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<p><span style="font-size: 11.0pt; font-family: 'Calibri',sans-serif;">This book constitutes the refereed proceedings of the 16th International Workshop on <span class="mx-text">Machine Learning in Medical Imaging</span>, MLMI 2025, held in Conjunction with MICCAI 2025, Daejeon, South Korea, on&#xa0;September 23, 2025.</span></p><p><span style="font-size: 11.0pt; font-family: 'Calibri',sans-serif;">The 65 full papers included in this book were carefully reviewed and selected from 101 submissions. They focus on advanced scientific research </span><span style="font-size: 11.0pt; font-family: 'Calibri',sans-serif; mso-fareast-font-family: 'Google Sans Text'; color: #1b1c1d;">covering topics such as deep learning, foundation models, generative learning, and statistical methods with their applications to computer-aided diagnosis, multi-modality fusion, image reconstruction, digital pathology, and large-scale data analytics.&#xa0;</span></p>

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Machine Learning in Medical Imaging

  • 会议论文集

  • 发表日期：

    2026年

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摘要

This book constitutes the refereed proceedings of the 16th International Workshop on Machine Learning in Medical Imaging, MLMI 2025, held in Conjunction with MICCAI 2025, Daejeon, South Korea, on September 23, 2025.

The 65 full papers included in this book were carefully reviewed and selected from 101 submissions. They focus on advanced scientific research covering topics such as deep learning, foundation models, generative learning, and statistical methods with their applications to computer-aided diagnosis, multi-modality fusion, image reconstruction, digital pathology, and large-scale data analytics.