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State of the Art in Information Extraction and Quantitative Analysis for Multimodality Biomolecular Imaging

机译：多模态生物分子成像的信息提取和定量分析的最新技术

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摘要

Rapid advances in optical instrumentation, high-speed cameras, and fluorescent probes have spurred tremendous growth in the volume of biomolecular imaging data. Various optical imaging modalities are used for probing biological systems in vivo and in vitro. These include traditional two-dimensional imaging, three-dimensional confocal imaging, time-lapse imaging, and multispectral imaging. Many applications require a combination of these imaging modalities, which gives rise to huge data sets. However, lack of powerful information extraction and quantitative analysis tools poses a major hindrance to exploiting the full potential of the information content of these data. In particular, automated extraction of semantic information from multimodality imaging data, crucial for understanding biological processes, poses unique challenges. Information extraction from large sets of biomolecular imaging data requires modeling at multiple levels of detail to allow not only quantitative analysis but also interpretation and extraction of high-level semantic information. In this paper, we survey the state of the art in the area of information extraction and automated analysis tools for in vivo and in vitro biomolecular imaging. The modeling and knowledge extraction for these data require sophisticated image processing and machine learning techniques, as well as formalisms for information extraction and knowledge management. Development of such tools has the potential to significantly improve biological discovery and drug development processes.
机译：光学仪器，高速相机和荧光探针的飞速发展刺激了生物分子成像数据量的巨大增长。各种光学成像方式被用于在体内和体外探测生物系统。这些包括传统的二维成像，三维共聚焦成像，延时成像和多光谱成像。许多应用需要这些成像模式的组合，从而产生了巨大的数据集。但是，缺乏功能强大的信息提取和定量分析工具对利用这些数据的信息内容的全部潜力构成了重大障碍。特别地，从多模态成像数据中自动提取语义信息对理解生物学过程至关重要，这带来了独特的挑战。从大量生物分子成像数据中提取信息需要在多个细节级别进行建模，以便不仅可以进行定量分析，还可以解释和提取高级语义信息。在本文中，我们概述了用于体内和体外生物分子成像的信息提取和自动分析工具领域的最新技术。这些数据的建模和知识提取需要复杂的图像处理和机器学习技术，以及信息提取和知识管理的形式主义。此类工具的开发具有显着改善生物学发现和药物开发过程的潜力。

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