LEADER 04320nam 22006135 450 001 996691676303316 005 20251121114926.0 010 $a3-032-10351-7 024 7 $a10.1007/978-3-032-10351-2 035 $a(MiAaPQ)EBC32427261 035 $a(Au-PeEL)EBL32427261 035 $a(CKB)43675264000041 035 $a(DE-He213)978-3-032-10351-2 035 $a(EXLCZ)9943675264000041 100 $a20251121d2026 u| 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aOphthalmic Medical Image Analysis $e12th International Workshop, OMIA 2025, Held in Conjunction with MICCAI 2025, Daejeon, South Korea, September 27, 2025, Proceedings /$fedited by Huihui Fang, Meng Wang, Heng Li, Hao Chen, Hrvoje Bogunovi?, Cecilia S. Lee 205 $a1st ed. 2026. 210 1$aCham :$cSpringer Nature Switzerland :$cImprint: Springer,$d2026. 215 $a1 online resource (300 pages) 225 1 $aLecture Notes in Computer Science,$x1611-3349 ;$v16209 311 08$a3-032-10350-9 327 $a -- DVIA-Net: Dual-path Video Information Aggregation Network for Anterior Chamber Angle Analysis. -- BEAM: Boosting Fundus Image Enhancement via Adapted Text-to-Image Models. -- Multimodal Fusion Framework Using Contrastive Learning for Exposure Keratopathy. -- GARD: Gamma-based Anatomical Restoration and Denoising for Retinal OCT. -- Anomaly Detection in Anterior Eye Segment Using Self-Supervised Siamese Autoencoders. -- Generalized Visual Field Pattern Discovery Using Archetypal Analysis. -- Uncertainty-Aware Multimodal Fusion for Reliable Fundus Disease Classification Using a Vision-Language Foundation Model. -- RetBench: Which Ophthalmic Foundation Model Performs Best and Why?. -- On the Limits of Uncertainty-Aware Fine-Tuning for Robust Diabetic Retinopathy Screening. -- Semi-Automated Retinal Microsurgery Video Annotation with SAM2: Comparative Analysis of Prompt Strategies. -- Cross Domain Few Shot Learning for Intra-operative OCT Segmentation. -- Reasoning-Enhanced Vision-Language Model for Interpretable Diabetic Retinopathy Detection in Ultra-Wide-Field Fundus Images. -- PASO: A Multipurpose Porcine Anterior Segment Dataset Featuring Spectral and Reconstructed OCT Volume Scans and Surgical Instrument Segmentation Masks. -- abVAE: Attribute-Based Booster Variational Autoencoder for Interpretable Latent Presentation in Optical Coherence Tomography of Glaucomatous Eyes. -- Early CHD Detection from Retinal Fundus Scans using a Spatial Context-Aware Hierarchical Attention Framework. -- Dataset, Baseline and Evaluation Design for GAVE Challenge. -- UncEGA-Net: Uncertainty-Guided Edge Attention for Optic Nerve Segmentation in Ultrasound Images. 330 $aThis book constitutes the refereed proceedings of the 12th International Workshop, OMIA 2025, Held in Conjunction with MICCAI 2025, Daejeon, South Korea, September 27, 2025. The 17 full papers presented in this book were carefully selected and reviewed from 33 submissions.This workshop aimed to bring together scientists, clinicians, and students from multiple disciplines in the growing ophthalmic image analysis community such as electronic engineering, computer science, mathematics, and medicine to discuss the latest advancements in the field. 410 0$aLecture Notes in Computer Science,$x1611-3349 ;$v16209 606 $aComputer vision 606 $aArtificial intelligence 606 $aPattern recognition systems 606 $aComputer networks 606 $aComputer Vision 606 $aArtificial Intelligence 606 $aAutomated Pattern Recognition 606 $aComputer Communication Networks 615 0$aComputer vision. 615 0$aArtificial intelligence. 615 0$aPattern recognition systems. 615 0$aComputer networks. 615 14$aComputer Vision. 615 24$aArtificial Intelligence. 615 24$aAutomated Pattern Recognition. 615 24$aComputer Communication Networks. 676 $a006.37 700 $aFang$b Huihui$01784632 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a996691676303316 996 $aOphthalmic Medical Image Analysis$94466423 997 $aUNISA