Machine Learning in Medical Imaging
This book constitutes the proceedings of the 11th International Workshop on Machine Learning in Medical Imaging, MLMI 2020, held in conjunction with MICCAI 2020, in Lima, Peru, in October 2020. The conference was held virtually due to the COVID-19 pandemic.
The 68 papers presented in this volume were carefully reviewed and selected from 101 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.
- प्रतिलिपि अधिकार:
- 2020 Springer
- Book Quality:
- Springer International Publishing
- Date of Addition:
- Art and Architecture, Computers and Internet, Nonfiction,
- Usage Restrictions:
- This is a copyrighted book.
Choosing a Book Format
EPUB is the standard publishing format used by many e-book readers including iBooks, Easy Reader, VoiceDream Reader, etc. This is the most popular and widely used format.
DAISY format is used by GoRead, Read2Go and most Kurzweil devices.
Audio (MP3) format is used by audio only devices, such as iPod.
Braille format is used by Braille output devices.
DAISY Audio format works on DAISY compatible players such as Victor Reader Stream.
Accessible Word format can be unzipped and opened in any tool that supports .docx files.