International Journal of Imaging Systems and Technology
About: International Journal of Imaging Systems and Technology is an academic journal published by Wiley-Blackwell. The journal publishes majorly in the area(s): Computer science & Artificial intelligence. It has an ISSN identifier of 0899-9457. Over the lifetime, 1655 publications have been published receiving 25224 citations. The journal is also known as: Imaging systems and technology.
Topics: Computer science, Artificial intelligence, Segmentation, Convolutional neural network, Pattern recognition (psychology)
Papers published on a yearly basis
TL;DR: This methodology is shown to provide superior delineations of a number of known white matter tracts, in a manner robust to crossing fiber effects, and has been compiled into a software package, called MRtrix, which has been made freely available for use by the scientific community.
Abstract: In recent years, diffusion-weighted magnetic resonance imaging has attracted considerable attention due to its unique potential to delineate the white matter pathways of the brain. However, methodologies currently available and in common use among neuroscientists and clinicians are typically based on the diffusion tensor model, which has comprehensively been shown to be inadequate to characterize diffusion in brain white matter. This is due to the fact that it is only capable of resolving a single fiber orientation per voxel, causing incorrect fiber orientations, and hence pathways, to be estimated through these voxels. Given that the proportion of affected voxels has been recently estimated at 90%, this is a serious limitation. Furthermore, most implementations use simple “deterministic” streamlines tracking algorithms, which have now been superseded by “probabilistic” approaches. In this study, we present a robust set of tools to perform tractography, using fiber orientations estimated using the validated constrained spherical deconvolution method, coupled with a probabilistic streamlines tracking algorithm. This methodology is shown to provide superior delineations of a number of known white matter tracts, in a manner robust to crossing fiber effects. These tools have been compiled into a software package, called MRtrix, which has been made freely available for use by the scientific community. © 2012 Wiley Periodicals, Inc. Int J Imaging Syst Technol, 22, 53–66, 2012 © 2012 Wiley Periodicals, Inc.
TL;DR: A detailed study of several very important aspects of Super‐Resolution, often ignored in the literature, are presented, and robustness, treatment of color, and dynamic operation modes are discussed.
Abstract: Super-Resolution reconstruction produces one or a set of high-resolution images from a sequence of low-resolution frames. This article reviews a variety of Super-Resolution methods proposed in the last 20 years, and provides some insight into, and a summary of, our recent contributions to the general Super-Resolution problem. In the process, a detailed study of several very important aspects of Super-Resolution, often ignored in the literature, is presented. Spe- cifically, we discuss robustness, treatment of color, and dynamic operation modes. Novel methods for addressing these issues are accompanied by experimental results on simulated and real data. Finally, some future challenges in Super-Resolution are outlined and discussed. © 2004 Wiley Periodicals, Inc. Int J Imaging Syst Technol, 14, 47-57, 2004; Published online in Wiley InterScience (www.interscience.wiley. com). DOI 10.1002/ima.20007
TL;DR: An algorithm is explained that is used to make images from electrical impedance data measured on the boundary of a circle in two dimensions, based on the method of least squares, which does not reproduce the conductivity accurately, but yields useful images.
Abstract: The inverse conductivity problem is the mathematical problem that must be solved in order for electrical impedance tomography systems to be able to make images. Here we show how this inverse conductivity problem is related to a number of other inverse problem. We then explain the workings of an algorithm that we have used to make images from electrical impedance data measured on the boundary of a circle in two dimensions. This algorithm is based on the method of least squares. It takes one step of a Newton's method, using a constant conductivity as an initial guess. Most of the calculations can therefore be done analytically. The resulting code is named NOSER, for Newton's One-Step Error Reconstructor. It provides a reconstruction with 496 degrees of freedom. The code does not reproduce the conductivity accurately (unless it differs very little from a constant), but it yields useful images. This is illustrated by images reconstructed from numerical and experimental data, including data from a human chest.
TL;DR: The results show that in both high and low frequency cases, good reconstructed profiles and smoothed versions of the original profiles can be obtained for smoothly varying permittivity profiles ( lossless) and discontinuous profiles (lossless), respectively.
Abstract: A new method, based on an iterative procedure, for solving the two-dimensional inverse scattering problem is presented. This method employs an equivalent Neumann series solution in each iteration step. The purpose of the algorithm is to provide a general method to solve the two-dimensional imaging problem when the Born and the Rytov approximations break down. Numerical simulations were calculated for several cases where the conditions for the first order Born approximation were not satisfied. The results show that in both high and low frequency cases, good reconstructed profiles and smoothed versions of the original profiles can be obtained for smoothly varying permittivity profiles (lossless) and discontinuous profiles (lossless), respectively. A limited number of measurements around the object at a single frequency with four to eight plane incident waves from different directions are used. The method proposed in this article could easily be applied to the three-dimensional inverse scattering problem, if computational resources are available.
TL;DR: The matrix transform approach called dynamic analysis (DA), which enables on‐line real‐time imaging of major and trace elements using proton‐induced X‐ray emission (PIXE), and provides off‐line iterative yield corrections to these images to compensate for changing sample composition across an image area.
Abstract: The X-ray spectra of pure elements, excited using MeV energy beam of protons from the nuclear microprobe, have known spectra signatures. This makes X-ray spectra for more complex mixtures amenable to decomposition into contributions from the component elements. By devising this procedure as a matrix operation that transforms directly from spectrum vector to elemental concentration vector, the decomposition can be performed very efficiently enabling the real-time projection of the component element signals. In the case of a raster-scanned beam, with data that contain position information for each X-ray event, this approach enables the real-time projection of component element spatial distribution images. This paper describes the matrix transform approach called dynamic analysis (DA), which enables on-line real-time imaging of major and trace elements using proton-induced X-ray emission (PIXE). The method also provides off-line iterative yield corrections to these images to compensate for changing sample composition across an image area. The resulting images are quantitative in two respects: (1) they resolve the pure element components and strongly reject interferences from other elements and (2) they can be directly interrogated for sample composition at each pixel, over areas, or along lines across the image area, with accuracy comparable to microanalytical point analysis methods. The paper describes the DA method, presents tests, and discusses its application to quantitative major and trace element imaging in geology. © 2001 John Wiley & Sons, Inc. Int J Imaging Syst Technol 11, 219–230, 2000