GENERAL PHYSICS |
| title | Sparse angle CT image artifact suppression method based on structure enhancement and artifact estimation |
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