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Medical Imaging, IEEE Transactions on

Issue 3 • Date Sep 1995

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Displaying Results 1 - 22 of 22
  • Pure phase-encoded MRI and classification of solids

    Publication Year: 1995 , Page(s): 616 - 620
    Cited by:  Papers (1)  |  Patents (2)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (516 KB)  

    Here, the authors combine a pure phase-encoded magnetic resonance imaging (MRI) method with a new tissue-classification technique to make geometric models of a human tooth. They demonstrate the feasibility of three-dimensional imaging of solids using a conventional 11.7-T NMR spectrometer. In solid-state imaging, confounding line-broadening effects are typically eliminated using coherent averaging methods. Instead, the authors circumvent them by detecting the proton signal at a fixed phase-encode time following the radio-frequency excitation. By a judicious choice of the phase-encode time in the MRI protocol, the authors differentiate enamel and dentine sufficiently to successfully apply a new classification algorithm. This tissue-classification algorithm identifies the distribution of different material types, such as enamel and dentine, in volumetric data. In this algorithm, the authors treat a voxel as a volume, not as a single point, and assume that each voxel may contain more than one material. They use the distribution of MR image intensities within each voxel-sized volume to estimate the relative proportion of each material using a probabilistic approach. This combined approach, involving MRI and data classification, is directly applicable to bone imaging and hard-tissue contrast-based modeling of biological solids View full abstract»

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  • A digital filtration technique for scatter-glare correction based on thickness estimation

    Publication Year: 1995 , Page(s): 587 - 595
    Cited by:  Papers (2)  |  Patents (4)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (736 KB)  

    In order to quantitate anatomical and physiological parameters such as vessel dimensions and volumetric blood flow, it is necessary to make corrections for scatter and veiling glare, which are the major sources of nonlinearities in videodensitometric digital subtraction angiography (DSA). A convolution filtering technique has been investigated to estimate scatter-glare distribution in DSA images without the need to sample the scatter-glare intensity for each patient. This technique utilizes exposure parameters and image gray levels to assign equivalent Lucite thickness for every pixel in the image. The thickness information is then used to estimate scatter-glare intensity on a pixel-by-pixel basis. To test its ability to estimate scatter-glare intensity, the correction technique was applied to images of a Lucite step phantom, anthropomorphic chest phantom, head phantom, and animal models at different thicknesses, projections, and beam energies. The root-mean-square (rms) percentage error of these estimates was obtained by comparison with direct scatter-glare measurements made behind a lead strip. The average rms percentage errors in the scatter-glare estimate for the 25 phantom studies and the 17 animal studies were 6.44% and 7.96%, respectively. These results indicate that the scatter-glare intensity can be estimated with adequate accuracy for a wide range of thicknesses, projections, and beam energies using exposure parameters and gray level information View full abstract»

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  • Feature selection in the pattern classification problem of digital chest radiograph segmentation

    Publication Year: 1995 , Page(s): 537 - 547
    Cited by:  Papers (26)  |  Patents (6)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1148 KB)  

    In pattern classification problems, the choice of variables to include in the feature vector is a difficult one. The authors have investigated the use of stepwise discriminant analysis as a feature selection step in the problem of segmenting digital chest radiographs. In this problem, locally calculated features are used to classify pixels into one of several anatomic classes. The feature selection step was used to choose a subset of features which gave performance equivalent to the entire set of candidate features, while utilizing less computational resources. The impact of using the reduced/selected feature set on classifier performance is evaluated for two classifiers: a linear discriminator and a neural network. The results from the reduced/selected feature set were compared to that of the full feature set as well as a randomly selected reduced feature set. The results of the different feature sets were also compared after applying an additional postprocessing step which used a rule-based spatial information heuristic to improve the classification results. This work shows that, in the authors' pattern classification problem, using a feature selection step reduced the number of features used, reduced the processing time requirements, and gave results comparable to the full set of features View full abstract»

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  • The gridding method for image reconstruction by Fourier transformation

    Publication Year: 1995 , Page(s): 596 - 607
    Cited by:  Papers (42)  |  Patents (10)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1100 KB)  

