Machine Learning in Medical Imaging

12th International Workshop, MLMI 2021, Held in Conjunction with MICCAI 2021, Strasbourg, France, September 27, 2021, Proceedings
1. Auflage 2021
ISBN: 978-3-030-87588-6
Verlag: Springer International Publishing

Buch, Englisch, 704 Seiten, Format (B × H): 155 mm x 235 mm, Gewicht: 1077 g

Reihe: Image Processing, Computer Vision, Pattern Recognition, and Graphics

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.

Zielgruppe

Research

Autoren/Hrsg.

Lian, Chunfeng

Cao, Xiaohuan

Yan, Pingkun

Rekik, Islem

Xu, Xuanang

Fachgebiete

• Mathematik | Informatik EDV | Informatik Informatik Bildsignalverarbeitung
• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Computer Vision

Inhaltsverzeichnis

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