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MRI-CT融合示例

于 2020-05-11 发布

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下载积分: 1 下载次数: 2

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代码说明：

说明：这是MRI-CT融合示例code，编程语言为matlab。内含图像，注释清晰，代码完整，下载解压后可以直接运行。(This is an example code of MRI-CT fusion, and the programming language is matlab. The image is included, the annotation is clear, and the code is complete. After downloading and decompressing, it can run directly.)

文件列表：

MRI-CT融合示例, 0 , 2018-11-03
MRI-CT融合示例\CC.m, 273 , 2013-09-27
MRI-CT融合示例\MI.m, 1256 , 2011-12-29
MRI-CT融合示例\PCAfusion.m, 367 , 2013-09-28
MRI-CT融合示例\README.txt, 97 , 2013-10-23
MRI-CT融合示例\ct.jpg, 5267 , 2013-09-06
MRI-CT融合示例\ctmrifusion_gaijin.m, 754 , 2018-07-19
MRI-CT融合示例\dipinchuli.m, 918 , 2018-07-19
MRI-CT融合示例\energy.m, 126 , 2013-09-30
MRI-CT融合示例\energyfusion.m, 772 , 2013-09-30
MRI-CT融合示例\entropy.m, 600 , 2013-09-29
MRI-CT融合示例\gradient_variance.m, 412 , 2013-09-30
MRI-CT融合示例\gradient_variancefusion.m, 471 , 2013-09-30
MRI-CT融合示例\gradientenergy.m, 157 , 2013-09-30
MRI-CT融合示例\gradientenergyfusion.m, 510 , 2013-09-30
MRI-CT融合示例\metrics.m, 366 , 2013-09-29
MRI-CT融合示例\mri.jpg, 6731 , 2013-09-06
MRI-CT融合示例\shili.m, 1235 , 2013-10-10

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KMEANS(matlab)
说明： Matlab环境下的k-means聚类算法，实现图像分割，很快阿！(K-means Clustering arithmetic based on Matlab platform.It s fast for Image-Division!)

2005-09-29 18:19:51下载

积分：1
基于OPENCV的SIFT特征提取与匹配算法 OPENCV_SIFT_VC6
基于OPENCV的SIFT特征提取与匹配算法。包含完整的从图像高斯金字塔、DOG、空间极值点提取、关键点描述、KDtree匹配等关键步骤的全部函数实现，对全面深入理解Lowe的SIFT算法有莫大帮助。程序运行前须安装（1）OpenCV: http://opencvlibrary.sourceforge.net （2）SIFT: http://web.engr.oregonstate.edu/~hess/index.html，并配置其环境参数。(OPENCV the SIFT-based feature extraction and matching algorithm. Contains a complete Gaussian pyramid from the image, DOG, space extremum point extraction, description of key points, KDtree matching key step in the realization of the full function of the comprehensive and in-depth understanding of Lowe s SIFT algorithm of tremendous help. Program to run before the installation of (1) OpenCV: http://opencvlibrary.sourceforge.net (2) SIFT: http://web.engr.oregonstate.edu/ ~ hess/index.html, and configure the parameters of their environment.)

2020-06-26 03:00:02下载

积分：1
JPEG-Enr
基于matlab的JPEG编解码程序。里面有2个程序，一个是程序是编解码过程，一个纯编码过程。含解释。(Program based on Matlab JPEG codec. There are two programs, one program is the process of encoding and decoding, a pure coding process. Containing explained.)

2012-03-27 09:40:04下载

积分：1
phasecorrelation
运用相位相关法对图像进行匹配，并通过图形形象地显示相关系数位置。对图像的亮度变换不敏感，相关峰尖突出，有较高的配准精度。(fft、ifft、phase correlation)

2010-08-27 14:29:33下载

积分：1
regiongrow2
区域生长，基本处理方法是以一组种子点开始来行程生长区域，即将哪些预定义属性类似于种子的邻域像素附加到每个种子上 (regional growth, the basic approach is based on a group of seed starting point to the growth of regional tour, What about predefined attributes similar to seed the neighborhood of each pixel additional seeds)

2006-12-21 20:53:55下载

积分：1
recognize_face
利用灰度积分投影直接对人脸图像进行检测和眼睛定位是一种常用的算法,但是直接采用该算法会受到背景、特征等因素的影响,识别准确率较低。提出了一种基于最大类间方差阈值和区域膨胀相结合的检测与定位算法。该算法首先计算最大类间方差设置阈值,把灰度图像转换为二值图像并检测出人脸区域,然后通过对该人脸区域中的连通区域进行膨胀及连通性处理,精确定位眼睛坐标。实验表明,此算法可靠,具有较好的识别效果。(face recognized)

2010-08-19 16:45:54下载

积分：1
Desktop
图像的腐蚀函数，非常有用，欢迎大家下载，一块进步(Corrosion function of the image, useful, and welcome to download, a progress)

2012-09-17 20:02:47下载

积分：1
vendor
说明： Invensense公司的modm实例代码example。初始化以及IIC的引用示例。(The example of modm from Invensense. IIC initiation and configuration initiation.)

2019-03-13 14:09:03下载

积分：1
mcmcstuff
本源码是基于Markov chain Monte Carlo (MCMC)的Bayesian inference工具包,其中包括MCMC采样，基于MCMC的高斯分类，同时描述了采样的一些方法。其中还有使用文档(toolbox is a collection of Matlab functions for Bayesian inference with Markov chain Monte Carlo (MCMC) methods)

2009-03-02 17:54:09下载

积分：1
Image-Fusion
泊松融合在某种意义上解决了图像融合的问题，但其在融合的过程中仅仅考虑了融入图像的梯度，而没有利用背景图像的梯度，因此，在使用泊松融合的过程中，需要对融入区域的标记较为准确，否则，会造成背景纹理的丢失，视觉上可以明显觉察图像融入的痕迹。因此，对公式稍作修改，在考虑前景的同时考虑背景的变化，可以得到更优的结果。(Poisson convergence in a sense solved the problem of image fusion, but it only considers the integration of image gradient in the integration process, but not the use of a background image gradient, therefore, the use of the Poisson integration process, the need for more accurate marker into the area, otherwise, it will result in the loss of background texture, image integration can clearly perceive the visual traces. Therefore, the formula slightly modified, in considering the prospect of taking into account the changes in the background, you can get better results.)

2015-04-21 12:11:50下载

积分：1

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