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This book presents a series of revised papers selected from the First MICCAI Meets Africa Workshop, MImA 2024, and First MICCAI Workshop on Empowering Medical Information Computing and Research through Early-Career Expertise, EMERGE 2024, which was held in Marrakesh, Morocco, during October 6, 2024.MImA 2024 accepted 21 full papers from 45 submissions; for EMERGE 8 papers are included from 9 submissions. They describe cutting-edge research from computational scientists and clinical researchers working on a variety of medical image computing challenges relevant to the African and broader global contexts, as well as emerging techniques for image computing methods tailored to low-resource settings.
- Nyhet
828 kr
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This book presents a series of revised papers selected from the Second MICCAI Student Board Workshop, EMERGE 2025, Held in Conjunction with MICCAI 2025, Daejeon, South Korea, September 23, 2025, Proceedings.The 13 full papers presented in this book were carefully reviewed and selected from 19 submissions. These papers were organized in the following topical sections: Foundation Models and Generalization in Medical AI; Representation Learning for Detection and Diagnosis; Signals, Bias, and Structure in Medical Data; Poster Presentations.
- Nyhet
Medical Image Computing and Computer Assisted Intervention – MICCAI 2025 Doctoral Symposium
Held in Conjunction with MICCAI 2025, Daejeon, South Korea, September 23–27, 2025, Proceedings
Häftad, Engelska, 2026
1 573 kr
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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.