LEADER 00926nam0-22002771i-450- 001 990006761440403321 005 20001010 035 $a000676144 035 $aFED01000676144 035 $a(Aleph)000676144FED01 035 $a000676144 100 $a20001010d--------km-y0itay50------ba 101 0 $aita 105 $ay-------001yy 200 1 $aSAPERE scientifico e questione sociale tra '800 e '900$eatti del Convegno in occasione del cinquantesimo anniversario della morte del Prof. Pietro Albertoni 210 $as.l.$cIstituto Provinciale per la storiadel movimento di liberazione nel mantovano$ds.d. 215 $a346 p 21 cm 702 1$aAlbertoni,$bEttore A. 801 0$aIT$bUNINA$gRICA$2UNIMARC 901 $aBK 912 $a990006761440403321 952 $aXI A 1961$b11092$fFSPBC 959 $aFSPBC 996 $aSAPERE scientifico e questione sociale tra '800 e '900$9631413 997 $aUNINA DB $aGEN01 LEADER 05018nam 22006375 450 001 996668463703316 005 20250714130232.0 010 $a3-031-98691-1 024 7 $a10.1007/978-3-031-98691-8 035 $a(MiAaPQ)EBC32212127 035 $a(Au-PeEL)EBL32212127 035 $a(CKB)39653458700041 035 $a(DE-He213)978-3-031-98691-8 035 $a(EXLCZ)9939653458700041 100 $a20250714d2026 u| 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aMedical Image Understanding and Analysis $e29th Annual Conference, MIUA 2025, Leeds, UK, July 15?17, 2025, Proceedings, Part II /$fedited by Sharib Ali, David C. Hogg, Michelle Peckham 205 $a1st ed. 2026. 210 1$aCham :$cSpringer Nature Switzerland :$cImprint: Springer,$d2026. 215 $a1 online resource (505 pages) 225 1 $aLecture Notes in Computer Science,$x1611-3349 ;$v15917 311 08$a3-031-98690-3 327 $a -- Image-guided Diagnosis. -- FD-SSD: Semi-Supervised Detection of Bone Fenestration and Dehiscence in Intraoral Images. -- Interpretable Prediction of Lymph Node Metastasis in Rectal Cancer MRI Using Variational Autoencoders. -- Self-Guided SwinTransformer Improves Breast Cancer Detection Through Iterative Attention-Based Zooming. -- Can AI Be Faster, Accurate, and Explainable? SpikeNet Makes It Happen. -- A Novel Feature-Prioritized Loss Function for Enhanced Pneumonia Segmentation in Chest X-rays. -- Bridging Accuracy and Explainability: A SHAP-Enhanced CNN for Skin Cancer Diagnosis. -- Multi-Scale WSI Analysis: A Cascade Framework for Efficient Breast Cancer Metastasis Detection. -- Learning to Harmonize Cross-vendor X-ray Images by Non-linear Image Dynamics Correction. -- Modified CBAM: Sub-Block Pooling for Improved Channel and Spatial Attention. -- WSI-AL: A Novel Active Learning Framework for Whole Slide Image Selection. -- A Deep-learning Approach for Diagnosing and Grading Ankylosing Spondylitis Sacroiliitis by X-ray Images. -- Towards Breast Tumor Aggressiveness Classification in Digital Mammograms Using Boundary-Aware Segmentation and Feature Analysis. -- Image-guided Intervention. -- Joint Dento-Facial Shape Model. -- Out-of-Distribution Detection in Gastrointestinal Vision by Estimating Nearest Centroid Distance Deficit. -- Deep Learning-Driven Pipeline for Automated Wound Measurement of Chronic Wounds. -- Midline-constrained Loss in the Anatomical Landmark Segmentation of 3D Liver Models. -- DepthClassNet: A Multitask Framework for Monocular Depth Estimation and Texture Classification in Endoscopic Imaging. -- Assessing the Generalization Performance of SAM for Ureteroscopy Scene Segmentation and Understanding. -- Modelling Uncertainty in Graph Convolutional Networks for Edge Detection in Mammograms. -- Classification of Gastroscopy Images Under extreme Class Imbalance: A Deep Learning Pipeline. -- Temporally Consistent Smoke Removal from Endoscopic Video Images. -- Toward Patient-specific Partial Point Cloud to Surface Completion for Pre- to Intra-operative Registration in Image-guided Liver Interventions. -- EfficientDet with Knowledge Distillation and Instance Whitening for Real-time and Generalisable Polyp Detection. 330 $aThe three-volume set LNCS 15916,15917 & 15918 constitutes the refereed proceedings of the 29th Annual Conference on Medical Image Understanding and Analysis, MIUA 2025, held in Leeds, UK, during July 15?17, 2025. The 67 revised full papers presented in these proceedings were carefully reviewed and selected from 99 submissions. The papers are organized in the following topical sections: Part I: Frontiers in Computational Pathology; and Image Synthesis and Generative Artificial Intelligence. Part II: Image-guided Diagnosis; and Image-guided Intervention. Part III: Medical Image Segmentation; and Retinal and Vascular Image Analysis. 410 0$aLecture Notes in Computer Science,$x1611-3349 ;$v15917 606 $aComputer vision 606 $aArtificial intelligence 606 $aComputers 606 $aApplication software 606 $aComputer Vision 606 $aArtificial Intelligence 606 $aComputing Milieux 606 $aComputer and Information Systems Applications 615 0$aComputer vision. 615 0$aArtificial intelligence. 615 0$aComputers. 615 0$aApplication software. 615 14$aComputer Vision. 615 24$aArtificial Intelligence. 615 24$aComputing Milieux. 615 24$aComputer and Information Systems Applications. 676 $a006.37 700 $aAli?$b S?a?riba$01872788 701 $aHogg$b David C$01835206 701 $aPeckham$b Michelle$01621464 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a996668463703316 996 $aMedical Image Understanding and Analysis$94528428 997 $aUNISA