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portada Medical Image Computing and Computer Assisted Intervention – Miccai 2025: 28Th International Conference, Daejeon, South Korea, September 23–27, 2025,. Part x (Lecture Notes in Computer Science) (en Inglés)
Formato
Libro Físico
Editorial
Autor
Idioma
Inglés
N° páginas
696
Encuadernación
Tapa Blanda
ISBN13
9783032051264

Medical Image Computing and Computer Assisted Intervention – Miccai 2025: 28Th International Conference, Daejeon, South Korea, September 23–27, 2025,. Part x (Lecture Notes in Computer Science) (en Inglés)

Gee James C.,Alexander Daniel C.,Hong Jaesung (Autor) · Springer Verlag Gmbh · Tapa Blanda

Medical Image Computing and Computer Assisted Intervention – Miccai 2025: 28Th International Conference, Daejeon, South Korea, September 23–27, 2025,. Part x (Lecture Notes in Computer Science) (en Inglés) - Gee James C.,Alexander Daniel C.,Hong Jaesung

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Reseña del libro "Medical Image Computing and Computer Assisted Intervention – Miccai 2025: 28Th International Conference, Daejeon, South Korea, September 23–27, 2025,. Part x (Lecture Notes in Computer Science) (en Inglés)"

The 16-volume set LNCS 15960 - 15975 constitutes the refereed proceedings of the 28th International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2025, which took place in Daejeon, South Korea, during September 23-27, 2025. The total of 1027 papers included in the proceedings was carefully reviewed and selected from 3447 submissions. They were organized in topical parts as follows: Part I, LNCS Volume 15960: Multimodal Fusion and Contextual Reasoning in Medical Imaging Part II, LNCS Volume 15961: Surgical Navigation, Scene Understanding, and Video Modeling Part III, LNCS Volume 15962: Learning and Augmented Reality for Surgical and Endoscopic Applications (I) Part IV, LNCS Volume 15963: Learning and Augmented Reality for Surgical and Endoscopic Applications (II) Part V, LNCS Volume 15964: Graph-Based Methods in Medical Imaging Part VI, LNCS Volume 15965: Datasets and Methods for Image Quality Enhancement Part VII, LNCS Volume 15966: Trustworthy and Responsible AI for Medical Imaging Part VIII, LNCS Volume 15967: Multimodal Learning for Diagnosis, Risk Prediction, and Survival Analysis Part IX, LNCS Volume 15968: Core Techniques in Medical Imaging: Segmentation, Registration, Synthesis, Reconstruction, and Other Emerging Methods (I) Part X, LNCS Volume 15969: Core Techniques in Medical Imaging: Segmentation, Registration, Synthesis, Reconstruction, and Other Emerging Methods (II) Part XI, LNCS Volume 15970: Core Techniques in Medical Imaging: Segmentation, Registration, Synthesis, Reconstruction, and Other Emerging Methods (III) Part XII, LNCS Volume 15971: Core Techniques in Medical Imaging: Segmentation, Registration, Synthesis, Reconstruction, and Other Emerging Methods (IV) Part XIII, LNCS Volume 15972: Adapting Foundation Models for Medical Imaging: LLMs, VLMs, and Cross-Domain Generalization (I) Part XIV, LNCS Volume 15973: Adapting Foundation Models for Medical Imaging: LLMs, VLMs, and Cross-Domain Generalization (II) Part XV, LNCS Volume 15974: Adapting Foundation Models for Medical Imaging: LLMs, VLMs, and Cross-Domain Generalization (III) Part XVI, LNCS Volume 15975: Statistical Techniques in Medical Imaging: Causality, Imputation, Weak Supervision, and Other Methods

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