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Special issue on deep learning in biomedical signal and medical image processing [1128 T]

机译:生物医学信号深度学习的特殊问题及医学图像处理[1128 T]

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摘要

Recent improvements in artificial intelligence, big data and machine learning have enhanced the importance of biomedical signal and image processing research. Biomedical signal processing requires the analysis of measurements at specific periods in time and noted on a patient's chart to provide useful infonnation upon which clinicians can make determinations. Biomedical image processing is similar in concept to biomedical signal processing in multiple dimensions. It includes the analysis, enhancement and presentation of images captured via X-Ray, Ultrasound, MRI, nuclear medicine and visual imaging technologies. Deep learning is now quickly extending in all science and engineering research fields, including biomedical sciences. It is practised to build computational intelligent models directly from the biomedical signals.
机译:最近的人工智能,大数据和机器学习的改进增强了生物医学信号和图像处理研究的重要性。生物医学信号处理需要在特定时段及时分析测量,并在患者的图表上注明,以提供有用的信息,临床医生可以进行确定。生物医学图像处理在概念上与多维的生物医学信号处理类似。它包括通过X射线,超声波,MRI,核医学和视觉成像技术捕获的图像的分析,增强和呈现。深度学习现在正在迅速在所有科学和工程研究领域延伸,包括生物医学科学。它是直接从生物医学信号构建计算智能模型。

著录项

  • 来源
    《Multimedia Tools and Applications》 |2020年第14期|9161-9161|共1页
  • 作者

    Tao Hu; Liu Liu; Wen Si;

  • 作者单位

    Kent State University Kent OH USA;

    Nanjing University of Posts and Telecommunications Nanjing China;

    College of Engineering University of South Florida Tampa FL USA;

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  • 正文语种 eng
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