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001481313 001__ 1481313
001481313 003__ OCoLC
001481313 005__ 20231031003332.0
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001481313 008__ 231003s2023\\\\sz\a\\\\o\\\\\101\0\eng\d
001481313 020__ $$a9783031438981$$q(electronic bk.)
001481313 020__ $$a3031438981$$q(electronic bk.)
001481313 020__ $$z9783031438974$$q(print)
001481313 0247_ $$a10.1007/978-3-031-43898-1$$2doi
001481313 035__ $$aSP(OCoLC)1401632227
001481313 040__ $$aGW5XE$$beng$$erda$$epn$$cGW5XE$$dEBLCP$$dN$T
001481313 049__ $$aISEA
001481313 050_4 $$aRC78.7.D53$$bI58 2023eb
001481313 08204 $$a616.07/54$$223/eng/20231003
001481313 1112_ $$aInternational Conference on Medical Image Computing and Computer-Assisted Intervention$$n(26th :$$d2023 :$$cVancouver, B.C. ; Online)
001481313 24510 $$aMedical image computing and computer assisted intervention -- MICCAI 2023 :$$b26th International Conference, Vancouver, BC, Canada, October 8-12, 2023, Proceedings.$$nPart III /$$cHayit Greenspan, Anant Madabhushi, Parvin Mousavi, Septimiu Salcudean, James Duncan, Tanveer Syeda-Mahmood, Russell Taylor, editors.
001481313 264_1 $$aCham :$$bSpringer,$$c2023.
001481313 300__ $$a1 online resource (xxxviii, 771 pages) :$$billustrations (some color).
001481313 336__ $$atext$$btxt$$2rdacontent
001481313 337__ $$acomputer$$bc$$2rdamedia
001481313 338__ $$aonline resource$$bcr$$2rdacarrier
001481313 4901_ $$aLecture notes in computer science,$$x1611-3349 ;$$v14222
001481313 500__ $$aIncludes author index.
001481313 5050_ $$aIntro -- Preface -- Organization -- Contents - Part III -- Machine Learning - Explainability, Bias, and Uncertainty II -- Pre-trained Diffusion Models for Plug-and-Play Medical Image Enhancement -- 1 Introduction -- 2 Method -- 2.1 Denoising Diffusion Probabilistic Models (DDPM) for Unconditional Image Generation -- 2.2 Image Enhancement with Denoising Algorithm -- 2.3 Pre-Trained Diffusion Models for Plug-and-play Medical Image Enhancement -- 3 Experiments -- 4 Results and Discussion -- 5 Conclusion -- References
001481313 5058_ $$aGRACE: A Generalized and Personalized Federated Learning Method for Medical Imaging -- 1 Introduction -- 2 Method -- 2.1 Overview of the GPFL Framework -- 2.2 Local Training Phase: Feature Alignment & Personalization -- 2.3 Aggregation Phase: Consistency-Enhanced Re-weighting -- 3 Experiments -- 3.1 Dataset and Experimental Setting -- 3.2 Comparison with SOTA Methods -- 3.3 Further Analysis -- 4 Conclusion -- References -- Chest X-ray Image Classification: A Causal Perspective -- 1 Introduction -- 2 Methodology -- 2.1 A Causal View on CXR Images -- 2.2 Causal Intervention via Backdoor Adjustment
001481313 5058_ $$a2.3 Training Object -- 3 Experiments -- 3.1 Experimental Setup -- 3.2 Results and Analysis -- 4 Conclusion -- References -- DRMC: A Generalist Model with Dynamic Routing for Multi-center PET Image Synthesis -- 1 Introduction -- 2 Method -- 2.1 Center Interference Issue -- 2.2 Network Architecture -- 2.3 Dynamic Routing Strategy -- 2.4 Loss Function -- 3 Experiments and Results -- 3.1 Dataset and Evaluation -- 3.2 Implementation -- 3.3 Comparative Experiments -- 3.4 Ablation Study -- 4 Conclusion -- References
001481313 5058_ $$aFederated Condition Generalization on Low-dose CT Reconstruction via Cross-domain Learning -- 1 Introduction -- 2 Method -- 2.1 iRadonMAP -- 2.2 Proposed FedCG Method -- 3 Experiments -- 3.1 Dataset -- 3.2 Implementation Details -- 4 Result -- 4.1 Reuslt on Condition #1 -- 4.2 Result on Condition #2 -- 4.3 Ablation Experiments -- 5 Conclusion -- References -- Enabling Geometry Aware Learning Through Differentiable Epipolar View Translation -- 1 Introduction -- 2 Methods -- 3 Experiments -- 3.1 Model Training -- 4 Results -- 5 Discussion and Conclusion -- References
001481313 5058_ $$aEnhance Early Diagnosis Accuracy of Alzheimer's Disease by Elucidating Interactions Between Amyloid Cascade and Tau Propagation -- 1 Introduction -- 2 Method -- 2.1 Reaction-Diffusion Model for Neuro-Dynamics -- 2.2 Construction on the Interaction Between Tau and Amyloid -- 2.3 Neural Network Landscape of RDM-Based Dynamic Model -- 3 Experiments -- 3.1 Data Description and Experimental Setting -- 3.2 Ablation Study in Prediction Disease Progression -- 3.3 Prognosis Accuracies on Forecasting AD Risk -- 4 Conclusion -- References
001481313 506__ $$aAccess limited to authorized users.