    The authors explore a computational method for reconstructing an n-dimensional signal f from a sampled version of its Fourier transform fˆ. The method involves a window function wˆ and proceeds in three steps. First, the convolution gˆ=wˆ*fˆ is computed numerically on a Cartesian grid, using the available samples of fˆ. Then, g=wf is computed via the inverse discrete Fourier transform, and finally f is obtained as g/w. Due to the smoothing effect of the convolution, evaluating wˆ*fˆ is much less error prone than merely interpolating fˆ. The method was originally devised for image reconstruction in radio astronomy, but is actually applicable to a broad range of reconstructive imaging methods, including magnetic resonance imaging and computed tomography. In particular, it provides a fast and accurate alternative to the filtered backprojection. The basic method has several variants with other applications, such as the equidistant resampling of arbitrarily sampled signals or the fast computation of the Radon (Hough) transform View full abstract»

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  • Semi-automatic tracking of myocardial motion in MR tagged images

    Publication Year: 1995 , Page(s): 422 - 433
    Cited by:  Papers (14)  |  Patents (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1112 KB)  

    Tissue tagging using magnetic resonance (MR) imaging has enabled quantitative noninvasive analysis of motion and deformation in vivo. One method for MR tissue tagging is Spatial Modulation of Magnetization (SPAMM). Manual detection and tracking of tissue tags by visual inspection remains a time-consuming and tedious process. The authors have developed an interactively guided semi-automated method of detecting and tracking tag intersections in cardiac MR images. A template matching approach combined with a novel adaptation of active contour modeling permits rapid analysis of MR images. The authors have validated their technique using MR SPAMM images of a silicone gel phantom with controlled deformations. Average discrepancy between theoretically predicted and semi-automatically selected tag intersections was 0.30 mm±0.17 [mean±SD, NS (P<0.05)]. Cardiac SPAMM images of normal volunteers and diseased patients also have been evaluated using the authors' technique View full abstract»

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  • Wavelet analysis for brain-function imaging

    Publication Year: 1995 , Page(s): 556 - 564
    Cited by:  Papers (3)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (960 KB)  

    The authors present a new algorithmic procedure for the analysis of brain images. This procedure is specifically designed to image the activity and functional organization of the brain. The authors' results are tested on data collected and previously analyzed with the technique known as in vivo optical imaging of intrinsic signals. The authors' procedure enhances the applicability of this technique and facilitates the extension of the underlying ideas to other imaging problems (e.g., functional MRI). The authors' thrust is two fold. First, they give a systematic method to control the blood vessel artifacts which typically reduce the dynamic range of the image. They propose a mathematical model for the vibrations in time of the veins and arteries and they design a new method for cleaning the images of the vessels with the highest time variations. This procedure is based on the analysis of the singularities of the images. The use of wavelet transform is of crucial importance in characterizing the singularities and reconstructing appropriate versions of the original images. The second important component of the authors' work is the analysis of the time evolution of the fine structure of the images. They show that, once the images have been cleaned of the blood vessel vibrations/variations, the principal component of the time evolutions of the signals is due to the functional activity following the stimuli. The part of the brain where this function takes place can be localized and delineated with precision View full abstract»

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  • Electromagnetic considerations for RF current density imaging [MRI technique]

    Publication Year: 1995 , Page(s): 515 - 524
    Cited by:  Papers (8)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (944 KB)  

    Radio frequency current density imaging (RF-CDI) is a recent MRI technique that can image a Larmor frequency current density component parallel to B0. Because the feasibility of the technique was demonstrated only for homogeneous media, the authors' goal here is to clarify the electromagnetic assumptions and field theory to allow imaging RF currents in heterogeneous media. The complete RF field and current density imaging problem is posed. General solutions are given for measuring lab frame magnetic fields from the rotating frame magnetic field measurements. For the general case of elliptically polarized fields, in which current and magnetic field components are not in phase, one can obtain a modified single rotation approximation. Sufficient information exists to image the amplitude and phase of the RF current density parallel to B0 if the partial derivative in the B0 direction of the RF magnetic field (amplitude and phase) parallel to B0 is much smaller than the corresponding current density component. The heterogeneous extension was verified by imaging conduction and displacement currents in a phantom containing saline and pure water compartments. Finally, the issues required to image eddy currents are presented. Eddy currents within a sample will distort both the transmitter coil reference system, and create measurable rotating frame magnetic fields. However, a three-dimensional electro-magnetic analysis will be required to determine how the reference system distortion affects computed eddy current images View full abstract»

