Multiscale Multimodal Medical Imaging

This book constitutes the refereed proceedings of the First International Workshop on Multiscale Multimodal Medical Imaging, MMMI 2019, held in conjunction with MICCAI 2019 in Shenzhen, China, in October 2019.

The 13 papers presented were carefully reviewed and selected from 18 submissions. The MMMI workshop aims to advance the state of the art in multi-scale multi-modal medical imaging, including algorithm development, implementation of methodology, and experimental studies. The papers focus on medical image analysis and machine learning, especially on machine learning methods for data fusion and multi-score learning.

• artificial intelligence
• biomedical imaging
• color image processing
• computer vision
• image analysis
• image enhancement
• image processing
• image quality
• image reconstruction
• image segmentation
• imaging systems
• machine learning
• neural networks
• pattern recognition

• Harvard Medical School, Boston, USA

  Quanzheng Li, Xiang Li

• University of Southern California, Los Angeles, USA

  Richard Leahy

• Peking University, Beijing, China

  Bin Dong

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