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A review of the medical hyperspectral imaging systems and unmixing algorithms' in biological tissues

机译:生物组织中医学高光谱成像系统和解密算法的综述

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摘要

Hyperspectral fluorescence imaging (HFI) is a well-known technique in the medical research field and is considered a non-invasive tool for tissue diagnosis. This review article gives a brief introduction to acquisition methods, including the image preprocessing methods, feature selection and extraction methods, data classifi-cation techniques and medical image analysis along with recent relevant references. The process of fusion of unsupervised unmixing techniques with other classification methods, like the combination of support vector machine with an artificial neural network, the latest snapshot Hyperspectral imaging (HSI) and vortex analysis techniques are also outlined. Finally, the recent applications of hyperspectral images in cellular differentiation of various types of cancer are discussed.
机译:高光谱荧光成像(HFI)是医学研究领域中的众所周知的技术,被认为是一种用于组织诊断的非侵入性工具。本综述文章简要介绍了采集方法,包括图像预处理方法,特征选择和提取方法,数据分类技术和医学图像分析以及最近的相关参考。融合无监督的解密技术与其他分类方法,如支持向量机的组合,如具有人工神经网络的支持矢量机,最新的快照高光谱成像(HSI)和涡旋分析技术也在概述中。最后,讨论了近期斑谱图像在各种类型癌症的细胞分化中的应用。

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