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Medical Imaging, IEEE Transactions on

Issue 3 • Date March 2008

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Displaying Results 1 - 16 of 16
  • Table of contents

    Publication Year: 2008 , Page(s): C1
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  • IEEE Transactions on Medical Imaging publication information

    Publication Year: 2008 , Page(s): C2
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  • Seamless Warping of Diffusion Tensor Fields

    Publication Year: 2008 , Page(s): 285 - 299
    Cited by:  Papers (7)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (884 KB) |  | HTML iconHTML  

    To warp diffusion tensor fields accurately, tensors must be reoriented in the space to which the tensors are warped based on both the local deformation field and the orientation of the underlying fibers in the original image. Existing algorithms for warping tensors typically use forward mapping deformations in an attempt to ensure that the local deformations in the warped image remains true to the orientation of the underlying fibers; forward mapping, however, can also create ldquoseamsrdquo or gaps and consequently artifacts in the warped image by failing to define accurately the voxels in the template space where the magnitude of the deformation is large (e.g., |Jacobian| > 1). Backward mapping, in contrast, defines voxels in the template space by mapping them back to locations in the original imaging space. Backward mapping allows every voxel in the template space to be defined without the creation of seams, including voxels in which the deformation is extensive. Backward mapping, however, cannot reorient tensors in the template space because information about the directional orientation of fiber tracts is contained in the original, unwarped imaging space only, and backward mapping alone cannot transfer that information to the template space. To combine the advantages of forward and backward mapping, we propose a novel method for the spatial normalization of diffusion tensor (DT) fields that uses a bijection (a bidirectional mapping with one-to-one correspondences between image spaces) to warp DT datasets seamlessly from one imaging space to another. Once the bijection has been achieved and tensors have been correctly relocated to the template space, we can appropriately reorient tensors in the template space using a warping method based on Procrustean estimation. View full abstract»

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  • Phonovibrography: Mapping High-Speed Movies of Vocal Fold Vibrations Into 2-D Diagrams for Visualizing and Analyzing the Underlying Laryngeal Dynamics

    Publication Year: 2008 , Page(s): 300 - 309
    Cited by:  Papers (32)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1717 KB) |  | HTML iconHTML  

    Endoscopic high-speed laryngoscopy in combination with image analysis strategies is the most promising approach to investigate the interrelation between vocal fold vibrations and voice disorders. So far, due to the lack of an objective and standardized analysis procedure a unique characterization of vocal fold vibrations has not been achieved yet. We present a visualization and analysis strategy which transforms the segmented edges of vibrating vocal folds into a single 2-D image, denoted Phonovibrogram (PVG). Within a PVG the individual type of vocal fold vibration becomes uniquely characterized by specific geometric patterns. The PVG geometries give an intuitive access on the type and degree of the laryngeal asymmetry and can be quantified using an image segmentation approach. The PVG analysis was applied to 14 representative recordings derived from a high-speed database comprising normal and pathological voices. We demonstrate that PVGs are capable to differentiate and quantify different types of normal and pathological vocal fold vibrations. The objective and precise quantification of the PVG geometry may have the potential to realize a novel classification of vocal fold vibrations. View full abstract»

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  • A Novel Method for the Automatic Grading of Retinal Vessel Tortuosity

    Publication Year: 2008 , Page(s): 310 - 319
    Cited by:  Papers (30)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (2208 KB) |  | HTML iconHTML  

    Tortuosity is among the first alterations in the retinal vessel network to appear in many retinopathies, such as those due to hypertension. An automatic evaluation of retinal vessel tortuosity would help the early detection of such retinopathies. Quite a few techniques for tortuosity measurement and classification have been proposed, but they do not always match the clinical concept of tortuosity. This justifies the need for a new definition, able to express in mathematical terms the tortuosity as perceived by ophthalmologists. We propose here a new algorithm for the evaluation of tortuosity in vessels recognized in digital fundus images. It is based on partitioning each vessel in segments of constant-sign curvature and then combining together each evaluation of such segments and their number. The algorithm has been compared with other available tortuosity measures on a set of 30 arteries and one of 30 veins from 60 different images. These vessels had been preliminarily ordered by a retina specialist by increasing perceived tortuosity. The proposed algorithm proved to be the best one in matching the clinically perceived vessel tortuosity. View full abstract»