001481313 520__ $$aThe ten-volume set LNCS 14220, 14221, 14222, 14223, 14224, 14225, 14226, 14227, 14228, and 14229 constitutes the refereed proceedings of the 26th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2023, which was held in Vancouver, Canada, in October 2023. The 730 revised full papers presented were carefully reviewed and selected from a total of 2250 submissions. The papers are organized in the following topical sections: Part I: Machine learning with limited supervision and machine learning - transfer learning; Part II: Machine learning -- learning strategies; machine learning -- explainability, bias, and uncertainty; Part III: Machine learning -- explainability, bias and uncertainty; image segmentation; Part IV: Image segmentation; Part V: Computer-aided diagnosis; Part VI: Computer-aided diagnosis; computational pathology; Part VII: Clinical applications -- abdomen; clinical applications -- breast; clinical applications -- cardiac; clinical applications -- dermatology; clinical applications -- fetal imaging; clinical applications -- lung; clinical applications -- musculoskeletal; clinical applications -- oncology; clinical applications -- ophthalmology; clinical applications -- vascular; Part VIII: Clinical applications -- neuroimaging; microscopy; Part IX: Image-guided intervention, surgical planning, and data science; Part X: Image reconstruction and image registration.
001481313 588__ $$aOnline resource; title from PDF title page (SpringerLink, viewed October 3, 2023).
001481313 650_0 $$aDiagnostic imaging$$xData processing$$vCongresses.$$0(DLC)sh2007006024
001481313 655_0 $$aElectronic books.
001481313 7001_ $$aGreenspan, Hayit,$$eeditor.
001481313 7001_ $$aMadabhushi, Anant,$$eeditor.$$1https://orcid.org/0000-0002-5741-0399
001481313 7001_ $$aMousavi, Parvin,$$eeditor.
001481313 7001_ $$aSalcudean, Septimiu Edmund,$$eeditor.$$1https://orcid.org/0000-0001-8826-8025
001481313 7001_ $$aDuncan, James,$$d1951-$$eeditor.$$1https://orcid.org/0000-0002-5167-9856$$0(OCoLC)oca00745149
001481313 7001_ $$aSyeda-Mahmood, Tanveer,$$eeditor.$$1https://orcid.org/0000-0003-0059-3208
001481313 7001_ $$aTaylor, Russell,$$eeditor.$$0(orcid)0000-0001-6272-1100$$1https://orcid.org/0000-0001-6272-1100
001481313 830_0 $$aLecture notes in computer science ;$$v14222.$$x1611-3349
001481313 852__ $$bebk
001481313 85640 $$3Springer Nature$$uhttps://univsouthin.idm.oclc.org/login?url=https://link.springer.com/10.1007/978-3-031-43898-1$$zOnline Access$$91397441.1
001481313 909CO $$ooai:library.usi.edu:1481313$$pGLOBAL_SET
001481313 980__ $$aBIB
001481313 980__ $$aEBOOK
001481313 982__ $$aEbook
001481313 983__ $$aOnline
001481313 994__ $$a92$$bISE