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The authors describe almost entirely automated procedures for estimation of global, voxel, and cluster-level statistics to test the null hypothesis of zero neuroanatomical difference between two groups of structural magnetic resonance imaging (MRI) data. Theoretical distributions under the null hypothesis are available for (1) global tissue class volumes; (2) standardized linear model [analysis of...

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In the technique known as gridding, the data samples are weighted for sampling density and convolved with a finite kernel, then resampled on a grid preparatory to a fast Fourier transform. The authors compare the artifact introduced into the image for various convolving functions of different sizes, including the Kaiser-Bessel window and the zero-order prolate spheroidal wave function (PSWF). They...

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Guidance systems designed for neurosurgery, hip surgery, and spine surgery, and for approaches to other anatomy that is relatively rigid can use rigid-body transformations to accomplish image registration. These systems often rely on point-based registration to determine the transformation, and many such systems use attached fiducial markers to establish accurate fiducial points for the registrati...

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One of the major drawbacks of magnetic resonance imaging (MRI) has been the lack of a standard and quantifiable interpretation of image intensities. Unlike in other modalities, such as X-ray computerized tomography, MR images taken for the same patient on the same scanner at different times may appear different from each other due to a variety of scanner-dependent variations and, therefore, the ab...

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Based on the theory of approximation, this paper presents a unified analysis of interpolation and resampling techniques. An important issue is the choice of adequate basis functions. The authors show that, contrary to the common belief, those that perform best are not interpolating. By opposition to traditional interpolation, the authors call their use generalized interpolation; they involve a pre...

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This paper presents two new rebinning algorithms for the reconstruction of three-dimensional (3-D) positron emission tomography (PET) data. A rebinning algorithm is one that first sorts the 3-D data into an ordinary two-dimensional (2-D) data set containing one sinogram for each transaxial slice to be reconstructed; the 3-D image is then recovered by applying to each slice a 2-D reconstruction met...

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An algorithm is presented for the fuzzy segmentation of two-dimensional (2-D) and three-dimensional (3-D) multispectral magnetic resonance (MR) images that have been corrupted by intensity inhomogeneities, also known as shading artifacts. The algorithm is an extension of the 2-D adaptive fuzzy C-means algorithm (2-D AFCM) presented in previous work by the authors. This algorithm models the intensi...

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A comparison of six similarity measures for use in intensity-based two-dimensional-three-dimensional (2-D-3-D) image registration is presented. The accuracy of the similarity measures are compared to a "gold-standard" registration which has been accurately calculated using fiducial markers. The similarity measures are used to register a computed tomography (CT) scan of a spine phantom to a fluoros...

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The solution of impedance distribution in electrical impedance tomography is a nonlinear inverse problem that requires the use of a regularization method. The generalized Tikhonov regularization methods have been popular in the solution of many inverse problems. The regularization matrices that are usually used with the Tikhonov method are more or less ad hoc and the implicit prior assumptions are...

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When one integrates a function of two variables x,y - a point function f(P) in the plane - subject to suitable regularity conditions along an arbitrary straight line g then one obtains in the integral values F(g), a line function. In Part A of the present paper the problem which is solved is the inversion of this linear functional transformation, that is the following questions are answered: can e...

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A new method is proposed to subtract the count of scattered photons from that acquired with a photopeak window at each pixel in each planar image of single-photon emission computed tomography (SPECT). The subtraction is carried out using two sets of data: one set is acquired with a main window centered at photopeak energy and the other is acquired with two subwindows on both sides of the main wind...

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Describes an extrinsic-point-based, interactive image-guided neurosurgical system designed at Vanderbilt University, Nashville, TN, as part of a collaborative effort among the Departments of Neurological Surgery, Computer Science, and Biomedical Engineering. Multimodal image-to-image (II) and image-to-physical (IP) registration is accomplished using implantable markers. Physical space tracking is ...

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Infrared thermal imaging of the skin has been used for several decades to monitor the temperature distribution of human skin. Abnormalities such as malignancies, inflammation, and infection cause localized increases in temperature which show as hot spots or as asymmetrical patterns in an infrared thermogram. Even though it is nonspecific, infrared thermology is a powerful detector of problems that...

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An improved echo planar high-speed imaging technique using spiral scan is presented and experimental advantages are discussed. This proposed spiral-scan echo planar imaging (SEPI) technique employs two linearly increasing sinusoidal gradient fields, which results in a spiral trajectory in the spatial frequency domain (k-domain) that covers the entire frequency domain uniformly. The advantages of t...

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Presents a new approach to the correction of intensity inhomogeneities in magnetic resonance imaging (MRI) that significantly improves intensity-based tissue segmentation. The distortion of the image brightness values by a low-frequency bias field impedes visual inspection and segmentation. The new correction method called parametric bias field correction (PABIC) is based on a simplified model of ...

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The maximum likelihood (ML) expectation maximization (EM) approach in emission tomography has been very popular in medical imaging for several years. In spite of this, no satisfactory convergent modifications have been proposed for the regularized approach. Here, a modification of the EM algorithm is presented. The new method is a natural extension of the EM for maximizing likelihood with concave ...

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This paper presents an algorithm for segmenting and measuring retinal vessels, by growing a “Ribbon of Twins” active contour model, which uses two pairs of contours to capture each vessel edge, while maintaining width consistency. The algorithm is initialized using a generalized morphological order filter to identify approximate vessels centerlines. Once the vessel segments are identified the netw...

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The magnetic particle imaging (MPI) imaging process is a new method of medical imaging with great promise. In this paper we derive the 1-D MPI signal, resolution, bandwidth requirements, signal-to-noise ratio (SNR), specific absorption rate, and slew rate limitations. We conclude with experimental data measuring the point spread function for commercially available SPIO nanoparticles and a demonstr...

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We give criteria for the distinguishability of two different conductivity distributions inside a body by electric current computed tomography (ECCT) systems with a specified precision. It is shown in a special case how these criteria can be used to determine the measurement precision needed to distinguish between two different conductivity distributions. It is also shown how to select the patterns...

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We present here a new method to identify the position of the optic disc (OD) in retinal fundus images. The method is based on the preliminary detection of the main retinal vessels. All retinal vessels originate from the OD and their path follows a similar directional pattern (parabolic course) in all images. To describe the general direction of retinal vessels at any given position in the image, a...

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Presents diffeomorphic transformations of three-dimensional (3-D) anatomical image data of the macaque occipital lobe and whole brain cryosection imagery and of deep brain structures in human brains as imaged via magnetic resonance imagery. These transformations are generated in a hierarchical manner, accommodating both global and local anatomical detail. The initial low-dimensional registration i...

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The problem of parameter estimation from Rician distributed data (e.g., magnitude magnetic resonance images) is addressed. The properties of conventional estimation methods are discussed and compared to maximum-likelihood (ML) estimation which is known to yield optimal results asymptotically. In contrast to previously proposed methods, ML estimation is demonstrated to be unbiased for high signal-t...

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This paper presents a new technique for the automatic model-based segmentation of three-dimensional (3-D) objects from volumetric image data. The development closely follows the seminal work of Taylor and Cootes on active shape models, but is based on a hierarchical parametric object description rather than a point distribution model. The segmentation system includes both the building of statistic...

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It is often desired to calculate line integrals through a field of reconstructed CT density pixels for the purpose of improving CT image quality. Two algorithms widely published and discussed in the past are known to either degrade spatial resolution or generate errors in the results due to the discontinuous "square pixel" modeling of the reconstructed image. An algorithm is described, based on li...

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