Artificial intelligence (AI) as an emerging technology is gaining momentum in medical imaging. Of all the advances in modern medicine, medical imaging is among the most remarkable developments.
We are hoping this collection will further the understanding of AI in medical imaging, highlight its versatility and applications, can help enhance medical screenings, improve precision medicine, assess patient risk factors, and lighten the load for physicians.
Artificial intelligence (AI) is an innovative and by all odds, a life-changing tool in Medical Imaging. AL algorithms, particularly Deep Learning have gain ground in image-recognition tasks. Methods ranging from convolutional neural networks to variational autoencoders have found plethora of applications in the medical image analysis field, propelling it forward at a rapid pace. AI can automatically recognize and analyze complex patterns in large sets of imaging data with excellent accuracy, sensitivity and specificity. This will lead to better disease prediction and therapy planning. As AI is gaining momentum in Imaging and Diagnostics, the time is ripe to prioritize innovation, scrutiny and research programs. This book aims to improve the clinical efficiency, as well as spare no effort to probe the different types of technological advancements to get more reliable and accurate diagnostic conclusion, which will function as a second opinion to support the medical professionals. The book carefully articulates a wide spectrum of paradigms like segmentation, feature extraction, feature selection, and classification using ML/DL.
This book will aim to provide relevant frameworks and latest empirical research findings in this domain. It will address the myriad of applications of AI in medical imaging whilst aiding relevant researches to understand the complexities and to translate it into practice effectively.
Submitted manuscripts must following formats available at Springer website. Manuscripts should be at most 10 pages (content) + 2 pages (references and acknowledgements)
- Originality: Each chapter must be an original analysis and must be the author’s own work. Chapters already published are not eligible.
- Coauthors: Chapters written solo or co-authored are permitted.
- One Submission: Participants can submit only one chapter, whether as sole author or coauthor.
Scientific Reviewing Committee
TBA – A group of Scientists, Engineers, Doctors and Professionals
No chapter submission / competition entry fees or any registration fees.
Scope of the Book
The topics of interest include, but are not limited to, the following:
- The Role of Medical Image Computing and Machine Learning in Healthcare
- Deep Learning for Medical Imaging
- Medical Image analysis with Intelligent Techniques
- Intelligent Techniques for Smart Health care
- Medical Imaging with Deep Neural Networks
- Advanced classifier for medical Image classification
- Advanced and hybrid classification models for medical Images
- Efficient Deep Learning Approaches for Health Informatics
- Medical Image Analysis, Processing and Enhancement
- Intelligent Techniques in Medical Image Segmentation
- Security and Privacy aspects in Medical Imaging
- Importance of emerging technologies in Medical Imaging
Chapter Submission: 01-Sep-2022
Finalists Announcement: 15-Sep-2022
Chapter Selection Date: 26-Sep-2022