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《INTERNATIONAL JOURNAL OF IMAGING SYSTEMS AND TECHNOLOGY》杂志封面

《INTERNATIONAL JOURNAL OF IMAGING SYSTEMS AND TECHNOLOGY》中科院JCR分区

  • 2025年3月升级版:
  • 大类小类学科Top综述期刊
    计算机科学 4区
    ENGINEERING, ELECTRICAL & ELECTRONIC
    工程:电子与电气
    4区
    IMAGING SCIENCE & PHOTOGRAPHIC TECHNOLOGY
    成像科学与照相技术
    4区
    OPTICS
    光学
    4区

  • 2023年12月升级版:
  • 大类小类学科Top综述期刊
    计算机科学 4区
    ENGINEERING, ELECTRICAL & ELECTRONIC
    工程:电子与电气
    4区
    IMAGING SCIENCE & PHOTOGRAPHIC TECHNOLOGY
    成像科学与照相技术
    4区
    OPTICS
    光学
    4区

    《INTERNATIONAL JOURNAL OF IMAGING SYSTEMS AND TECHNOLOGY》期刊简介:

    The International Journal of Imaging Systems and Technology (IMA) is a forum for the exchange of ideas and results relevant to imaging systems, including imaging physics and informatics. The journal covers all imaging modalities in humans and animals.

    IMA accepts technically sound and scientifically rigorous research in the interdisciplinary field of imaging, including relevant algorithmic research and hardware and software development, and their applications relevant to medical research. The journal provides a platform to publish original research in structural and functional imaging.

    The journal is also open to imaging studies of the human body and on animals that describe novel diagnostic imaging and analyses methods. Technical, theoretical, and clinical research in both normal and clinical populations is encouraged. Submissions describing methods, software, databases, replication studies as well as negative results are also considered.

    The scope of the journal includes, but is not limited to, the following in the context of biomedical research:

    Imaging and neuro-imaging modalities: structural MRI, functional MRI, PET, SPECT, CT, ultrasound, EEG, MEG, NIRS etc.;
    Neuromodulation and brain stimulation techniques such as TMS and tDCS;
    Software and hardware for imaging, especially related to human and animal health;
    Image segmentation in normal and clinical populations;
    Pattern analysis and classification using machine learning techniques;
    Computational modeling and analysis;
    Brain connectivity and connectomics;
    Systems-level characterization of brain function;
    Neural networks and neurorobotics;
    Computer vision, based on human/animal physiology;
    Brain-computer interface (BCI) technology;
    Big data, databasing and data mining.

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