| 书目名称 | Deep Learning and Medical Applications | | 编辑 | Jin Keun Seo | | 视频video | | | 概述 | Provides an understanding of the interfaces between the model and other factors, and of clinical applications.Offers comprehensive, in-depth understanding of deep learning-based medical image‘analysis | | 丛书名称 | Mathematics in Industry | | 图书封面 |  | | 描述 | Over the past 40 years, diagnostic medical imaging has undergone remarkable advancements in CT, MRI, and ultrasound technology. Today, the field is experiencing a major paradigm shift, thanks to significant and rapid progress in deep learning techniques. As a result, numerous innovative AI-based programs have been developed to improve image quality and enhance clinical workflows, leading to more efficient and accurate diagnoses..AI advancements of medical imaging not only address existing unsolved problems but also present new and complex challenges. Solutions to these challenges can improve image quality and reveal new information currently obscured by noise, artifacts, or other signals. Holistic insight is the key to solving these challenges. Such insight may lead to a creative solution only when it is based on a thorough understanding of existing methods and unmet demands..This book focuses on advanced topics in medical imagingmodalities, including CT and ultrasound, with the aim of providing practical applications in the healthcare industry. It strikes a balance between mathematical theory, numerical practice, and clinical applications, offering comprehensive coverage from basi | | 出版日期 | Book 2023 | | 关键词 | Medical image computing; Image reconstruction method; Nonlinear inverse problems; Mathematical modeling | | 版次 | 1 | | doi | https://doi.org/10.1007/978-981-99-1839-3 | | isbn_softcover | 978-981-99-1841-6 | | isbn_ebook | 978-981-99-1839-3Series ISSN 1612-3956 Series E-ISSN 2198-3283 | | issn_series | 1612-3956 | | copyright | The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapor |
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发表于 2025-3-21 19:47:53
