搜索资源列表
hough.rar
- 霍夫变换，基于视网膜图片的霍夫变换，C++Builder环境下运行,Hough transform, Hough transform-based retinal image, C++ Builder environment running
Registration
- 主要是对视网膜图像进行血管分割，效果还不错-Primarily on retinal vascular image segmentation, the effect was not bad
zengqiang
- 图像增强，基于视网膜图片的图像增强，C++Builder环境下运行-Image enhancement, image enhancement based on the retinal image, C++ Builder environment running
library_management_system1
- retinal image There are several modes of examination, e.g. fluorescein angiography, ICG angiography, infra-red imaging
fundus-image-segemention
- 一种基于灰度的区域灰度分割算法，主要用于视网膜血管分割-Segmentation algorithm based on gray-scale regional gray, mainly used for retinal vessel segmentation
fenshuiling
- 这是医学图像处理中分水岭算法，利用图像形态学的基于区域的分割技术，本人已经成功对视网膜眼底图像进行分割，希望学习医学图像处理的同学可以得到有用的东西-This is watershed algorithm in medical image processing, the use of image morphology based on region segmentation technology, I have successfully in retinal fundus image segme
code
- 配准的一个新的方法——使用分叉结构的视网膜图像配准 -Retinal Image Registration Using bifurcation structures
VesselTest
- 视网膜图像中血管的提取和检测，高斯滤波器模板匹配法提取血管，然后进行血管剔除-Retinal image of blood vessels in the extraction and detection, gaussian filter template matching method to extract the blood vessels, and blood vessels
simple-hybrid
- 图像预处理。首先提取视网膜图像的绿色通道图像，然后进行对比度限制直方图均衡化。-Image preprocessing. Extraction of retinal image of the green channel image first, and then carries on the contrast limited histogram equalization.
iamgepreprocesing
- 视网膜图像的预处理，包括二值图像的获取，RGB转换到HSI模型。-Retinal image preprocessing, including binary image acquisition, RGB to HSI model.
Hessian
- 基于海森矩阵的视网膜图像血管增强，用到特征值-Retinal vascular image enhancement based on hazen matrix, use characteristic value
Gabor_GLM_FEX
- 视网膜血管检测的Gabor变换和机器学习，教程 本教程将演示如何Gabor变换和广义 的线性模型（GLM）可用于视网膜血管检测 图像。 ，我们将尝试检测视网膜血管从 的训练图像，首先，Gabor滤波器与图像卷积。 GLM将使用Gabor变换的图像特征确定 （独立变量）和容器的位置 为结果（因变量）。- Retinal Vessel Detection by Gabor Transform and Machine Learning, a Tutorial T