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Medical Imaging, IEEE Transactions on

Issue 9 • Date Sept. 1999

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Displaying Results 1 - 8 of 8
  • Adaptive fuzzy segmentation of magnetic resonance images

    Page(s): 737 - 752
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (894 KB)  

    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 intensity inhomogeneities as a gain field that causes image intensities to smoothly and slowly vary through the image space. It iteratively adapts to the intensity inhomogeneities and is completely automated. In this paper, the authors fully generalize 2-D AFCM to three-dimensional (3-D) multispectral images. Because of the potential size of 3-D image data, they also describe a new faster multigrid-based algorithm for its implementation. They show, using simulated MR data, that 3-D AFCM yields lower error rates than both the standard fuzzy C-means (FCM) algorithm and two other competing methods, when segmenting corrupted images. Its efficacy is further demonstrated using real 3-D scalar and multispectral MR brain images. View full abstract»

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  • A characterization of the geometric architecture of the peritalar joint complex via MRI, an aid to classification of foot type

    Page(s): 753 - 763
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (535 KB)  

    The purpose of this work is to study the architecture of the rearfoot using in vivo MR image data. Each data set used in this study is made of sixty sagittal slices of the foot acquired in a 1.5-T commercial GE MR system. The authors use the live-wire method to delineate boundaries and form the surfaces of the bones. In the first part of this work, they describe a new method to characterize the three-dimensional (3-D) relationships of four bones of the peritalar complex and apply this description technique to data sets from ten normal subjects and from seven pathological cases. In the second part, the authors propose a procedure to classify feet, based on the values of these new architectural parameters. They conclude that this noninvasive method offers a unique tool to characterize the 3-D architecture of the feet in live patients, based on a set of new architectural parameters. This can be integrated into a set of tools to improve diagnosis and treatment of foot malformations. View full abstract»

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  • Thoracic electrical impedance tomographic measurements during volume controlled ventilation-effects of tidal volume and positive end-expiratory pressure

    Page(s): 764 - 773
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (630 KB)  

    The aim of the study was to analyze thoracic electrical impedance tomographic (EIT) measurements accomplished under conditions comparable with clinical situations during artificial ventilation. Multiple EIT measurements were performed in pigs in three transverse thoracic planes during the volume controlled mode of mechanical ventilation at various tidal volumes (V T) and positive end-expiratory pressures (PEEP). The protocol comprised following ventilatory patterns: (1) V T (400, 500, 600, 700 ml) was varied in a random order at various constant PEEP levels and (2) PEEP (2, 5, 8, 11, 14 cm H 2O) was randomly modified during ventilation with a constant V T. The EIT technique was used to generate cross-sectional images of (1) regional lung ventilation and (2) regional shifts in lung volume with PEEP. The quantitative analysis was performed in terms of the tidal amplitude of the impedance change, reflecting the volume of delivered gas at various preset V T and the end-expiratory impedance change, revealing the variation of the lung volume at various PEEP levels. The results showed: (1) an increase in the tidal amplitude of the impedance change, proportional to the delivered V T at all constant PEEP levels, (2) a rising end-expiratory impedance change, with PEEP reflecting an increase in gas volume, and (3) a PEEP-dependent redistribution of the ventilated gas between the planes. The generated images and the quantitative results indicate the ability of EIT to identify regional changes in V T and lung volume during mechanical ventilation. View full abstract»

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  • Scale-space signatures for the detection of clustered microcalcifications in digital mammograms

    Page(s): 774 - 786
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (420 KB)  

    A method is described for the automated detection of microcalcifications in digitized mammograms. The method is based on the Laplacian scale-space representation of the mammogram only. First, possible locations of microcalcifications are identified as local maxima in the filtered image on a range of scales. For each finding, the size and local contrast is estimated, based on the Laplacian response denoted as the scale-space signature. A finding is marked as a microcalcification if the estimated contrast is larger than a predefined threshold which depends on the size of the finding. It is shown that the signature has a characteristic peak, revealing the corresponding image features. This peak can be robustly determined. The basic method is significantly improved by consideration of the statistical variation of the estimated contrast, which is the result of the complex noise characteristic of the mammograms. The method is evaluated with the Nijmegen database and compared to other methods using these mammograms. Results are presented as the free-response receiver operating characteristic (FROG) performance. At a rate of one false positive cluster per image the method reaches a sensitivity of 0.84, which is comparable to the best results achieved so far. View full abstract»

