
Machine Learning in Medical Imaging
The 48 full papers presented in this volume were carefully reviewed and selected from 64 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.
- Alaotsikko
- 13th International Workshop, MLMI 2022, Held in Conjunction with MICCAI 2022, Singapore, September 18, 2022, Proceedings
- Toimittaja
- Chunfeng Lian, Xiaohuan Cao, Islem Rekik, Xuanang Xu, Zhiming Cui
- Painos
- 1st ed. 2022
- ISBN
- 9783031210136
- Kieli
- englanti
- Paino
- 310 grammaa
- Julkaisupäivä
- 16.12.2022
- Kustantaja
- Springer International Publishing AG
- Sivumäärä
- 479