实验一DICOM图像的读取和显示DICOM（Digital Imaging and Communications in Medicine）即医学数字成像和通信，是医学图像和相关信息的国际标准。
它定义了质量能满足临床需要的可用于数据交换的医学图像格式，利用不同的灰度值实现成像。
DICOM被广泛应用于放射医疗，心血管成像以及放射诊疗诊断设备（X射线，CT，核磁共振，超声等），并且在眼科和牙科等其它医学领域得到越来越深入广泛的应用。
当前大约有百亿级符合DICOM标准的医学图像用于临床使用。
I = dicomread('CT-MONO2-16-ankle.dcm');info = dicominfo('CT-MONO2-16-ankle.dcm');I = dicomread(info);imshow(I,'DisplayRange',[]);dicomwrite(I,'ankle.dcm');info = dicominfo('CT-MONO2-16-ankle.dcm');I = dicomread(info);dicomwrite(I,'ankle.dcm',info);（2）图像读取程序如下：I = dicomread('CT-MONO2-16-ankle.dcm');imtool(I,'DisplayRange',[])info = dicominfo('CT-MONO2-16-ankle.dcm');info.SeriesInstanceUIDmax(I(:))min(I(:))Imodified = I;Imodified(Imodified == 4080) = 32;imshow(Imodified,[])2040608010012020406080100120204060801001202040608010012020406080100120204060801001202040608010012020406080100120实验二 MRI 图像显示和读取MRI 可获得人体横面、冠状面、矢状面及任何方向断面的图像，实现三维定位图像。
完整程序如下：load mri ; D = squeeze(D); figure('Colormap',map) image_num = 8;image(D(:,:,image_num)) axis image ; x = xlim; y = ylimImage num=8Image num=2 Image num=12 Imagenum=18204060801001202-D Contour Slicefigure('Colormap',cm)contourslice(D,[],[],image_num) axis ij xlim(x) ylim(y)daspect([1,1,1])Displaying 3-D Contour Slicesigure('Colormap',cm)contourslice(D,[],[],[1,12,19,27],8); view(3); axis tightApplying an Isosurface to the MRI Datafigure('Colormap',map) Ds = smooth3(D);hiso = patch(isosurface(Ds,5),... FaceColor',[1,.75,.65],... EdgeColor','none'); isonormals(Ds,hiso)hcap = patch(isocaps(D,5),... FaceColor','interp',... EdgeColor','none'); view(35,30) ; axis tight ;20406080100120daspect([1,1,.4]); lightangle(45,30);set(gcf,'Renderer','zbuffer'); lighting phong set(hcap,'AmbientStrength',.6)set(hiso,'SpecularColorReflectance',0,'SpecularExponent',50)程序：figure('Colormap',map)Ds = smooth3(D);hiso = patch(isosurface(Ds,5),... 'FaceColor',[1,.75,.65],... 'EdgeColor','none');isonormals(Ds,hiso)实验三平行束投影仿真实验原理:sheep-logan 模型用来模拟头部断层图像，通过得到sheep-logan 头型，得到不同方向上投影数据，利用模拟X 光平行束重建图像。
程序如下：clc; clear all ; close all ; N=256; I=phantom(N); figure;projection data2040608010012014016018050100150200250300350102030405060imshow(I) figure;imshow(I,[0.8 1.0])clc; clear all ; close all ; N=256; I=phantom(N); theta=0:179; P=radon(I,theta); figure; imshow(I);title('original head model'); figure;imagesc(P),colormap(gray),colorbar title('projection data');实验四 利用Radon 函数直接反投影重建图像程序如下：clc;clear all;close all;N=256;I=phantom(N);delta=pi/180;theta=0:1:179;theta_num=length(theta);P=radon(I,theta);[mm,nn]=size(P);e=floor((mm-N-1)/2+1)+1;P=P(e: N+e-1,:);P1=reshape(P,N,theta_num);rec=medfuncBackprojection(theta_num,N,P1,delta);figure;imshow(I,[]);figure;imshow(rec,[]);function rec=medfuncBackprojection(theta_num,N,R1,delta)rec=zeros(N);for m=1:theta_numpm=R1(:,m);Cm=(N/2)*(1-cos((m-1)*delta)-sin((m-1)*delta));for k1=1:Nfor k2=1:NXrm=Cm+(k2-1)*cos((m-1)*delta)+(k1-1)*sin((m-1)*delta);n=floor(Xrm);t=Xrm-floor(Xrm);n=max(1,n);n=min(n,N-1);p=(1-t)*pm(n)+t*pm(n+1);rec(N+1-k1,k2) = rec(N+1-k1,k2)+p;endendend实验五滤波反投影算法重建实验实验原理:目前CT图像重建算法多采用滤波反投影算法.利用滤波反投影算法的基本原理,对R-L,S-L滤波函数分别进行了计算机仿真对比实验.即先对图像进行反投影，再利用滤波函数的卷积累加求和实现图像重建。
实验结果表明利用滤波反投影较好地重建图像,关键是滤波函数的选择.主程序：%filtered backprojection reconstructionclc;clear all;close all;N=256;I=phantom(N);delta=pi/180;theta=0:1:179;theta_num=length(theta);d=1;P=radon(I,theta);[mm,nn]=size(P);e=floor((mm-N-1)/2+1)+1;P=P(e: N+e-1,:);P1=reshape(P,N,theta_num);fh_RL=medfuncRLfilterfunction(N,d);rec= medfuncRLfilteredbackprojrction(theta_num,N,P1,delta,fh_RL);figure;imshow(I,[]);figure;imshow(rec,[]);function fh_RL=medfuncRLfilterfunction(N,d)fh_RL=zeros(1,N)for k1=1:Nfh_RL(k1)=-1/(pi*pi*((k1-N/2-1)*d)^2)if mod(k1-N/2-1,2)==0fh_RL(k1)=0;endendfh_RL(N/2+1)=1/(4*d^2);function rec_RL = medfuncRLfilteredbackprojrction(theta_num,N,R1,delta,fh_RL) rec_RL=zeros(N);for m=1:theta_numpm=R1(:,m);pm_RL=conv(fh_RL,pm,'same');Cm=(N/2)*(1-cos((m-1)*delta)-sin((m-1)*delta));for k1=1:Nfor k2=1:NXrm=Cm+(k2-1)*cos((m-1)*delta)+(k1-1)*sin((m-1)*delta);n=floor(Xrm);t=Xrm-floor(Xrm);n=max(1,n);n=min(n,N-1);m p_RL = (1-t)*pm_RL(n)+t*pm_RL(n+1);rec_RL(N+1-k1,k2)=rec_RL(N+1-k1,k2)+p_RL;endendendendR—L函数滤波反投影图像S—L滤波反投影成像。