biomedical图像分析：在MRI和CT扫描中的特殊应用

English | 2024 | ISBN-10: 9819999383 | 177 pages| Epub PDF (True) | 53 MB

This book provides an in-depth study of biomedical image analysis. It reviews and summarizes previous research work in biomedical image analysis and also provides a brief introduction to other computation techniques, such as fuzzy sets, neutrosophic sets, clustering algorithm and fast forward quantum optimization algorithm, focusing on how these techniques can be integrated into different phases of the biomedical image analysis. In particular, this book describes novel methods resulting from the fuzzy sets, neutrosophic sets, clustering algorithm and fast forward quantum optimization algorithm. It also demonstrates how a new quantum-clustering based model can be successfully applied in the context of clustering the COVID-19 CT scans. Thanks to its easy-to-read style and the clear explanati ons of the models, the book can be used as a concise yet comprehensive reference guide to biomedical image analysis, and will be valuable not only for graduate students, but also forresearchers and professionals working for academic, business and government

这本书深入研究了生物医学图像分析。它回顾和总结了以往的研究工作，并简要介绍了其他计算技术，如模糊集合、邻近集、聚类算法及快速前向量子优化算法，重点讲述这些技术如何融入生物医学图像分析的不同阶段。特别是，本书描述了由模糊集合、邻近集、聚类算法和快速前向量子优化算法所衍生的新方法。它还展示了基于量子聚类的新模型在CT扫描数据聚类中的成功应用。由于其易读性以及对模型清晰的解释，这本书可以作为简明而全面的参考指南用于生物医学图像分析，并且不仅适合研究生使用，也适用于学术、商业和政府领域的研究者和专业人士。

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