LEADER 01432nam0 22002891i 450 001 VAN00027198 005 20240806100334.906 010 $a88-324-1427-9 100 $a20041103d1995 |0itac50 ba 101 $aita 102 $aIT 105 $a|||| ||||| 200 1 $aCapitolato speciale di appalto per opere di costruzione del paesaggio con il computer$edisposizioni amministrative e prescrizioni tecniche$fMario Di Fidio$gcon un programma che permette di compilare, modificare e stampare gli articoli del capitolato o parte di essi: elaborazione software S.T.R. s.r.l., Pegognaga (MN) 210 $aMilano$cPirola$d1995 215 $a114, 23 p.$d30 cm$e1 floppy disk. 606 $aSpazi verdi$xSistemazione$xCapitolati di appalto$3VANC012176$2FI 620 $dMilano$3VANL000284 676 $a344.4506712$v21 700 1$aDi Fidio$bMario$3VANV022645$09602 712 02$aS.T.R.$cs.r.l.$3VANV022646 712 $aPirola $3VANV107884$4650 801 $aIT$bSOL$c20240906$gRICA 899 $aBIBLIOTECA DEL DIPARTIMENTO DI ARCHITETTURA E DISEGNO INDUSTRIALE$1IT-CE0107$2VAN01 912 $aVAN00027198 950 $aBIBLIOTECA DEL DIPARTIMENTO DI ARCHITETTURA E DISEGNO INDUSTRIALE$d01PREST IIEb9 $e01 27475 20050628 996 $aCapitolato speciale di appalto per opere di costruzione del paesaggio con il computer$91431314 997 $aUNICAMPANIA LEADER 05203nam 22007455 450 001 9910983083203321 005 20250626164051.0 010 $a3-031-73290-1 024 7 $a10.1007/978-3-031-73290-4 035 $a(MiAaPQ)EBC31738109 035 $a(Au-PeEL)EBL31738109 035 $a(CKB)36389234200041 035 $a(DE-He213)978-3-031-73290-4 035 $a(EXLCZ)9936389234200041 100 $a20241022d2025 u| 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aMachine Learning in Medical Imaging $e15th International Workshop, MLMI 2024, Held in Conjunction with MICCAI 2024, Marrakesh, Morocco, October 6, 2024, Proceedings, Part II /$fedited by Xuanang Xu, Zhiming Cui, Islem Rekik, Xi Ouyang, Kaicong Sun 205 $a1st ed. 2025. 210 1$aCham :$cSpringer Nature Switzerland :$cImprint: Springer,$d2025. 215 $a1 online resource (263 pages) 225 1 $aLecture Notes in Computer Science,$x1611-3349 ;$v15242 311 08$a3-031-73292-8 320 $aIncludes bibliographical references and index. 327 $aRobust Box Prompt based SAM for Medical Image Segmentation -- Multi-task Learning Approach for Intracranial Hemorrhage Prognosis -- Mitigating False Predictions In Unreasonable Body Regions -- UniFed: A Universal Federation of a Mixture of Highly Heterogeneous Medical Image Classification Tasks -- Tackling domain generalization for out-of-distribution endoscopic imaging -- Benchmarking Dependence Measures to Prevent Shortcut Learning in Medical Imaging -- Selective Classifier Based Search Space Shrinking for Radiographs Retrieval -- Pseudo-Rendering for Resolution and Topology-Invariant Cortical Parcellation -- Partially Supervised Unpaired Multi-Modal Learning for Label-Efficient Medical Image Segmentation -- VIS-MAE: An Efficient Self-Supervised Learning Approach on Medical Image Segmentation and Classification -- Transformer-based Parameter Fitting of Models derived from Bloch-McConnell Equations for CEST MRI Analysis -- Probabilistic 3D Correspondence Prediction from Sparse Unsegmented Images -- StoDIP: Efficient 3D MRF image reconstruction with deep image priors and stochastic iterations -- Detection of Emerging Infectious Diseases in Lung CT based on Spatial Anomaly Patterns -- Data Alchemy: Mitigating Cross-Site Model Variability Through Test Time Data Calibration -- Noise-robust onformal prediction for medical image classification -- Identifying Critical Tokens for Accurate Predictions in Transformer-based Medical Imaging Models.-Resource-efficient Medical Image Analysis with Self-adapting Forward-Forward Networks -- SDF-Net: A Hybrid Detection Network for Mediastinal Lymph Node Detection on Contrast CT Images -- Arges: Spatio-Temporal Transformer for Ulcerative Colitis Severity Assessment in Endoscopy Videos -- Characterizing the Histology Spatial Intersections between Tumor-infiltrating Lymphocytes and Tumors for Survival Prediction of Cancers Via Graph Contrastive Learning.-Identifying Nonalcoholic Fatty Liver Disease and Adanced Liver Fibrosis from MRI in UK Biobank -- Explainable and Controllable Motion Curve Guided Cardiac Ultrasound Video Generation. 330 $aThis book constitutes the proceedings of the 15th International Workshop on Machine Learning in Medical Imaging, MLMI 2024, held in conjunction with MICCAI 2024, Marrakesh, Morocco, on October 6, 2024. The 63 full papers presented in this volume were carefully reviewed and selected from 100 submissions. They focus on major trends and challenges in the above-mentioned area, aiming to identify new-cutting-edge techniques and their uses in medical imaging using artificial intelligence (AI) and machine learning (ML). 410 0$aLecture Notes in Computer Science,$x1611-3349 ;$v15242 606 $aComputer vision 606 $aPattern recognition systems 606 $aMachine learning 606 $aComputer engineering 606 $aComputer networks 606 $aSocial sciences$xData processing 606 $aBioinformatics 606 $aComputer Vision 606 $aAutomated Pattern Recognition 606 $aMachine Learning 606 $aComputer Engineering and Networks 606 $aComputer Application in Social and Behavioral Sciences 606 $aComputational and Systems Biology 615 0$aComputer vision. 615 0$aPattern recognition systems. 615 0$aMachine learning. 615 0$aComputer engineering. 615 0$aComputer networks. 615 0$aSocial sciences$xData processing. 615 0$aBioinformatics. 615 14$aComputer Vision. 615 24$aAutomated Pattern Recognition. 615 24$aMachine Learning. 615 24$aComputer Engineering and Networks. 615 24$aComputer Application in Social and Behavioral Sciences. 615 24$aComputational and Systems Biology. 676 $a006.37 702 $aXu$b Xuanang 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910983083203321 996 $aMachine Learning in Medical Imaging$92998079 997 $aUNINA