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| Link zu diesem Datensatz | https://d-nb.info/1373288027 |
| Titel | Information Processing in Medical Imaging : 29th International Conference, IPMI 2025, Kos, Greece, May 25–30, 2025, Proceedings, Part II / edited by Ipek Oguz, Shaoting Zhang, Dimitris N. Metaxas |
| Person(en) |
Oguz, Ipek (Herausgeber) Zhang, Shaoting (Herausgeber) Metaxas, Dimitris N. (Herausgeber) |
| Organisation(en) | SpringerLink (Online service) (Sonstige) |
| Ausgabe | 1st ed. 2026 |
| Verlag | Cham : Springer Nature Switzerland, Imprint: Springer |
| Zeitliche Einordnung | Erscheinungsdatum: 2026 |
| Umfang/Format | Online-Ressource, XVIII, 408 p. 119 illus., 115 illus. in color. : online resource. |
| Andere Ausgabe(n) |
Printed edition:: ISBN: 978-3-031-96624-8 Printed edition:: ISBN: 978-3-031-96626-2 |
| Inhalt | Computer-aided diagnosis/surgery: Concepts from Neurons: Building Interpretable Medical Image Diagnostic Models by Dissecting Opaque Neural Networks -- BioSonix: Can Physics-based Sonification Perceptualize Tissue Deformations from Tool Interactions? Brain: Explainable Deep Model for Understanding Neuropathological Events Through Neural Symbolic Regression -- A Multi-Layer Neural Transport Model for Characterizing Pathology Propagation in Neurodegenerative Diseases -- Enhancing Alzheimer's Diagnosis: Leveraging Anatomical Landmarks in Graph Convolutional Neural Networks on Tetrahedral Meshes -- Hierarchical Variable Importance with Statistical Control for Medical Data-Based Prediction -- Disentangle disease-relevant patterns from irrelevant patterns in fMRI analysis using equivariant and contrastive learning. Diffusion models: Continuous Diffusion Model for Self-supervised Denoising and Super-resolution on Fluorescence Microscopy Images -- Self-Supervised Denoising of Diffusion MRI Data with Efficient Collaborative Diffusion Model -- MAD-AD: Masked Diffusion for Unsupervised Brain Anomaly Detection. Self-supervised learning: Taming Masked Image Modeling for Chest X-ray Diagnosis by Incorporating Clinical Visual Priors -- Diffusion MAE: Paving the Way for Representation Learning of Diffusion MRI -- Resolving quantitative MRI model degeneracy in self-supervised machine learning. Vision-language models: Knowledge-enhanced Hyperbolic Language-Image Pretraining for Zero-shot Learning -- Structure Observation Driven Image-Text Contrastive Learning for Computed Tomography Report Generation -- Hierarchical CLIPs for Fine-grained Anatomical Lesion Localization from Whole-body PET/CT Images -- Multi-View and Multi-Scale Alignment for Contrastive Language-Image Pre-training in Mammography -- Interpretable Few-Shot Retinal Disease Diagnosis with Concept-Guided Prompting of Vision-Language Models -- Full Conformal Adaptation of Medical Vision-Language Models -- A Reality Check of Vision-Language Pre-training in Radiology: Have We Progressed Using Text? Shape analysis: ToothForge: Automatic Dental Shape Generation using Synchronized Spectral Embeddings -- LEDA: Log-Euclidean Diffeomorphism Autoencoder for Efficient Statistical Analysis of Diffeomorphisms -- CoRLD: Contrastive Representation Learning of Deformable Shapes in Images. Time-series image analysis: 4DRGS: 4D Radiative Gaussian Splatting for Efficient 3D Vessel Reconstruction from Sparse-View Dynamic DSA Images -- Brightness-Invariant Tracking Estimation in Tagged MRI -- SafeTriage: Facial Video De-identification for Privacy-Preserving Stroke Triage |
| Persistent Identifier |
URN: urn:nbn:de:101:1-2508070406282.027857211677 DOI: 10.1007/978-3-031-96625-5 |
| URL | https://doi.org/10.1007/978-3-031-96625-5 |
| ISBN/Einband/Preis | 978-3-031-96625-5 |
| Sprache(n) | Englisch (eng) |
| Beziehungen | Lecture Notes in Computer Science ; 15830 |
| Sachgruppe(n) | 004 Informatik |
| Online-Zugriff | Archivobjekt öffnen |
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