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Medical Image Computing and Computer Assisted Intervention - MICCAI 2025 Doctoral Symposium
Medical Image Computing and Computer Assisted Intervention - MICCAI 2025 Doctoral Symposium
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This book constitutes the refereed proceedings of the first MICCAI Doctoral Symposium, held in conjunction with 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 28 full papers included in this book were carefully reviewed and selected from 28 submissions. They were organized in topical sections as follows: Neuroimaging and Neurovascular Analysis; Cardiovascula…

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This book constitutes the refereed proceedings of the first MICCAI Doctoral Symposium, held in conjunction with 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 28 full papers included in this book were carefully reviewed and selected from 28 submissions. They were organized in topical sections as follows: Neuroimaging and Neurovascular Analysis; Cardiovascular and Pulmonary Imaging; Computational Pathology and Cancer Imaging; Machine Learning – Fairness and Multimodal Learning; Machine Learning – Representation Learning and Foundation Models; Image Reconstruction, Segmentation, and Radiotherapy; and Surgical and Clinical Video Analysis.

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This book constitutes the refereed proceedings of the first MICCAI Doctoral Symposium, held in conjunction with 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 28 full papers included in this book were carefully reviewed and selected from 28 submissions. They were organized in topical sections as follows: Neuroimaging and Neurovascular Analysis; Cardiovascular and Pulmonary Imaging; Computational Pathology and Cancer Imaging; Machine Learning – Fairness and Multimodal Learning; Machine Learning – Representation Learning and Foundation Models; Image Reconstruction, Segmentation, and Radiotherapy; and Surgical and Clinical Video Analysis.

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