医学图像配准（B样条弹性配准、非刚性二维和三维图像配准与DEMON（流体）算法）（matlab实现，进过测试，可运行）

刚性二维和三维图像配准与DEMON（流体）算法）（matlab实现，进过测试，可运行）"/>

医学图像配准（B样条弹性配准、非刚性二维和三维图像配准与DEMON（流体）算法）（matlab实现，进过测试，可运行）

医学图像配准

链接: 提取码: 5ykr

包含的医学图像配准算法：

1. 一般的刚性变换
2. 非刚性变换：B样条弹性配准
3. 非刚性变换： 多模态非刚性图像配准算法：非刚性二维和三维图像配准与DEMON（流体）算法，扩展模式转换。

以下是B样条弹性配准源代码（matlab实现）：
先解压此文件

后直接修改以下三个文件（每个文件分别是一种模式）中的图片位置即可

% Example using lsqnonlin optimizer and registration error image 
% instead of value.% clean
clear all; close all; clc;% Read two greyscale images of Lena
I1=im2double(imread('test1.png')); 
I2=im2double(imread('test3.png'));% b-spline grid spacing in x and y direction
Spacing=[32 32];% Type of registration error used see registration_error.m
type='d';% Make the Initial b-spline registration grid
[O_trans]=make_init_grid(Spacing,size(I1));% Convert all values tot type double
I1=double(I1); I2=double(I2); O_trans=double(O_trans); % Smooth both images for faster registration
I1s=imfilter(I1,fspecial('gaussian',[20 20],5));
I2s=imfilter(I2,fspecial('gaussian',[20 20],5));% Optimizer parameters
optim=optimset('Display','iter','MaxIter',40);% Reshape O_trans from a matrix to a vector.
sizes=size(O_trans); O_trans=O_trans(:);% Start the b-spline nonrigid registration optimizer
O_trans = lsqnonlin(@(x)bspline_registration_image(x,sizes,Spacing,I1s,I2s,type),O_trans,[],[],optim);% Reshape O_trans from a vector to a matrix
O_trans=reshape(O_trans,sizes);% Transform the input image with the found optimal grid.
Icor=bspline_transform(O_trans,I1,Spacing); % Make a (transformed) grid image
Igrid=make_grid_image(Spacing,size(I1));
Igrid=bspline_transform(O_trans,Igrid,Spacing); % Show the registration results
figure,
subplot(2,2,1), imshow(I1); title('input image 1');
subplot(2,2,2), imshow(I2); title('input image 2');
subplot(2,2,3), imshow(Icor); title('transformed image 1');
subplot(2,2,4), imshow(Igrid); title('grid');

实验结果：