Intracranial　aneurysm　refers　to　a　neoplastic　protrusion　of　the　arterial　wall　caused　by　a　localized　abnormal　enlargement　of　the　cerebral　artery　lumen.　In　clinical　practice,　patients　in　the　early　stage　of　onset　generally　have　no　obvious　symptoms,　which　is　very　easy　to　miss　diagnosis.　In　medicine,　methods　such　as　MRA,　CTA　and　DSA　can　be　used　to　display　the　images　of　blood　vessels.　Among　them,　magnetic　resonance　angiography　(MRA)　has　the　advantages　of　low　cost　and　small　damage　to　the　human　body.　Which　can　display　the　images　of　blood　vessels　in　the　brain.　The　data　set　used　herein　was　based　on　images　provided　by　a　three-dimensional　time-of-flight　magnetic　resonance　angiography　system.　The　main　contributions　of　this　paper　are　as　follows:　(1)　We　improved　a　classic　3D　U-Net　model　with　the　combination　of　attention　gate,　residual　connection,　and　the　changes　of　size.　Which　achieved　automatic　segmentation　of　aneurysms　in　MRA.　In　the　detection　of　aneurysms　with　mean　diameters　of　6.10mm　and　7.69mm,　the　sensitivity　was　83.4%　and　86.4%　respectively.　(2)　On　the　basis　of　this　sensitivity,　we　achieved　a　low　false　positive　rate　which　was　0.36　FPs/case　and　0.34　FPs/case　respectively.　CCS　CONCEPTS　•Computing　methodologiesg　1/4Computer　graphicsg　1/4Image　manipulationg　1/4Image　processing　©　2022　ACM.