LEADER 04258nam 22007815 450 001 996691670103316 005 20251010131517.0 010 $a3-032-07945-4 024 7 $a10.1007/978-3-032-07945-9 035 $a(MiAaPQ)EBC32336904 035 $a(Au-PeEL)EBL32336904 035 $a(CKB)41597845600041 035 $a(DE-He213)978-3-032-07945-9 035 $a(EXLCZ)9941597845600041 100 $a20251010d2026 u| 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aImage Analysis in Stroke Diagnosis and Interventions $e5th International Workshop, SWITCH 2025, Held in Conjunction with MICCAI 2025, Daejeon, South Korea, September 23, 2025, Proceedings /$fedited by Ruisheng Su, Ezequiel de la Rosa, Linda Vorberg, Jiong Zhang, Adam Hilbert, Leonhard Rist, Theo van Walsum 205 $a1st ed. 2026. 210 1$aCham :$cSpringer Nature Switzerland :$cImprint: Springer,$d2026. 215 $a1 online resource (167 pages) 225 1 $aLecture Notes in Computer Science,$x1611-3349 ;$v16098 311 08$a3-032-07944-6 327 $aDirect vascular territory segmentation on cerebral digital subtraction angiography -- Towards Diagnostic Quality Flat-Panel Detector CT Imaging Using Diffusion Models -- OccluNet: Spatio-Temporal Deep Learning for Occlusion Detection on DSA -- CLAIRE-DSA: Fluoroscopic Image Classification for Quality Assurance of Computer Vision Pipelines in Acute Ischemic Stroke -- From Thresholds to Teachers: Correcting Unsupervised Learning for Arterial Calcifications in CTA -- Leveraging Last-Known-Well Times for Radiomics-based Stroke Onset Estimation from Non-Contrast CT -- Discriminating Distal Ischemic Stroke from Seizure-Induced Stroke Mimics Using Dynamic Susceptibility Contrast MRI -- Outcome prediction and individualized treatment effect estimation in patients with large vessel occlusion stroke -- Self-Supervised Pretraining and Multi-Label Decoding for Intracranial Hemorrhage Segmentation. 330 $aThis book constitutes the refereed proceedings of the 5th International Workshop on Stroke Imaging and Treatment , SWITCH 2025, held in conjunction with MICCAI 2025, in Daejeon, South Korea, on September 23, 2025. The 9 revised full papers presented in this volume were selected form 11 submissions. These papers highlight recent advances in image analysis for the diagnosis and intervention of ischemic and haemorrhagic stroke, with a focus on integrating artificial intelligence and computational techniques to address clinically relevant challenges. . 410 0$aLecture Notes in Computer Science,$x1611-3349 ;$v16098 606 $aComputer vision 606 $aMedical informatics 606 $aSocial sciences$xData processing 606 $aApplication software 606 $aEducation$xData processing 606 $aArtificial intelligence 606 $aComputer Vision 606 $aHealth Informatics 606 $aComputer Application in Social and Behavioral Sciences 606 $aComputer and Information Systems Applications 606 $aComputers and Education 606 $aArtificial Intelligence 615 0$aComputer vision. 615 0$aMedical informatics. 615 0$aSocial sciences$xData processing. 615 0$aApplication software. 615 0$aEducation$xData processing. 615 0$aArtificial intelligence. 615 14$aComputer Vision. 615 24$aHealth Informatics. 615 24$aComputer Application in Social and Behavioral Sciences. 615 24$aComputer and Information Systems Applications. 615 24$aComputers and Education. 615 24$aArtificial Intelligence. 676 $a006.37 700 $aSu$b Ruisheng$01781479 701 $ade la Rosa$b Ezequiel$01784443 701 $aVorberg$b Linda$01860712 701 $aZhang$b Jiong$01860713 701 $aHilbert$b Adam$01860714 701 $aRist$b Leonhard$01784444 701 $avan Walsum$b Theo$01860715 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a996691670103316 996 $aImage Analysis in Stroke Diagnosis and Interventions$94466457 997 $aUNISA