Among various medical imaging tools, chest radiographs are the most important and widely used diagnostic tool for detection of thoracic pathologies. Research is being carried out in order to propose robust automatic diagnostic tool for detection of pathologies from chest radiographs. Artificial Intelligence techniques especially deep learning methodologies have found to be giving promising results in automating the field of medicine. Lot of research has been done for automatic and fast detection of pneumothorax from chest radiographs while proposing several frameworks based on artificial intelligence and machine learning techniques. This study summarizes the existing literature for the automatic detection of pneumothorax from chest x-rays along with describing the available chest radiographs datasets. The comparative analysis of the literature is also provided in terms of goodness. Limitations of the existing literature along with the research gaps is also given for further investigation. The paper provides a brief overview of the present work for pneumothorax detection for helping the researchers in selection of optimal approach for future research.
翻译:在各种医学成像工具中,胸透射仪是用于检测胸腔病理的最重要和广泛使用的诊断工具,目前正在进行研究,以提出健全的自动诊断工具,用于检测胸腔射线病理,人工智能技术,特别是深层学习方法,发现在医学领域自动化方面产生了大有希望的结果,对胸腔射电图中的肺炎球菌的自动和快速检测进行了大量研究,同时根据人工智能和机器学习技术提出了若干框架,该研究总结了从胸部X射线中自动检测肺炎球菌的现有文献,同时描述了现有的胸部射电图数据集,对文献的比较分析也以良好方式提供,对现有文献的局限性以及研究差距也作了进一步调查,论文简要概述了目前为帮助研究人员选择未来研究的最佳方法而进行的肺透风学检测工作。