目的探索建立三维核医学图像配准和融合进行心肌存活评价的定量分析方法。
Objective To establish a new quantitative analyzing method for myocardial viability evaluation based on the 3-d registration and fusion of the nuclear medicine images.
利用图像配准技术和融合技术，对两个同质传感器拍摄的车辆图像进行配准和融合。
Using the image registration technology and fusion technology, vehicles image collected by two homogeneity sensors are registered and fused;
在第三章中，我们提出了一个三维点云数据片间基于紧支撑r BF的配准和融合算法。
In Chapter 3, we present a novel registration algorithm for 3d point cloud patches based on CSRBF.
医学图像的配准和融合是医学图像处理的一个新的领域，其目的是为医生提供更多的诊断信息。
Medical image registration and merging is a new area in medical image processing the purpose is to provide more diagnostic information to the physicians.
图像融合前均行颅脑mri薄层扫描及常规X刀术前CT定位扫描，然后将CT和MRI图像资料传输至工作站上进行图像配准和融合。
Before the fusion of ct and MRI images MRI scan and ct scan for location of X-knife were performed respectively, then MR and ct image were transferred to workstation for the fusion of images.
结果：使得融合后图像有很强的抗配准偏差能力，并且能极大程度地保留原来解剖性信息图像和功能性图像的信息。
Results: the image fusion was capable to balance registration error and could reserve the anatomical and functional information to a great extent.
各传感器间的空间配准和时间配准是多传感器数据信息有效融合的关键。
Space registration and time registration are keys to fuse multi-sensors data information effectively.
介绍了一种新的基于信息融合的TM影像和GIS矢量数据自动配准方法。
This paper introduce a new method for automatic registration based on amalgamation of information on TM image and gis vector data.
实现了3个激光线结构光传感器的数据配准和数据融合，得到可用于制鞋CAD和制植CAD的脚形和植形数据。
Implement the registration and merging of 3-d range data produced by triple laser stripe sensors. The final data can be used by Shoemaking-CAD.
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.
针对不同视场的多源图像融合技术，本文提出一种仿射变换和线性插值相结合的配准方法；
Zhendui different field of multi-source image fusion, we propose a affine transformation and linear combination of registration methods;
提出了一种全自动、多模态的信息融合解决方案用于配准视频图像和磁跟踪数据。
The paper reports a fully-automated, multiple-modality sensor data registration scheme between video and magnetic tracker data.
提出了一种全自动、多模态的信息融合解决方案用于配准视频图像和磁跟踪数据。
The paper reports a fully-automated, multiple-modality sensor data registration scheme between video and magnetic tracker data.
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