本文主要内容是关于多模态医学图像融合的研究和实现。
This paper aims at pilot study on multimodality medical image fusion.
提出了一种用于多模态医学图像处理的特定区域轮廓提取算法。
This paper approves a novel contour extraction algorithm of special region to resolve the problems in multi - mode medical image registration.
多模态医学图像的配准在医学诊断和治疗计划中起着重要的作用。
Multimodality medical image registration has important applications in clinical diagnosis and therapy planning.
方法提出一种基于自由变形模型的多模态医学图像的非刚性配准的方法。
Method A non-rigid registration method of multimodal medical images based on Free Form Deformation(FFD) was proposed.
多模态医学图像融合在医学图像的分析和诊断上具有极为重要的应用价值。
Multi-modality medical image fusion plays an important role in medical analysis and diagnosis.
为了准确、可靠地配准多模态医学图像，提出了一种基于互信息的全局优化配准算法。
A global optimization method based on mutual information is proposed for multimodality medical image registration.
为了实现多模态医学图像的配准融合，提出一种加快寻优的医学图像互信息配准算法实现CT和MR图像的配准。
A new medical image mutual information registration method, which can speedup the optimized process is proposed for CT and MR medical image auto rigid registration.
医学成像新技术、多模态医学成像的图像与信息融合、大数据病例的挖掘，是实现临床精准医疗的重要工程基础。
Precision Medicine relies on advent medical imaging technique, fusion of multi-modality medical imaging and information, and large-scale data mining on medical cases.
医学成像新技术、多模态医学成像的图像与信息融合、大数据病例的挖掘，是实现临床精准医疗的重要工程基础。
Precision Medicine relies on advent medical imaging technique, fusion of multi-modality medical imaging and information, and large-scale data mining on medical cases.
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