Automatic interpretation system for cell pathology smear
The invention discloses an automatic interpretation system for a cell pathology smear. The system comprises an imaging module; an image acquisition module; an image storage and management module; an image preprocessing module; the intelligent interpretation module receives the image output by the im...
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creator | GENG CHEN DAI YAKANG WENG QIAOYOU GONG WEI XU MIN CHEN MINJIANG ZHOU ZHIYONG JI JIANSONG |
description | The invention discloses an automatic interpretation system for a cell pathology smear. The system comprises an imaging module; an image acquisition module; an image storage and management module; an image preprocessing module; the intelligent interpretation module receives the image output by the image preprocessing module, predicts and classifies a normal sample and a lesion sample for the image, and further predicts and interprets the lesion type when the image is the lesion sample; and the report writing module automatically generates an interpretation conclusion text of the sample corresponding to the image. According to the method, the artificial intelligence auxiliary diagnosis technology is successfully applied to the rapid staining cytopathology, the accuracy and consistency of diagnosis can be remarkably improved, and the workload of cytopathology doctors is reduced; according to the method, the existing convolutional neural network is improved, the multi-channel attention mechanism characteristics a |
format | Patent |
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The system comprises an imaging module; an image acquisition module; an image storage and management module; an image preprocessing module; the intelligent interpretation module receives the image output by the image preprocessing module, predicts and classifies a normal sample and a lesion sample for the image, and further predicts and interprets the lesion type when the image is the lesion sample; and the report writing module automatically generates an interpretation conclusion text of the sample corresponding to the image. According to the method, the artificial intelligence auxiliary diagnosis technology is successfully applied to the rapid staining cytopathology, the accuracy and consistency of diagnosis can be remarkably improved, and the workload of cytopathology doctors is reduced; according to the method, the existing convolutional neural network is improved, the multi-channel attention mechanism characteristics a</description><language>chi ; eng</language><subject>CALCULATING ; COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS ; COMPUTING ; COUNTING ; OPTICAL ELEMENTS, SYSTEMS, OR APPARATUS ; OPTICS ; PHYSICS</subject><creationdate>2022</creationdate><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://worldwide.espacenet.com/publicationDetails/biblio?FT=D&date=20220422&DB=EPODOC&CC=CN&NR=114387596A$$EHTML$$P50$$Gepo$$Hfree_for_read</linktohtml><link.rule.ids>230,308,777,882,25545,76296</link.rule.ids><linktorsrc>$$Uhttps://worldwide.espacenet.com/publicationDetails/biblio?FT=D&date=20220422&DB=EPODOC&CC=CN&NR=114387596A$$EView_record_in_European_Patent_Office$$FView_record_in_$$GEuropean_Patent_Office$$Hfree_for_read</linktorsrc></links><search><creatorcontrib>GENG CHEN</creatorcontrib><creatorcontrib>DAI YAKANG</creatorcontrib><creatorcontrib>WENG QIAOYOU</creatorcontrib><creatorcontrib>GONG WEI</creatorcontrib><creatorcontrib>XU MIN</creatorcontrib><creatorcontrib>CHEN MINJIANG</creatorcontrib><creatorcontrib>ZHOU ZHIYONG</creatorcontrib><creatorcontrib>JI JIANSONG</creatorcontrib><title>Automatic interpretation system for cell pathology smear</title><description>The invention discloses an automatic interpretation system for a cell pathology smear. The system comprises an imaging module; an image acquisition module; an image storage and management module; an image preprocessing module; the intelligent interpretation module receives the image output by the image preprocessing module, predicts and classifies a normal sample and a lesion sample for the image, and further predicts and interprets the lesion type when the image is the lesion sample; and the report writing module automatically