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  • A dual mesh scheme for finite element based reconstruction algorithms

    Publication Year: 1995 , Page(s): 504 - 514
    Cited by:  Papers (34)  |  Patents (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (928 KB)  

    The finite element (FE) method has found several applications in emerging imaging modalities, especially microwave imaging which has been shown to be potentially useful in a number of areas including thermal estimation. In monitoring temperature distributions, the biological phenomena of temperature variations of tissue dielectric properties is exploited. By imaging these properties and their changes during such therapies as hyperthermia, temperature distributions can be deduced using difference imaging techniques. The authors focus on a microwave imaging problem where the hybrid element (HE) method is used in conjunction with a dual mesh scheme in an effort to image complex wavenumbers, k2. The dual mesh scheme is introduced to improve the reconstructed images of tissue properties and is ideally suited for systems using FE methods as their computational base. Since the electric fields typically vary rapidly over a given body when irradiated by high-frequency electromagnetic sources, a dense mesh is needed for these fields to be accurately represented. Conversely, k2 may be fairly constant over subregions of the body which would allow for a less dense sampling of this parameter in those regions. In the dual mesh system employed, the first mesh, which is uniformly dense, is used for calculating the electric fields over the body whereas the second mesh, which is nonuniform and less dense, is used for representing the k2 distribution within the region of interest. The authors examine the 2-D TM polarization case for a pair of dielectric distributions on both a large and small problem to demonstrate the flexibility of the dual mesh method along with some of the difficulties associated with larger imaging problems. Results demonstrate the capabilities of the dual mesh concept in comparison to a single mesh approach for a variety of test cases, suggesting that the dual mesh method is critical for FE based image reconstruction where rapidly varying physical quantities are used to recover smoother property profiles, as can occur in microwave imaging of biological bodies View full abstract»

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  • Anatomically constrained electrical impedance tomography for anisotropic bodies via a two-step approach

    Publication Year: 1995 , Page(s): 498 - 503
    Cited by:  Papers (10)  |  Patents (6)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (548 KB)  

    Discusses the inclusion of anatomical constraints and anisotropy in static Electrical Impedance Tomography (EIT) using a two-step approach to EIT. In the first step, the boundaries between regions of different conductivities are anatomically constrained using Magnetic Resonance Imaging (MRI) data. In the second step, the conductivity values in different regions are determined. Anisotropic conductivity regions are included to allow better modeling of the muscle regions (e.g., skeletal muscle) which exhibit a greater conductivity in the direction parallel to the muscle fiber. This two-step approach is used to reconstruct the conductivity profile of a canine torso, illustrating its potential application in extracting conductivity values for bioelectric modeling View full abstract»

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  • Model-based 3-D segmentation of multiple sclerosis lesions in magnetic resonance brain images

    Publication Year: 1995 , Page(s): 442 - 453
    Cited by:  Papers (43)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1444 KB)  

    Human investigators instinctively segment medical images into their anatomical components, drawing upon prior knowledge of anatomy to overcome image artifacts, noise, and lack of tissue contrast. The authors describe: 1) the development and use of a brain tissue probability model for the segmentation of multiple sclerosis (MS) lesions in magnetic resonance (MR) brain images, and 2) an empirical comparison of the performance of statistical and decision tree classifiers, applied to MS lesion segmentation. Based on MR image data obtained from healthy volunteers, the model provides prior probabilities of brain tissue distribution per unit voxel in a standardized 3-D “brain space”. In comparison to purely data-driven segmentation, the use of the model to guide the segmentation of MS lesions reduced the volume of false positive lesions by 50-80% View full abstract»

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  • A new method for distortion correction of electronic endoscope images

    Publication Year: 1995 , Page(s): 548 - 555
    Cited by:  Papers (16)  |  Patents (5)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (584 KB)  

    A new method to correct the barrel distortion of an electronic endoscope image is presented. A correction model assuming circularly symmetric distortion is introduced with the following model parameters: the center of distortion and the coefficients of polynomials representing the distortion correction in the radial direction. If the imaging system is distortion-free, straight lines in the object space should be imaged as straight lines. Based on this criterion, a distorted image of a standard pattern consisting of a grid of several straight lines is recorded, and the model parameters are then estimated as a basis for straightening distorted lines. This method has the advantage of not needing a careful placement of the standard pattern for calibration. Correction results are presented for the grid pattern chart to verify a sufficient degree of correction. Examples of distortion correction of real intestinal images and physicians' comments are also presented View full abstract»

