A comparative study on interpolation methods for controlled cardiac. In computed tomography ct or magnetic resonance imaging mri, image reconstruction requires in terpolation to approximate the discrete functions to. Ct image quality a summary image noise image noise, in its most simple definition, is measured as the standard deviation of voxel values in a homogenous typically water phantom. Quantitative evaluation of convolutionbased methods for. Obviously, the quality of the interpolation process has a large influence on the quality of the registration. The results of scaling the original image using cubic bspline. A method of reducing image artifacts in images acquired with fan beam, helical scanning, tomographic imaging systems uses half scans of less than 360 of projection data of an imaged object on each side of the slice plane being imaged. Grandview boulevard, w1180, waukesha, wisconsin 53188 ken d. Department of electrical engineering, 275 fitzpatrick, university of notre dame, notre dame, indiana 465565637. A comparative study on interpolation methods for controlled.
Interpolation and biomedical imaging image processing task specific operation imaging modality tomographic reconstruction. Here, the shapedepth information available in each 2d image in the image stack is manipulated to get a 3d reconstruction, which gives a more accurate 3d view of the organ of interest. In spiral ct, the longitudinal resolution is also determined by the table increment per rotation, and by the interpolation algorithm used. Image interpolation techniques are referred in literature by many terminologies, such as image resizing, image resampling, digital zooming, image magnification or. Introduction computed tomography ct is an advanced imaging technique which provides complete object visualisation in terms of crosssectional details. Sparse sampling with limited projections of views has wide applications in fast scanning 410s such as cardiac ct and neonate ct examination 23. This results in pixels smaller than the actual resolution of the image. The input to the registration software is the images to be registered. Our study aimed to use anthropomorphic phantoms of different sizes to determine the impact of patients vertical offcentering on patient doses and image noise in chest ct. Learn more about linear, spline, interpolate, interpolation, edge, greyscale, image, grid, mesh. Therefore, image interpolation methods have occupied a peculiar position in medical image processing 1. Trilinear interpolation algorithm for reconstruction of 3d.
One of the most fundamental concepts in ct image reconstruction if the centralslice theorem. A threedimensional statistical approach to improved image. Image interpolation in medical area is of high importance as most 3d biomedical volume images are sampled where the distance between consecutive slices significantly greater than the inplane pixel size due to radiation dose or scanning time. This theorem states that the 1d ft of the projection of an object is the same as the values of the 2d ft of the object along a line drawn through the center of the 2d ft plane. Evolution and innovation in ct image reconstruction are often driven by advances in ct system designs, which in turn are driven by clinical demands. Image coregistration is to map a floating image to a fixed or target image by using a mathematical model. The images reconstructed using nonuniform weighting have poor image quality especially when fewer projection angles are used. The effect of patient centering on patient dose and image noise in chest ct touko kaasalainen1,2 kirsi palmu1,3 vappu reijonen1,2. Uniform weighting image reconstruction using fanbeamfdk reconstruction or parallelbeamtfdk reconstruction algorithm requires a uniform b,sory,t grid respectively.
Learn more about digital image processing, down sampling, reconstruction, imaging, image processing, linear interpolation matlab. Image interpolation creates a number of new slices between known slices in order to obtain an isotropic volume image. Pgqquality management slideshare uses cookies to improve functionality and performance, and to provide you with relevant advertising. Nevertheless, all previous methods focused on lowresolution image interpolation, and most of them work poorly on highresolution image. Pivotal to understanding of ct reconstruction relates 2d ft of image to 1d ft of its projection n. Image interpolation and resampling biomedical imaging group.
Pdf volume interpolation of ct images from tree trunks. Image interpolation and display in reply to this post by joachim wesner hi joachim, you are right of course, i have used the word interpolation not in the strict sense, and it is a kind of lowpass filtering that should be done when downscaling. The scan was cropped to a 356x280 image, because a 6x4 inch photo scanned at 100 dpi would give an image size of 600x400 pixels, nearly full screen on a 640x480 pixel screen, and too large and slow for web pages. Here are three sample outputs you only said you want to use spline interpolation, but not which one. We propose a novel network, high resolution interpolation network hrinet, aiming at producing highresolution ct image interpolations. The example of asymmetric roles played by i0 and i1. In this work, a 3d reconstruction technique for mrict 2d image stack, based on shapelets has been proposed.
An interpolationbased data synthesis in the sinogram space is a straightforward example. Pdf image interpolation techniques in digital image. In this paper, image noise variance is derived for typical helical ct linear interpolation techniques, including the full scan fs, under. Image reconstruction with linear interpolation matlab. A threedimensional statistical approach to improved image quality for multislice helical ct jeanbaptiste thibaulta. Image reconstruction from 2d stack of mrict to 3d using. Introduction conebeam cb computed tomography ct was introduced to improve the precision and accuracy of radiotherapy jaffray et al2002. Us5270923a computed tomographic image reconstruction. Metal artifact reduction for practical dental computed. Zero filling interpolation radiology reference article. As a sinogram interpolation to uniformly generate immediate views, systematic interpolation methods are useful to improve image quality in various image systems such as 3d imaging, deinterlacing, and so on. Interpolation technique, quickscan tomography, firstgeneration ct system, ct images, tomographic image, computed tomography, imaging techniques, image processing, image visualisation 1.