generates an interpretation conclusion text of the sample corresponding to the image. According to the method, the artificial intelligence auxiliary diagnosis technology is successfully applied to the rapid staining cytopathology, the accuracy and consistency of diagnosis can be remarkably improved, and the workload of cytopathology doctors is reduced; according to the method, the existing convolutional neural network is improved, the multi-channel attention mechanism characteristics a</description><subject>CALCULATING</subject><subject>COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS</subject><subject>COMPUTING</subject><subject>COUNTING</subject><subject>OPTICAL ELEMENTS, SYSTEMS, OR APPARATUS</subject><subject>OPTICS</subject><subject>PHYSICS</subject><fulltext>true</fulltext><rsrctype>patent</rsrctype><creationdate>2022</creationdate><recordtype>patent</recordtype><sourceid>EVB</sourceid><recordid>eNrjZLBwLC3Jz00syUxWyMwrSS0qKEotAfLy8xSKK4tLUnMV0vKLFJJTc3IUChJLMvJz8tMrFYpzUxOLeBhY0xJzilN5oTQ3g6Kba4izh25qQX58anFBYnJqXmpJvLOfoaGJsYW5qaWZozExagBhIC8R</recordid><startdate>20220422</startdate><enddate>20220422</enddate><creator>GENG CHEN</creator><creator>DAI YAKANG</creator><creator>WENG QIAOYOU</creator><creator>GONG WEI</creator><creator>XU MIN</creator><creator>CHEN MINJIANG</creator><creator>ZHOU ZHIYONG</creator><creator>JI JIANSONG</creator><scope>EVB</scope></search><sort><creationdate>20220422</creationdate><title>Automatic interpretation system for cell pathology smear</title><author>GENG CHEN ; DAI YAKANG ; WENG QIAOYOU ; GONG WEI ; XU MIN ; CHEN MINJIANG ; ZHOU ZHIYONG ; JI JIANSONG</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-epo_espacenet_CN114387596A3</frbrgroupid><rsrctype>patents</rsrctype><prefilter>patents</prefilter><language>chi ; eng</language><creationdate>2022</creationdate><topic>CALCULATING</topic><topic>COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS</topic><topic>COMPUTING</topic><topic>COUNTING</topic><topic>OPTICAL ELEMENTS, SYSTEMS, OR APPARATUS</topic><topic>OPTICS</topic><topic>PHYSICS</topic><toplevel>online_resources</toplevel><creatorcontrib>GENG CHEN</creatorcontrib><creatorcontrib>DAI YAKANG</creatorcontrib><creatorcontrib>WENG QIAOYOU</creatorcontrib><creatorcontrib>GONG WEI</creatorcontrib><creatorcontrib>XU MIN</creatorcontrib><creatorcontrib>CHEN MINJIANG</creatorcontrib><creatorcontrib>ZHOU ZHIYONG</creatorcontrib><creatorcontrib>JI JIANSONG</creatorcontrib><collection>esp@cenet</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>GENG CHEN</au><au>DAI YAKANG</au><au>WENG QIAOYOU</au><au>GONG WEI</au><au>XU MIN</au><au>CHEN MINJIANG</au><au>ZHOU ZHIYONG</au><au>JI JIANSONG</au><format>patent</format><genre>patent</genre><ristype>GEN</ristype><title>Automatic interpretation system for cell pathology smear</title><date>2022-04-22</date><risdate>2022</risdate><abstract>The invention discloses an automatic interpretation system for a cell pathology smear. The system comprises an imaging module; an image acquisition module; an image storage and management module; an image preprocessing module; the intelligent interpretation module receives the image output by the image preprocessing module, predicts and classifies a normal sample and a lesion sample for the image, and further predicts and interprets the lesion type when the image is the lesion sample; and the report writing module automatically generates an interpretation conclusion text of the sample corresponding to the image. According to the method, the artificial intelligence auxiliary diagnosis technology is successfully applied to the rapid staining cytopathology, the accuracy and consistency of diagnosis can be remarkably improved, and the workload of cytopathology doctors is reduced; according to the method, the existing convolutional neural network is improved, the multi-channel attention mechanism characteristics a</abstract><oa>free_for_read</oa></addata></record> |
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subjects | CALCULATING COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS COMPUTING COUNTING OPTICAL ELEMENTS, SYSTEMS, OR APPARATUS OPTICS PHYSICS |
title | Automatic interpretation system for cell pathology smear |
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