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Towards the Semantic Enrichment of Free-Text Annotation of Image Quality Assessment for UK Biobank Cardiac Cine MRI Scans

机译:对英国生物库心脏电影MRI扫描图像质量评估的自由文本注释的语义扩展

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摘要

Image quality assessment is fundamental as it affects the level of confidence in any output obtained from image analysis. Clinical research imaging scans do not often come with an explicit evaluation of their quality, however reports are written associated to the patient/volunteer scans. This rich free-text documentation has the potential to provide automatic image quality assessment if efficiently processed and structured. This paper aims at showing how the use of Semantic Web technology for structuring free-text documentation can provide means for automatic image quality assessment. We aim to design and implement a semantic layer for a special dataset, the annotations made in the context of the UK Biobank Cardiac Cine MRI pilot study. This semantic layer will be a powerful tool to automatically infer or validate quality scores for clinical images and efficiently query image databases based on quality information extracted from the annotations. In this paper we motivate the need for this semantic layer, present an initial version of our ontology as well as preliminary results. The presented approach has the potential to be extended to broader projects and ultimately employed in the clinical setting.
机译:图像质量评估至关重要,因为它会影响从图像分析获得的任何输出的置信度。临床研究成像扫描通常不会对其质量进行明确评估,但是会撰写与患者/志愿者扫描相关的报告。如果处理和结构合理,此丰富的自由文本文档可能会提供自动图像质量评估。本文旨在展示如何使用语义网技术来构建自由文本文档,从而为自动图像质量评估提供手段。我们旨在为特殊数据集设计和实现语义层,这些注释是在英国生物银行心脏电影MRI试点研究的背景下做出的。该语义层将是一个强大的工具,可以自动推断或验证临床图像的质量得分,并基于从注释中提取的质量信息有效地查询图像数据库。在本文中,我们激发了对语义层的需求,提出了本体的初始版本以及初步结果。提出的方法有可能被扩展到更广泛的项目,并最终应用于临床。

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    Radcliffe Department of Medicine, Oxford Centre for Clinical Magnetic Resonance Research (OCMR), University of Oxford, Oxford, UK;

    Information Systems Group, Department of Computer Science, University of Oxford, Oxford, UK;

    Radcliffe Department of Medicine, Oxford Centre for Clinical Magnetic Resonance Research (OCMR), University of Oxford, Oxford, UK;

    William Harvey Research Institute, NIHR Cardiovascular Biomedical Research Unit at Barts, Queen Mary University of London, London, UK;

    William Harvey Research Institute, NIHR Cardiovascular Biomedical Research Unit at Barts, Queen Mary University of London, London, UK;

    William Harvey Research Institute, NIHR Cardiovascular Biomedical Research Unit at Barts, Queen Mary University of London, London, UK;

    William Harvey Research Institute, NIHR Cardiovascular Biomedical Research Unit at Barts, Queen Mary University of London, London, UK;

    Radcliffe Department of Medicine, Oxford Centre for Clinical Magnetic Resonance Research (OCMR), University of Oxford, Oxford, UK;

    William Harvey Research Institute, NIHR Cardiovascular Biomedical Research Unit at Barts, Queen Mary University of London, London, UK;

    Information Systems Group, Department of Computer Science, University of Oxford, Oxford, UK;

    Radcliffe Department of Medicine, Oxford Centre for Clinical Magnetic Resonance Research (OCMR), University of Oxford, Oxford, UK;

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  • 入库时间 2022-08-26 14:01:26

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