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首页> 外文期刊>BMC Bioinformatics >Real-time interactive data mining for chemical imaging information: application to automated histopathology
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Real-time interactive data mining for chemical imaging information: application to automated histopathology

机译:化学成像信息的实时交互式数据挖掘:在自动化组织病理学中的应用

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Background Vibrational spectroscopic imaging is now used in several fields to acquire molecular information from microscopically heterogeneous systems. Recent advances have led to promising applications in tissue analysis for cancer research, where chemical information can be used to identify cell types and disease. However, recorded spectra are affected by the morphology of the tissue sample, making identification of chemical structures difficult. Results Extracting features that can be used to classify tissue is a cumbersome manual process which limits this technology from wide applicability. In this paper, we describe a method for interactive data mining of spectral features using GPU-based manipulation of the spectral distribution. Conclusions This allows researchers to quickly identify chemical features corresponding to cell type. These features are then applied to tissue samples in order to visualize the chemical composition of the tissue without the use of chemical stains.
机译:背景技术振动光谱成像现在被用于多个领域,以从微观异质系统中获取分子信息。最近的进展已导致在癌症研究的组织分析中有希望的应用,其中化学信息可用于识别细胞类型和疾病。然而,记录的光谱受组织样品的形态的影响,从而使化学结构的鉴定变得困难。结果提取可用于对组织进行分类的功能是一个繁琐的手动过程,这限制了该技术的广泛应用。在本文中,我们描述了一种基于光谱分布的基于GPU的光谱特征交互式数据挖掘方法。结论这使研究人员可以快速识别与细胞类型相对应的化学特征。然后将这些特征应用于组织样本,以便在不使用化学染色剂的情况下可视化组织的化学组成。

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