| 書目名稱 | Digital Molecular Magnetic Resonance Imaging |
| 編輯 | Bamidele O. Awojoyogbe,Michael O. Dada |
| 視頻video | http://file.papertrans.cn/285/284722/284722.mp4 |
| 概述 | Presents computational and digital algorithms enabling the understanding of intricate structures in the human body.Discusses enhanced capabilities of MRI visualization to a level of anatomical visuali |
| 叢書名稱 | Series in BioEngineering |
| 圖書封面 |  |
| 描述 | .This book pushes the limits of conventional MRI visualization methods by completely changing the medical imaging landscape and leads to innovations that will help patients and healthcare providers alike. It enhances the capabilities of MRI anatomical visualization to a level that has never before been possible for researchers and clinicians. The computational and digital algorithms developed can enable a more thorough understanding of the intricate structures found within the human body, surpassing the constraints of traditional 2D methods. The Physics-informed Neural Networks as presented can enhance three-dimensional rendering for deeper understanding of the spatial relationships and subtle abnormalities of anatomical features and sets the stage for upcoming advancements that could impact a wider range of digital heath modalities. This book opens the door to ultra-powerful digital molecular MRI powered by quantum computing that can perform calculations that would take supercomputers millions of years.. |
| 出版日期 | Book 2024 |
| 關(guān)鍵詞 | Bloch NMR; Physics-informed neural networks (PINNs); Magnetic resonance relaxometry; Machine learning m |
| 版次 | 1 |
| doi | https://doi.org/10.1007/978-981-97-6370-2 |
| isbn_softcover | 978-981-97-6372-6 |
| isbn_ebook | 978-981-97-6370-2Series ISSN 2196-8861 Series E-ISSN 2196-887X |
| issn_series | 2196-8861 |
| copyright | The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapor |
|Archiver|手機(jī)版|小黑屋|
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