Automated Abnormality Classification of Chest Radiographs using MobileNetV2

机译：使用MobileNetV2对胸部X光片进行自动异常分类

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Chest X-ray is one of the most common screening and diagnostic radiological examinations for the detection of many lung diseases. Undoubtedly, evaluation of patient data and expert decisions are the most important factors in diagnosis. However, expert sys

机译：胸部X光检查是用于检测许多肺部疾病的最常见的筛查和放射诊断检查之一。毫无疑问，对患者数据的评估和专家决策是诊断中最重要的因素。但是，专家系统

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《International Congress on Human-Computer Interaction, Optimization and Robotic Applications》|2020年|1-4|共4页
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Secil Genc; Kubra Nur Akpinar; Serap Karagol;
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Histograms; Diseases; Machine learning; X-ray imaging; Adaptive equalizers; Diagnostic radiography; Lung;

机译：直方图;疾病;机器学习; X射线成像;自适应均衡器;放射诊断;肺;

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1. Automated abnormality classification of chest radiographs using deep convolutional neural networks [J] . Yu-Xing Tang, You-Bao Tang, Yifan Peng, npj Digital Medicine . 2020,第1期

机译：使用深卷积神经网络自动化胸部射线照相的异常分类
2. Zone-based analysis for automated detection of abnormalities in chest radiographs. [J] . Kao EF, Kuo YT, Hsu JS, Medical Physics . 2011,第7期

机译：基于区域的分析可自动检测胸部X光片中的异常。
3. Projection profile analysis for automated detection of abnormalities in chest radiographs. [J] . Kao EF, Lee C, Hsu JS, Medical Physics . 2006,第1期

机译：投影轮廓分析可自动检测胸部X光片中的异常。
4. Assessment of Data Augmentation Strategies Toward Performance Improvement of Abnormality Classification in Chest Radiographs [C] . Prasanth Ganesan, Sivaramakrishnan Rajaraman, Rodney Long, Annual International Conference of the IEEE Engineering in Medicine and Biology Society . 2019

机译：评估胸部X光片异常分类表现的数据增强策略的评估
5. Automated lung segmentation in digital posteroanterior and lateral chest radiographs: Applications in diagnostic radiology and nuclear medicine. [D] . Armato, Samuel G., III. 1997

机译：数字式后前胸片和外侧胸片中的自动肺分割：在放射诊断和核医学中的应用。
6. Automated abnormality classification of chest radiographs using deep convolutional neural networks [O] . Yu-Xing Tang, You-Bao Tang, Yifan Peng, 2020

机译：使用深度卷积神经网络对胸部X光片进行自动异常分类
7. Automated abnormality classification of chest radiographs using deep convolutional neural networks [O] . Yu-Xing Tang, You-Bao Tang, Yifan Peng, 2020

机译：使用深卷积神经网络自动化胸部射线照相的异常分类
8. NIOSH Health Hazard Evaluation Report HETA 90-0340-2659, A Trial of Additional211 Composite Standard Radiographs for Use with the ILO International Classification 211 of Radiographs of Pneumoconioses, Morgantown, West Virginia [R] . Jacobsen, M., Miller, W. E., Parker, J. E. 1999

机译：NIOsH健康危害评估报告HETa 90-0340-2659，用于国际劳工组织国际分类的附加211复合标准射线照片的试验211西弗吉尼亚州摩根敦的肺尘病射线照片

Automated Abnormality Classification of Chest Radiographs using MobileNetV2

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