书目名称 | Data-Driven Clinical Decision-Making Using Deep Learning in Imaging |
编辑 | M. F. Mridha,Nilanjan Dey |
视频video | |
概述 | Explores cutting-edge medical imaging advancements and their applications in clinical decision-making.Addresses the development of multimodal machine learning models.Brings together a global network o |
丛书名称 | Studies in Big Data |
图书封面 |  |
描述 | .This book explores cutting-edge medical imaging advancements and their applications in clinical decision-making. The book contains various topics, methodologies, and applications, providing readers with a comprehensive understanding of the field‘s current state and prospects. It begins with exploring domain adaptation in medical imaging and evaluating the effectiveness of transfer learning to overcome challenges associated with limited labeled data. The subsequent chapters delve into specific applications, such as improving kidney lesion classification in CT scans, elevating breast cancer research through attention-based U-Net architecture for segmentation and classifying brain MRI images for neurological disorders. Furthermore, the book addresses the development of multimodal machine learning models for brain tumor prognosis, the identification of unique dermatological signatures using deep transfer learning, and the utilization of generative adversarial networks to enhance breast cancer detection systems by augmenting mammogram images. Additionally, the authors present a privacy-preserving approach for breast cancer risk prediction using federated learning, ensuring the confiden |
出版日期 | Book 2024 |
关键词 | Medical Imaging; Breast Cancer; Deep Learning; Machine Learning; Convolutional Neural Network; Optimizati |
版次 | 1 |
doi | https://doi.org/10.1007/978-981-97-3966-0 |
isbn_softcover | 978-981-97-3968-4 |
isbn_ebook | 978-981-97-3966-0Series ISSN 2197-6503 Series E-ISSN 2197-6511 |
issn_series | 2197-6503 |
copyright | The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapor |