
Machine Learning in Medical Imaging
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.- Alaotsikko
- 12th International Workshop, MLMI 2021, Held in Conjunction with MICCAI 2021, Strasbourg, France, September 27, 2021, Proceedings
- Toimittaja
- Chunfeng Lian, Xiaohuan Cao, Islem Rekik, Xuanang Xu, Pingkun Yan
- Painos
- 1st ed. 2021
- ISBN
- 9783030875886
- Kieli
- englanti
- Paino
- 310 grammaa
- Julkaisupäivä
- 27.9.2021
- Kustantaja
- Springer Nature Switzerland AG
- Sivumäärä
- 704