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  • Theoretical relationships of receptor and delivery sensitivities and measurable parameters in in vivo neuroreceptor-radioligand interactions

    Publication Year: 1995 , Page(s): 608 - 615
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (596 KB)  

    In vivo quantification of neuroreceptors in human brains by PET or SPECT is complicated by the fact that a number of variables other than receptor concentration may influence the observed radioactivity in a brain region. This consideration has led the authors to formulate rigorous mathematical definitions of the concepts of receptor and delivery sensitivities. It has been speculated that a neuroreceptor-radioligand system having a high (low) receptor sensitivity would have a low (high) delivery sensitivity, and that the receptor sensitivity of a neuroreceptor-radioligand system can be determined by observing the time-course of the brain radioligand concentration following injection of no carrier added (nca) radioligand. Computer simulation studies of the characteristics of a simple model for in vivo neuroreceptor-radioligand interaction show that, under a set of realistic restrictions, there is a unique and intuitively satisfying relationship between receptor and delivery sensitivities: receptor sensitivity+delivery sensitivity≈1. In addition, the receptor sensitivity can be computed as a function of the observable parameters of the nca radioligand time course. These straightforward relationships are surprising in light of the complexity of the analytical solutions View full abstract»

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  • An improved method for MRI artifact correction due to translational motion in the imaging plane

    Publication Year: 1995 , Page(s): 471 - 479
    Cited by:  Papers (8)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1328 KB)  

    A computer postprocessing technique is developed to remove MRI artifact arising from unknown translational motion in the imaging plane. Based on previous artifact correction methods, the improved technique uses two successive steps to reduce read out and phase-encoding direction artifacts: First, the spectrum shift method is applied to remove read-out axis translational motion. Then, the phase retrieval method is employed to eliminate the remaining subpixel motion of the read-out axis and the entire motion of the phase-encoding axis. In the presence of noise, to protect edge detection (in the spectrum shift method), two high-density gray-level markers are added, one to each side of the imaging object. Experimental results with an actual MR scan confirmed the ability of the method to correct the artifact of an MR image caused by unknown translational motion in the imaging plane View full abstract»

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  • Markov random field for tumor detection in digital mammography

    Publication Year: 1995 , Page(s): 565 - 576
    Cited by:  Papers (42)  |  Patents (19)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1112 KB)  

    A technique is proposed for the detection of tumors in digital mammography. Detection is performed in two steps: segmentation and classification. In segmentation, regions of interest are first extracted from the images by adaptive thresholding. A further reliable segmentation is achieved by a modified Markov random field (MRF) model-based method. In classification, the MRF segmented regions are classified into suspicious and normal by a fuzzy binary decision tree based on a series of radiographic, density-related features. A set of normal (50) and abnormal (45) screen/film mammograms were tested. The latter contained 48 biopsy proven, malignant masses of various types and subtlety. The detection accuracy of the algorithm was evaluated by means of a free response receiver operating characteristic curve which shows the relationship between the detection of true positive masses and the number of false positive alarms per image. The results indicated that a 90% sensitivity can be achieved in the detection of different types of masses at the expense of two falsely detected signals per image. The algorithm was notably successful in the detection of minimal cancers manifested by masses ⩽10 mm in size. For the 16 such cases in the authors' dataset, a 94% sensitivity was observed with 1.5 false alarms per image. An extensive study of the effects of the algorithm's parameters on its sensitivity and specificity was also performed in order to optimize the method for a clinical, observer performance study View full abstract»

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  • Out-of-plane motion compensation in multislice spin-echo MRI

    Publication Year: 1995 , Page(s): 464 - 470
    Cited by:  Papers (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (800 KB)  

