image-registration

问题 I got two point clouds and try to scale them to the same size. My first approach was to just divide the square roots from the eigenvalues: pcl::PCA<pcl::PointNormal> pca; pca.setInputCloud(model_cloud_ptr); Eigen::Vector3f ev_M = pca.getEigenValues(); pca.setInputCloud(segmented_cloud_ptr); Eigen::Vector3f ev_S = pca.getEigenValues(); double s = sqrt(ev_M[0])/sqrt(ev_S[0]); This helps me to scale my model cloud to have approximately the same size as my segmented cloud. But the result is

问题 What are the steps in feature-based registration? If I have a transformed image matching to a stack of images (of which only one is the best match), what are the steps in registration? Once I find matches and use them to estimate a transform, what's usually the next step? 回答1: Find points/areas which are invariant to different kind of transformations like: translation, rotation, scale.. because this points are invariant to those transformation we can find them in the different images that we

问题 I have two MR acquisitions where the first one is a 3D acquisition (1x1x1 mm3) and the second is a 2D acquisition (2.24 x 2.24 x 5.00 mm, axial slices). The high resolution dataset is a full head 3D acquisition that gives 176 slices if resliced in the axial direction (orientation was initially saggital in the acquisition). The 2D acquisition only contains 3 axial slices that were selected to target specific regions in the brain and were acquired continuously. Is it possible to know, which

问题 I am using Matlab to transform an image to target image. I have geometric transformation(tform). for example this is my 'tform': 1.0235 0.0022 -0.0607 0 -0.0276 1.0002 0.0089 0 -0.0170 -0.0141 1.1685 0 12.8777 5.0311 -70.0325 1.0000 In Matlab2013, it is possible to do it easily using imwarp: %nii = 3D MR Image I = nii.img; dii=nii.hdr.dime.pixdim(2:4); Rfixed=imref3d(size(I),dii(2),dii(1),dii(3)); new_img= imwarp(old_img, Rfixed, tform, 'OutputView', Rfixed); the result is perfect using

问题 I have some doubts regarding 3D image registration and segmentation: Load dicom images: In DCE-MRI there are 4000 slices and total 100 stacks, so 40 in each stack. How can I load them to a 4D array using GDCM simpleITK function Registration: registration is pretty straight forward, we have to register all 100 stacks to the first stack. Registration accuracy : SimpleITK overlap ratio measure or hausdroff distance need segmentation and labelling. Now segmentation using region growing or

问题 I am working on image registration between infrared (LWIR) and visual images using FLIR dataset. RGB LWIR Scaling was a global transformation problem, which I resolved lucky. However, the translation varies with different image pairs (visual and IR) due to different FoV of visual sensors. I have tried area based (intensity) image registration which works well with half of the images only. I have also tried few feature based image registration techniques, but results were worse due to

问题 I am trying to register two volumetric images from brain (PET and CT or even PET and MR). Each of these volumetric images contains different numbers of 2D images (slices). For example, CT has 150 slices and PET has 100 slices. I was thinking of using an interpolation method to calculate and reduce the number of CT slices to 100. Is this a correct approach? Does anyone know of any resources that could be helpful for me? like a pseudo code, or steps that I should go through for registering two

问题 I have a paper document that will be scanned, and then I'll want to perform image registration (image alignment) on different scans of different copies of the document. I've noticed that paper forms often have a "registration mark" printed in the four corners of the piece of the paper (a cross-hairs: a circle with a plus intersecting in it). It looks something like this: In my case, I have the freedom to choose the exact shape of the registration mark, to make it as easy as possible for the

问题 I am trying to register two brain image volumes (each includes 2D slices). The first volume (target or moving volume) has the slice thickness and spacing of 1.5 and [1.5 1.5] respectively. For the second one (reference volume), these values are 4 and [0.9375 0.9375]. Also the number of slices are different. First volume has 96 slices and second has 44 slices. One of my friends, suggested to make the voxels isotropic, but I do not know how to do that. I can see that first volume is isotropic,

问题 I am using image registration toolbox to register two 3D images. I register the moving image to the fixed image. I use "imregtform" to save tform. tform = imregtform(moving,fixed,transformType,optimizer,metric) for example this is my 'tform': 1.0235 0.0022 -0.0607 0 -0.0276 1.0002 0.0089 0 -0.0170 -0.0141 1.1685 0 12.8777 5.0311 -70.0325 1.0000 then I use 'Imwarp' to transfer moving image to the fixed image. In my code it is, nii=load_untouch_nii(['mypath image.nii' ]); I = nii.img; dii=nii