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Registration of Multimodal Medical Images

机译:多模态医学图像配准

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摘要

Medical images are increasingly being used within healthcare for diagnosis, planning treatment, guiding treatment and monitoring disease progression. Within medical research (e.g. neu-roscience research) they are used to investigate disease processes and understand normal development and ageing. Technically, medical imaging mainly processes missing, ambiguous, complementary, redundant and distorted data. In this paper, we propose a set of MR-CT image registration methods by using spatial models like rigid, affne and projective transformations. The registered and fused image contains the properties and details of both MR and CT images and can efficiently be used in clinical medicine.
机译:医学图像在医疗保健中越来越多地用于诊断,计划治疗,指导治疗和监测疾病进展。在医学研究(例如神经科学研究)中,它们被用来调查疾病过程并了解正常的发育和衰老。从技术上讲,医学成像主要处理丢失,模棱两可,互补,冗余和失真的数据。在本文中,我们通过使用刚性,仿射和投影变换等空间模型,提出了一套MR-CT图像配准方法。配准和融合的图像包含MR和CT图像的属性和细节,可以有效地用于临床医学。

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