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  • Analysis of Tumor Vascularity Using Three-Dimensional Power Doppler Ultrasound Images

    Publication Year: 2008 , Page(s): 320 - 330
    Cited by:  Papers (23)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (995 KB) |  | HTML iconHTML  

    Tumor vascularity is an important factor that has been shown to correlate with tumor malignancy and was demonstrated as a prognostic indicator for a wide range of cancers. Three-dimensional (3-D) power Doppler ultrasound (PDUS) offers a convenient tool for investigators to inspect the signals of blood flow and vascular structures in breast cancer. In this paper, a new computer-aided diagnosis (CAD) system for quantifying Doppler ultrasound images based on 3-D thinning algorithm and neural network is proposed. We extracted the skeleton of blood vessels from 3-D PDUS data to facilitate the capturing of morphological changes. Nine features including vessel-to-volume ratio, number of vascular trees, length of vessels, number of branching, mean of radius, number of cycles, and three tortuosity measures, were extracted from the thinning result. Benign and malignant tumors can therefore be differentiated by a score computed by a multilayered perceptron (MLP) neural network using these features as parameters. The proposed system was tested on 221 breast tumors, including 110 benign and 111 malignant lesions. The accuracy, sensitivity, specificity, and positive and negative predictive values were 88.69% (196/221), 91.89% (102/111), 85.45% (94/110), 86.44% (102/118), and 91.26% (94/103), respectively. The value of the ROC curve was 0.94. The results demonstrate a correlation between the morphology of blood vessels and tumor malignancy, indicating that the newly proposed method can retrieves a high accuracy in the classification of benign and malignant breast tumors. View full abstract»

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  • Multiscale Vascular Surface Model Generation From Medical Imaging Data Using Hierarchical Features

    Publication Year: 2008 , Page(s): 331 - 341
    Cited by:  Papers (14)  |  Patents (17)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1341 KB) |  | HTML iconHTML  

    Computational fluid dynamics (CFD) modeling of blood flow from image-based patient specific models can provide useful physiologic information for guiding clinical decision making. A novel method for the generation of image-based, 3-D, multiscale vascular surface models for CFD is presented. The method generates multiscale surfaces based on either a linear triangulated or a globally smooth nonuniform rational B-spline (NURB) representation. A robust local curvature analysis is combined with a novel global feature analysis to set mesh element size. The method is particularly useful for CFD modeling of complex vascular geometries that have a wide range of vasculature size scales, in conditions where 1) initial surface mesh density is an important consideration for balancing surface accuracy with manageable size volumetric meshes, 2) adaptive mesh refinement based on flow features makes an underlying explicit smooth surface representation desirable, and 3) semi-automated detection and trimming of a large number of inlet and outlet vessels expedites model construction. View full abstract»

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  • Segmentation of Rodent Whole-Body Dynamic PET Images: An Unsupervised Method Based on Voxel Dynamics

    Publication Year: 2008 , Page(s): 342 - 354
    Cited by:  Papers (12)  |  Patents (4)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (623 KB) |  | HTML iconHTML  

    Positron emission tomography (PET) is a useful tool for pharmacokinetics studies in rodents during the preclinical phase of drug and tracer development. However, rodent organs are small as compared to the scanner's intrinsic resolution and are affected by physiological movements. We present a new method for the segmentation of rodent whole-body PET images that takes these two difficulties into account by estimating the pharmacokinetics far from organ borders. The segmentation method proved efficient on whole-body numerical rat phantom simulations, including 3-14 organs, together with physiological movements (heart beating, breathing, and bladder filling). The method was resistant to spillover and physiological movements, while other methods failed to obtain a correct segmentation. The radioactivity concentrations calculated with this method also showed an excellent correlation with the manual delineation of organs in a large set of preclinical images. In addition, it was faster, detected more organs, and extracted organs' mean time activity curves with a better confidence on the measure than manual delineation. View full abstract»

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  • Intraoperative Laparoscope Augmentation for Port Placement and Resection Planning in Minimally Invasive Liver Resection