Introduction after the advent of practical use of ray ct xray x computed tomography 30 years ago, furtherimprovement in the ability to check and examine precision has been achieved compared with the xray film which is merelyan. Helical ct image noiseanalytical results wang 1993. Keywords a digital image interpolation method that is performed in the image interpolation, image fusion, and curvelet transform. Several interpolation strategies have been proposed, including radial basis functions and thinplate splines johnson and christensen 2002, zagorchev and. Strategy of computed tomography sinogram inpainting based on. Leastsquares interpolation of fused mr and ct images in. Interpolation plus deep learning mar was further evaluated by human evaluations. Introduction computed tomography ct is an advanced imaging technique which provides complete object. The reconstructed image, using the interpolated data, shows enhanced image visualisation in ct images through reduction in reconstruction artifact and non. In conventional ct, the longitudinal spatial resolution is entirely determined by the slice thickness. To make the benefits and overhead of our new algorithm clear, we conduct throughout evaluations of our technique using a threedimensional 3d computed tomography ct workload 1 with two interpolation algorithms. An image fx,y tells us the intensity values at the integral lattice locations, i. Interpolation technique in computed tomography image. Ct, small lesions fall out of plane for each continuous slice yimproved contrast.
Feb 25, 2011 2d interpolation linear and spline of a. Thanh et al trilinear interpolation algorithm for reconstruction of 3d mri brain image where mx,y and sxi,yj are the input and output images and hi,j is a kernel with the size of 2x2 as shown in figure 7. They are required for image generation as well as in image postprocessing. Resolution and interpolation how scanners work howstuffworks. This theorem states that the 1d ft of the projection. For observation at different angles of the 3d brain image, the trilinear interpolation method was utilized to construct the 3d brain image from the enhanced 2d mri images. Us5270923a computed tomographic image reconstruction method. A deinterlacing method is a technique to convert an interlaced video sequence in a linebyline fashion. The scanners dpi is determined by the number of sensors in a single row xdirection sampling rate of the ccd or cis array by. Image interpolation in 4d ct using a bspline deformable. Bilinear applying linear spline interpolation in both x and y direction. This follows naturally from the interpretation of the sampling process in the frequency domain.
From a historical perspective, for example, the fanbeam axial. Interpolationbased registration solves for deformation at a set of specific locations and interpolates a dense deformation field for the rest of the image domain. In xray computed tomography ct, sparse sampling and detector gaps are two typical cases of sinogram incompleteness 17. This first article covers the fundamental principles of ct, including the basic geometry of the ct scan process, the nature of the measurements made by ct detectors, a qualitative explanation of the image reconstruction process, the evolution of ct technology the 4 generations of ct from the emi firstgeneration scanner through modern slip. Interpolation based registration solves for deformation at a set of specific locations and interpolates a dense deformation field for the rest of the image domain. Deepneuralnetwork based sinogram synthesis for sparseview ct. Alternative supervision network for highresolution ct image interpolation jiawei li1, jae chul koh2, wonsook lee3 1,3school of electrical engineering and computer science, university of ottawa 2department of anesthesiology and pain medicine, the korea university anam hospital abstract image interpolation in medical area is of high importance as most. Image interpolation is a widely used operation in image processing, medical imaging.
Pdf interpolation method in simple computed tomography scanner. Xray ct image, 3d reconstruction, lung, heartbeat, geometric transformation, area oriented interpolation. A single 360degree rotation of the tube is shaded in red. Collimation or slice thickness the width of the xray beam is determined by. Take a 16x16 pixel image and interpolate it to a 160x160 pixel image. Image enhancement for computed tomography using directional. Pdf a method for sinogram data interpolation based on a sinusoidal. There are, of course, much more complete definitions of noise that take into account the contrast scale of the scanner for example, the definition described.
May 21, 2009 computed tomography image reconstruction presented by. A deinterlacing method is a technique to convert an interlaced video sequence in. I created a function to interpolate along image slices. Directional sinogram interpolation for motion weighted 4d. Zero filling interpolation zip is the substitution of zeroes for unmeasured data points in order to increase the matrix size of the new data prior to fourier transformation of mr data. Introduction image fusion is considered as an integration of different source images to produce an image with higher visual quality than the source images. In this work, a 3d reconstruction technique for mri ct 2d image stack, based on shapelets has been proposed. Effect of patient centering on patient dose and image noise. The data model associated to interpolation also affects algorithmic considerations. In each case, he picked the most valuable image from three images for the fbp reconstruction, i.
In addition to the cubicspline interpolation applied in our studies, other advanced algorithms such as directional sinogram interpolation 23, 24 and deeplearningbased interpolation have been recently developed for generating additional projections to minimize streak artifacts in the sparseview ct image reconstruction. Image interpolation is a widely used operation in image processing, medical imaging, and. Video image size of a given original area depends only on resolution not true for printers. However, in patients with lesions in the thoracic and. A momentumbased diffeomorphic demons framework for. Computertomographie, publicis mcd verlag 2000 critics to spiral ct 1989. One of the most fundamental concepts in ct image reconstruction if the. To illustrate the asymmetry problem, we present an example in fig. Quantitative evaluation of convolutionbased methods for medical image interpolation erik h.
Simulation results shows that the 3d brain image which allows to view at different angles may support for doctors in early diagnosing problems inside human brain cortex for. Image interpolation techniques are referred in literature by many terminologies, such as image resizing, image resampling, digital zooming, image magnification or enhancement, etc. Correspondingly, in the time domain the reconstruc. Several interpolation strategies have been proposed, including radial basis functions and thinplate splines. Most flatbed scanners have a true hardware resolution of at least 300x300 dots per inch dpi.