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Nonrigid Registration of Medical Images: Theory, Methods, and Applications [Applications Corner]

机译:医学图像的非刚性配准:理论,方法和应用[应用专区]

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摘要

Medical image registration [1] plays an increasingly important role in many clinical applications, including the detection and diagnosis of diseases, planning of therapy, guidance of interventions, and the follow-up and monitoring of patients. The primary goal of image registration is to find corresponding anatomical or functional locations in two or more images. This has many applications: registration can be applied to images from the same subject acquired by different imaging modalities (multimodal image registration) or at different time points (serial image registration). Both cases are examples of intrasubject registration since the images are acquired from the same subject. Another application area for image registration is intersubject registration, where the aim is to align images acquired from different subjects, e.g., to study the anatomical variability within or across populations.
机译:医学图像配准[1]在许多临床应用中扮演着越来越重要的角色,包括疾病的检测和诊断,治疗计划,干预指导以及患者的随访和监测。图像配准的主要目标是在两个或更多图像中找到相应的解剖或功能位置。这具有许多应用:配准可以应用于通过不同的成像模式(多模态图像配准)或在不同的时间点(串行图像配准)从同一对象获取的图像。两种情况都是对象内配准的示例,因为图像是从同一对象获取的。图像配准的另一个应用领域是对象间配准,其目的是对齐从不同对象获取的图像,例如,研究人群内部或人群之间的解剖变异性。

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  • 来源
    《Signal Processing Magazine, IEEE》 |2010年第4期|共7页
  • 作者

    Rueckert D.; Aljabar P.;

  • 作者单位

    A professor of visual information processing in the Department of Computing, Imperial College London.;

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  • 正文语种 eng
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