    Publication Year: 2008 , Page(s): 355 - 369
    Cited by:  Papers (28)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1031 KB) |  | HTML iconHTML  

    In recent years, an increasing number of liver tumor indications were treated by minimally invasive laparoscopic resection. Besides the restricted view, two major intraoperative issues in laparoscopic liver resection are the optimal planning of ports as well as the enhanced visualization of (hidden) vessels, which supply the tumorous liver segment and thus need to be divided (e.g., clipped) prior to the resection. We propose an intuitive and precise method to plan the placement of ports. Pre operatively, self-adhesive fiducials are affixed to the patient's skin and a computed tomography (CT) data set is acquired while contrasting the liver vessels. Immediately prior to the intervention, the laparoscope is moved around these fiducials, which are automatically reconstructed to register the patient to its preoperative imaging data set. This enables the simulation of a camera flight through the patient's interior along the laparoscope's or instruments' axes to easily validate potential ports. Intraoperatively, surgeons need to update their surgical planning based on actual patient data after organ deformations mainly caused by application of carbon dioxide pneumoperitoneum. Therefore, preoperative imaging data can hardly be used. Instead, we propose to use an optically tracked mobile C-arm providing cone-beam CT imaging capability intraoperatively. After patient positioning, port placement, and carbon dioxide insufflation, the liver vessels are contrasted and a 3-D volume is reconstructed during patient exhalation. Without any further need for patient registration, the reconstructed volume can be directly augmented on the live laparoscope video, since prior calibration enables both the volume and the laparoscope to be positioned and oriented in the tracking coordinate frame. The augmentation provides the surgeon with advanced visual aid for the localization of veins, arteries, and bile ducts to be divided or sealed. View full abstract»

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  • A New Method for Registration-Based Medical Image Interpolation

    Publication Year: 2008 , Page(s): 370 - 377
    Cited by:  Papers (21)  |  Patents (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (814 KB) |  | HTML iconHTML  

    A new technique is presented for interpolating between grey-scale images in a medical data set. Registration between neighboring slices is achieved with a modified control grid interpolation algorithm that selectively accepts displacement field updates in a manner optimized for performance. A cubic interpolator is then applied to pixel intensities correlated by the displacement fields. Special considerations are made for efficiency, interpolation quality, and compression in the implementation of the algorithm. Experimental results show that the new method achieves good quality, while offering dramatic improvement in efficiency relative to the best competing method. View full abstract»

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  • A Statistical Model for Point-Based Target Registration Error With Anisotropic Fiducial Localizer Error

    Publication Year: 2008 , Page(s): 378 - 390
    Cited by:  Papers (20)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (571 KB) |  | HTML iconHTML  

    Error models associated with point-based medical image registration problems were first introduced in the late 1990s. The concepts of fiducial localizer error, fiducial registration error, and target registration error are commonly used in the literature. The model for estimating the target registration error at a position r in a coordinate frame defined by a set of fiducial markers rigidly fixed relative to one another is ubiquitous in the medical imaging literature. The model has also been extended to simulate the target registration error at the point of interest in optically tracked tools. However, the model is limited to describing the error in situations where the fiducial localizer error is assumed to have an isotropic normal distribution in R3. In this work, the model is generalized to include a fiducial localizer error that has an anisotropic normal distribution. Similar to the previous models, the root mean square statistic rmstre is provided along with an extension that provides the covariance matrix Sigmatre. The new model is verified using a Monte Carlo simulation and a set of statistical hypothesis tests. Finally, the differences between the two assumptions, isotropic and anisotropic, are discussed within the context of their use in 1) optical tool tracking simulation and 2) image registration. View full abstract»

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  • Registered 3-D Ultrasound and Digital Stereotactic Mammography for Breast Biopsy Guidance

    Publication Year: 2008 , Page(s): 391 - 401
    Cited by:  Papers (6)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1449 KB) |  | HTML iconHTML  

