Machine Learning in Medical Imaging (eBook, PDF)

12th International Workshop, MLMI 2021, Held in Conjunction with MICCAI 2021, Strasbourg, France, September 27, 2021, Proceedings
Redaktion: Lian, Chunfeng; Yan, Pingkun; Xu, Xuanang; Rekik, Islem; Cao, Xiaohuan

• Format: PDF

Produktbeschreibung

This book constitutes the proceedings of the 12th International Workshop on Machine Learning in Medical Imaging, MLMI 2021, held in conjunction with MICCAI 2021, in Strasbourg, France, in September 2021.*

The 71 papers presented in this volume were carefully reviewed and selected from 92 submissions. They focus on major trends and challenges in the above-mentioned area, aiming to identify new-cutting-edge techniques and their uses in medical imaging. Topics dealt with are: deep learning, generative adversarial learning, ensemble learning, sparse learning, multi-task learning, multi-view learning, manifold learning, and reinforcement learning, with their applications to medical image analysis, computer-aided detection and diagnosis, multi-modality fusion, image reconstruction, image retrieval, cellular image analysis, molecular imaging, digital pathology, etc.

*The workshop was held virtually.

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Produktdetails

• Verlag: Springer International Publishing
• Seitenzahl: 704
• Erscheinungstermin: 25. September 2021
• Englisch
• ISBN-13: 9783030875893
• Artikelnr.: 62634269

Inhaltsangabe

Contrastive Representations for Continual Learning of Fine-grained Histology Images.-