    In magnetic resonance imaging (MRI), it is well-known that patient motion plays a significant role in the degradation of image quality. Although the case of translational in-plane motion (x-y-motion) has been studied by several researchers, the effect of rigid, translational out-of-plane motion (z-motion) has not yet been completely analyzed due to its more complex nature. Out-of-plane motion introduces blurring along the slice-selection direction in addition to motion artifacts. Here, the authors present a model to represent the effect of out-of-plane motion on multislice MR data. The inversion of this model not only results in the correction of the artifacts due to out-of-plane motion, but also reduces blurring in the slice-selection direction, yielding higher resolution images. Because of the shift-varying nature of the authors' model, they propose to use a nonlinear postprocessing method, projection onto convex sets (POCS), for its inversion, provided that the motion kernel and the slice-selection profile are known. The proposed method has been tested on simulated data and then applied to actual MR data to demonstrate the feasibility of the technique in real imaging situations View full abstract»

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  • Protocol for the clinical functionality assessment of a workstation for stereotactic neurosurgery

    Publication Year: 1995 , Page(s): 577 - 586
    Cited by:  Papers (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1020 KB)  

    The objective of this study is to establish a protocol for the technical and clinical evaluation of a workstation for the planning of stereotactic neurosurgical interventions that has been developed in the framework of a joint European research project. Although several such workstations have been proposed before, they lacked the final and most important step, that of clinical validation. They failed to rigorously prove that their product was useful. The authors present a new method that is applicable to the evaluation of a wide range of medical technologies. Their protocol basically assesses the clinical relevance of the user requirements that are at the root of the development of the new technology. The evaluation consists of two stages. During functional specification, iterative prototyping is used to establish the clinical requirements and to assure the quality of the final product. A case study design is used in a second stage that assesses the clinical usability. A before-after study gives a first indication of cost effectiveness and improvement of health care quality View full abstract»

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  • Automatic detection of rib borders in chest radiographs

    Publication Year: 1995 , Page(s): 525 - 536
    Cited by:  Papers (14)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1092 KB)  

    An algorithm for detection of posterior rib borders in chest radiographs is presented. The algorithm first determines the thoracic cage boundary to restrict the area of search for the ribs. It then finds approximate rib borders using a knowledge-based Hough transform. Finally, the algorithm localizes the rib borders using an active contour model. Results of the proposed rib finding algorithm on 10 chest radiographs are presented View full abstract»

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  • Spectral extrapolation of spatially bounded images [MRI application]

    Publication Year: 1995 , Page(s): 487 - 497
    Cited by:  Papers (14)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (988 KB)  

    A spectral extrapolation algorithm for spatially bounded images is presented. An image is said to be spatially bounded when it is confined to a closed region and is surrounded by a background of zeros. With prior knowledge of the spatial domain zeros, the extrapolation algorithm extends the image's spectrum beyond a known interval of low-frequency components. The result, which is referred to as the finite support solution, has space variant resolution; features near the edge of the support region are better resolved than those in the center. The resolution of the finite support solution is discussed as a function of the number of known spatial zeros and known spectral components. A regularized version of the finite support solution is included for handling the case where the known spectral components are noisy. For both the noiseless and noisy cases, the resolution of the finite support solution is measured in terms of its impulse response characteristics, and compared to the resolution of the zerofilled and Nyquist solutions. The finite support solution is superior to the zerofilled solution for both the noisy and noiseless data cases. When compared to the Nyquist solution, the finite support solution may be preferred in the noisy data case. Examples using medical image data are provided View full abstract»

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  • Truncation artifact reduction in magnetic resonance imaging by Markov random field methods

    Publication Year: 1995 , Page(s): 434 - 441
    Cited by:  Papers (3)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (740 KB)  

    A new statistical method is proposed for reduction of truncation artifacts when reconstructing a function by a finite number of its Fourier series coefficients. Following the Bayesian approach, it is possible to take into account both the errors induced by the truncation of the Fourier series and some specific characteristics of the function. A suitable Markov random field is used for modeling these characteristics. Furthermore, in applications like Magnetic Resonance Imaging, where these coefficients are the measured data, the experimental random noise in the data can also be taken into account. Monte Carlo Markov chain methods are used to make statistical inference. Parameter selection in the Bayesian model is also addressed and a solution for selecting the parameters automatically is proposed. The method is applied successfully to both simulated and real magnetic resonance images View full abstract»

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  • Tracking and finite element analysis of stripe deformation in magnetic resonance tagging

    Publication Year: 1995 , Page(s): 413 - 421
    Cited by:  Papers (53)  |  Patents (2)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1076 KB)  