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  • A novel multiscale nonlinear thresholding method for ultrasonic speckle suppressing

    Page(s): 787 - 794
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (501 KB)  

    This paper presents a novel speckle suppression method for medical B-scan ultrasonic images. An original image is first separated into two parts with an adaptive filter. These two parts are then transformed into a multiscale wavelet domain and the wavelet coefficients are processed by a soft thresholding method, which is a variation of Donoho's (1995) soft thresholding method. The processed coefficients for each part are then transformed back into the space domain. Finally, the denoised image is obtained as the sum of the two processed parts. A computer-simulated image and an in vitro B-scan image of a pig heart have been used to test the performance of this new method. This technique effectively reduces the speckle noise, while preserving the resolvable details. It performs well in comparison to the multiscale thresholding technique without adaptive preprocessing and two other speckle-suppression methods. View full abstract»

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  • Reversible compression of MR images

    Page(s): 795 - 800
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (134 KB)  

    Methods for reversible coding can be classified according to the organization of the source model as either static, semi-adaptive, or adaptive. Magnetic resonance (MR) images have different statistical characteristics in the foreground and the background and separation is thus a promising path for reversible MR image compression. A new reversible compression method, based on static source models for foreground and background separately, is presented. The method is nonuniversal and uses contextual information to exploit the fact that entropy and bit rate are reduced by increasing the statistical order of the model. This paper establishes a realistic level of expectation regarding the bit rate in reversible MR image compression, in general, and the bit rate using static modeling, in particular. The experimental results show that compression using the new method can give bit rates comparable to the best existing reversible methods. View full abstract»

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  • Monotonic algorithms for transmission tomography

    Page(s): 801 - 814
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (364 KB)  

    Presents a framework for designing fast and monotonic algorithms for transmission tomography penalized-likelihood image reconstruction. The new algorithms are based on paraboloidal surrogate functions for the log likelihood, Due to the form of the log-likelihood function it is possible to find low curvature surrogate functions that guarantee monotonicity. Unlike previous methods, the proposed surrogate functions lead to monotonic algorithms even for the nonconvex log likelihood that arises due to background events, such as scatter and random coincidences. The gradient and the curvature of the likelihood terms are evaluated only once per iteration. Since the problem is simplified at each iteration, the CPU time is less than that of current algorithms which directly minimize the objective, yet the convergence rate is comparable. The simplicity, monotonicity, and speed of the new algorithms are quite attractive. The convergence rates of the algorithms are demonstrated using real and simulated PET transmission scans. View full abstract»

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  • A cone-beam reconstruction algorithm for circle-plus-arc data-acquisition geometry

    Page(s): 815 - 824
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (351 KB)  

    In cone-beam computerized tomography (CT), projections acquired with the focal spot constrained on a planar orbit cannot provide a complete set of data to reconstruct the object function exactly. There are severe distortions in the reconstructed noncentral transverse planes when the cone angle is large. In this work, a new method is proposed which can obtain a complete set of data by acquiring cone-beam projections along a circle-plus-arc orbit. A reconstruction algorithm using this circle-plus-arc orbit is developed, based on the Radon transform and Grangeat's formula. This algorithm first transforms the cone-beam projection data of an object to the first derivative of the three-dimensional (3-D) Radon transform, using Grangeat's formula, and then reconstructs the object using the inverse Radon transform. In order to reduce interpolation errors, new rebinning equations have been derived accurately, which allows one-dimensional (1-D) interpolation to be used in the rebinning process instead of 3-D interpolation, A noise-free Defrise phantom and a Poisson noise-added Shepp-Logan phantom were simulated and reconstructed for algorithm validation. The results from the computer simulation indicate that the new cone-beam data-acquisition scheme can provide a complete set of projection data and the image reconstruction algorithm can achieve exact reconstruction. Potentially, the algorithm can be applied in practice for both a standard CT gantry-based volume tomographic imaging system and a C-arm-based cone-beam tomographic imaging system, with little mechanical modification required. 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