Cell　segmentation　is　one　of　the　most　fundamental　tasks　in　the　areas　of　medical　image　analysis,　which　assists　in　cell　recognition　and　number　counting.　The　segmentation　results　obtained　will　be　poor　due　to　the　diverse　cell　morphology　and　the　frequent　presence　of　impurities　in　the　cell　pictures.　In　order　to　solve　the　cell　segmentation　which　are　from　a　competition　held　by　Neural　Information　Processing　Systems(NIPS),　we　present　a　network　that　combines　attention　gates　with　U-Net++　to　segment　varied　sizes　of　cells.　Using　the　feature　filtering　of　the　attention　gate　can　adjust　the　convolution　block’s　output,　so　as　to　improve　the　segmentation　effect.　The　F1　score　of　our　method　reached　0.5874,　Rank　Running　Time　get　2.5431　seconds.　©　2023　SPIE.