用于生物医学图像计算的多维调幅调频模型与方法。
Multidimensional AM-FM models and methods for biomedical image computing.
作者信息
Pattichis M S
机构信息
Department of Electrical and Computer Engineering, University of New Mexico, Albuquerque, USA.
出版信息
Annu Int Conf IEEE Eng Med Biol Soc. 2009;2009:5641-4. doi: 10.1109/IEMBS.2009.5333763.
This paper provides an overview of multidimensional AM-FM methods for analyzing medical images and videos. Over the last decade, several new AM-FM demodulation methods have been developed. We provide a discussion of what many of these methods share in common, and give some details on recent, Hilbert-based approaches. Medical image applications range from medical image segmentation, resolution enhancement, classification, reconstruction to new methods for video motion estimation. A brief summary of suggestions for future work in this area is also given.
本文概述了用于分析医学图像和视频的多维调幅调频（AM-FM）方法。在过去十年中，已经开发了几种新的AM-FM解调方法。我们讨论了这些方法中的许多共同之处，并详细介绍了最近基于希尔伯特变换的方法。医学图像应用范围从医学图像分割、分辨率增强、分类、重建到视频运动估计的新方法。本文还简要总结了该领域未来工作的建议。
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