    Large core needle biopsy is a common procedure used to obtain histological samples when cancer is suspected in diagnostic breast images. The procedure is typically performed under image guidance, with freehand ultrasound and stereotactic mammography (SM) being the most common modalities used. To utilize the advantages of both modalities, a biopsy device combining three-dimensional ultrasound (3DUS) and digital SM imaging with computer-aided needle guidance was developed. An implementation of a stereo camera method was applied to SM calibration, providing a target localization error of 0.35 mm. The 3D transformation between the two imaging modalities was then derived, with a target registration error of 0.52 mm. Finally, the needle guidance error of the device was evaluated using tissue-mimicking phantoms, showing a sample mean and standard deviation of and 0.49 plusmn 0.27 mm for targets planned from 3DUS and SM images, respectively. These results suggest that a biopsy procedure guided using this device would successfully sample breast lesions at a size greater than or equal to the smallest typically detected in mammographic screening (~2mm). View full abstract»

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  • An Analytical Scatter Correction for Singles-Mode Transmission Data in PET

    Publication Year: 2008 , Page(s): 402 - 412
    Cited by:  Papers (2)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (2212 KB) |  | HTML iconHTML  

    We present an analytical scatter correction, based upon the Klein-Nishina formula, for singles-mode transmission data in positron emission tomography (PET) and its implementation as part of an iterative image reconstruction algorithm. We compared our analytically-calculated scatter sinogram data with previously validated simulation data for a small animal PET scanner with 68Ge (a positron emitter) and 57Co (ap122-keV photon emitter) transmission sources using four different phantom configurations (three uniform water cylinders with radii of 25, 30, and 45 mm and a nonuniform phantom consisting of water, Teflon, and air). Our scatter calculation correctly predicts the contribution from single-scattered (one incoherent scatter interaction) photons to the simulated sinogram data and provides good agreement for the percent scatter fraction (SF) per sinogram for all phantoms and both transmission sources. We then applied our scatter correction as part of an iterative reconstruction algorithm for PET transmission data for simulated and experimental data using uniform and nonuniform phantoms. For both simulated and experimental data, the reconstructed linear attenuation coefficients (mu-values) agreed with expected values to within 4% when scatter corrections were applied, for both the 68Ge and 57Co transmission sources. We also tested our reconstruction and scatter correction procedure for two experimental rodent studies (a mouse and rat). For the rodent studies, we found that the average mu-values for soft-tissue regions of interest agreed with expected values to within 4%. Using a 2.2-GHz processor, each scatter correction iteration required between 6-27 min of CPU time (without any code optimization) depending on the phantom size and source used. This extra calculation time does not seem unreasonable considering that, without scatter corrections, errors in the reconstructed mu-values were between 18%-45% depending on the phan- - tom size and transmission source used. View full abstract»

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  • Analysis of Resolution and Noise Properties of Nonquadratically Regularized Image Reconstruction Methods for PET

    Publication Year: 2008 , Page(s): 413 - 424
    Cited by:  Papers (12)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (400 KB) |  | HTML iconHTML  

    We present accurate and efficient methods for estimating the spatial resolution and noise properties of nonquadratically regularized image reconstruction for positron emission tomography (PET). It is well known that quadratic regularization tends to over-smooth sharp edges. Many types of edge-preserving nonquadratic penalties have been proposed to overcome this problem. However, there has been little research on the quantitative analysis of nonquadratic regularization due to its nonlinearity. In contrast, quadratically regularized estimators are approximately linear and are well understood in terms of resolution and variance properties. We derive new approximate expressions for the linearized local perturbation response (LLPR) and variance using the Taylor expansion with the remainder term. Although the expressions are implicit, we can use them to accurately predict resolution and variance for nonquadratic regularization where the conventional expressions based on the first-order Taylor truncation fail. They also motivate us to extend the use of a certainty-based modified penalty to nonquadratic regularization cases in order to achieve spatially uniform perturbation responses, analogous to uniform spatial resolution in quadratic regularization. Finally, we develop computationally efficient methods for predicting resolution and variance of nonquadratically regularized reconstruction and present simulations that illustrate the validity of these methods. View full abstract»

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  • IEEE Transactions on Medical Imaging Information for authors

    Publication Year: 2008 , Page(s): C3
    Save to Project icon | Request Permissions | PDF file iconPDF (27 KB)  
    Freely Available from IEEE
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    Publication Year: 2008 , Page(s): C4
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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.

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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