    Magnetic resonance tissue tagging allows noninvasive in vivo measurement of soft tissue deformation. Planes of magnetic saturation are created, orthogonal to the imaging plane, which form dark lines (stripes) in the image. The authors describe a method for tracking stripe motion in the image plane, and show how this information can be incorporated into a finite element model of the underlying deformation. Human heart data were acquired from several imaging planes in different orientations and were combined using a deformable model of the left ventricle wall. Each tracked stripe point provided information on displacement orthogonal to the original tagging plane, i.e., a one-dimensional (1-D) constraint on the motion. Three-dimensional (3-D) motion and deformation was then reconstructed by fitting the model to the data constraints by linear least squares. The average root mean squared (rms) error between tracked stripe points and predicted model locations was 0.47 mm (n=3,100 points). In order to validate this method and quantify the errors involved, the authors applied it to images of a silicone gel phantom subjected to a known, well-controlled, 3-D deformation. The finite element strains obtained were compared to an analytic model of the deformation known to be accurate in the central axial plane of the phantom. The average rms errors were 6% in both the reconstructed shear strains and 16% in the reconstructed radial normal strain View full abstract»

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  • Parallel data resampling and Fourier inversion by the scan-line method

    Publication Year: 1995 , Page(s): 454 - 463
    Cited by:  Papers (5)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (864 KB)  

    Fourier inversion is an efficient method for image reconstruction in a variety of applications, for example, in computed tomography and magnetic resonance imaging. Fourier inversion normally consists of two steps, interpolation of data onto a rectilinear grid, if necessary, and inverse Fourier transformation. Here, the authors present interpolation by the scan-line method, in which the interpolation algorithm is implemented in a form consisting only of row operations and data transposes. The two-dimensional inverse Fourier transformation can also be implemented with only row operations and data transposes. Accordingly, Fourier inversion can easily be implemented on a parallel computer that supports row operations and data transposes on row distributed data. The conditions under which the scan-line implementations are algorithmically equivalent to the original serial computer implementation are described and methods for improving accuracy outside of those conditions are presented. The scan-line algorithm is implemented on the iWarp parallel computer using the Adapt language for parallel image processing. This implementation is applied to magnetic resonance data acquired along radial-lines and spiral trajectories through Fourier transform space View full abstract»

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  • Applications of similarity mapping in dynamic MRI

    Publication Year: 1995 , Page(s): 480 - 486
    Cited by:  Papers (4)  |  Patents (2)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (604 KB)  

    Dynamic images are temporal sequences of images, where the intensities of certain regions of interest (ROI's) change with time, whereas anatomical structures remain stationary. Here, new applications of dynamic image analysis, called similarity mapping, are reviewed. Similarity mapping identifies regions in a dynamic image sequence according to their temporal similarity or dissimilarity with respect to a reference ROI. Pixels in the resulting similarity map whose temporal sequence is similar to the reference ROI have high correlation values and are bright, while those with low correlation values are dark. Therefore, similarity mapping segments structures in a dynamic image sequence based on their temporal responses rather than spatial properties. The authors describe the abilities of similarity mapping to identify different image structures present in several dynamic MRI datasets with potential clinical value. They demonstrate that similarity mapping technique has been successful in identifying the following structures: 1) renal cortex and medulla, 2) activated areas of the brain during photic stimulation, 3) ischemia in the left coronary artery territory, 4) lung tumor, 5) tentorial meningioma, and 6) a region of focal ischemia in brain View full abstract»

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Aims & Scope

IEEE Transactions on Medical Imaging (T-MI) encourages the submission of manuscripts on imaging of body structures, morphology and function, and imaging of microscopic biological entities. The journal publishes original contributions on medical imaging achieved by various modalities, such as ultrasound, X-rays (including CT) magnetic resonance, radionuclides, microwaves, and light, as well as medical image processing and analysis, visualization, pattern recognition, and related methods. Studies involving highly technical perspectives are most welcome. The journal focuses on a unified common ground where instrumentation, systems, components, hardware and software, mathematics and physics contribute to the studies.

Full Aims & Scope

Meet Our Editors

Editor-in-Chief
Michael Insana
Beckman Institute for Advanced Science and Technology
Department of Bioengineering
University of Illinois at Urbana-Champaign
Urbana, IL 61801 USA
m.f.i@ieee.org