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Produktbild: Multimodal Learning and Fusion Across Scales for Clinical Decision Support
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Multimodal Learning and Fusion Across Scales for Clinical Decision Support 13th International Workshop, ML-CDS 2025, Held in Conjunction with MICCAI 2025, Daejeon, South Korea, September 27, 2025, Proceedings

Aus der Reihe Lecture Notes in Computer Science

53,99 €

inkl. gesetzl. MwSt., Versandkostenfrei

Beschreibung

Produktdetails

Einband

Taschenbuch

Erscheinungsdatum

24.02.2027

Abbildungen

X, 162 p. 43 illus., 41 illus. in color.

Herausgeber

Tanveer Syeda-Mahmood + weitere

Verlag

Springer

Seitenzahl

162

Maße (L/B)

23,5/15,5 cm

Sprache

Englisch

ISBN

978-3-032-30142-0

Beschreibung

Produktdetails

Einband

Taschenbuch

Erscheinungsdatum

24.02.2027

Abbildungen

X, 162 p. 43 illus., 41 illus. in color.

Herausgeber

Verlag

Springer

Seitenzahl

162

Maße (L/B)

23,5/15,5 cm

Sprache

Englisch

ISBN

978-3-032-30142-0

Herstelleradresse

Libri GmbH
Europaallee 1
36244 Bad Hersfeld
DE

Email: gpsr@libri.de

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  • Produktbild: Multimodal Learning and Fusion Across Scales for Clinical Decision Support

  • Multimodal analysis and fusion.- Multi-View and Multimodal Radiological Grading Using Spinal MRIs.- MRI-Supervised Ultra-Low Dose CT for 3D Liver Fat Fraction Mapping.- Integrating Pathology and CT Imaging for Personalized Recurrence Risk Prediction in Renal Cancer.- Expert-Driven Contextual Fusion of Multisequence MRI and Heterogeneous Clinical Data for Pancreatic Cancer Prognostic Prediction.- MOSAIK: Microclip-Guided TEMS-VQA and Mosaic Integrated Scene Fusion for Surgical VLMs.- Imaging Biomarkers for Neurodegenerative Diseases from Detailed Segmentation of Medial Temporal Lobe Subregions on in vivo Brain MRI Using Upsampling Strategy Guided by High-resolution ex vivo MRI.- Multimodal models for decision support.- X2CT-CLIP: Enable Multi-Abnormality Detection in Computed Tomography from Chest Radiography via Tri-Modal Contrastive Learning.- No Modality Left Behind: Dynamic Model Generation for Incomplete Medical Data.- From Pixels to Graphs: SAM-KG for Tumor Segmentation and Knowledge Graphs.- Multimodal Hypergraph Learning with Self-Attention for Early Alzheimer’s Diagnosis and Risk Factor Identification.- Leveraging generic foundation models for multimodal surgical data analysis.- Modality-agnostic input channels enable segmentation of brain lesions in multi-modal MRI with sequences unavailable during training.- Self-Supervised Contrastive Learning for Cardiac MR Sequence Classification.