# IEEE Transactions on Medical Imaging

## Filter Results

Displaying Results 1 - 21 of 21

Publication Year: 2007, Page(s):C1 - C4
| PDF (129 KB)
• ### IEEE Transactions on Medical Imaging publication information

Publication Year: 2007, Page(s): C2
| PDF (40 KB)
• ### Guest Editorial Special Issue on Computational Diffusion MRI

Publication Year: 2007, Page(s):1425 - 1427
| PDF (561 KB) | HTML
• ### Impact of an Improved Combination of Signals From Array Coils in Diffusion Tensor Imaging

Publication Year: 2007, Page(s):1428 - 1436
Cited by:  Papers (11)
| | PDF (1264 KB) | HTML

An improved method for the combination of signals from array coils is presented as a way to reduce the influence of the noise floor on the estimation of diffusion tensor imaging (DTI) parameters. By an optimized combination of signals from the array channels and complex averaging of measurements, this method leads to a significant reduction of the noise bias. This combination algorithm allows comp... View full abstract»

• ### Accuracy of $q$-Space Related Parameters in MRI: Simulations and Phantom Measurements

Publication Year: 2007, Page(s):1437 - 1447
Cited by:  Papers (26)
| | PDF (471 KB) | HTML

The accuracy of q-space measurements was evaluated at a 3.0-T clinical magnetic resonance imaging (MRI) scanner, as compared with a 4.7-T nuclear magnetic resonance (NMR) spectrometer. Measurements were performed using a stimulated-echo pulse-sequence on n-decane as well as on polyethylene glycol (PEG) mixed with different concentrations of water, in order to obtain bi-exponential signal decay cur... View full abstract»

• ### New Perspectives on the Sources of White Matter DTI Signal

Publication Year: 2007, Page(s):1448 - 1455
Cited by:  Papers (30)
| | PDF (748 KB) | HTML

A minimalist numerical model of white matter is presented, the objective of which is to help provide a biological basis for improved diffusion tensor imaging (DTI) analysis. Water diffuses, relaxes, and exchanges in three compartments-intracellular, extracellular, and myelin sheath. Exchange between compartments is defined so as to depend on the diffusion coefficients and the compartment sizes. Ba... View full abstract»

• ### Simulations of Short-Time Diffusivity in Lung Airspaces and Implications for S/V Measurements Using Hyperpolarized-Gas MRI

Publication Year: 2007, Page(s):1456 - 1463
Cited by:  Papers (7)
| | PDF (1622 KB) | HTML

We demonstrate a method for simulating restricted diffusion of hyperpolarized gases in lung airspaces that does not rely on an idealized analytic model of alveolar structure. Instead, the restricting geometry was generated from digital representations of histological sections of actual lung tissue obtained from a rabbit model of emphysema. Monte-Carlo simulations of restricted diffusion were perfo... View full abstract»

• ### A Unified Computational Framework for Deconvolution to Reconstruct Multiple Fibers From Diffusion Weighted MRI

Publication Year: 2007, Page(s):1464 - 1471
Cited by:  Papers (90)  |  Patents (3)
| | PDF (649 KB) | HTML

Diffusion magnetic resonance imaging (MRI) is a relatively new imaging modality which is capable of measuring the diffusion of water molecules in biological systems noninvasively. The measurements from diffusion MRI provide unique clues for extracting orientation information of brain white matter fibers and can be potentially used to infer the brain connectivity in vivo using tractography techniqu... View full abstract»

• ### Clinical DT-MRI Estimation, Smoothing, and Fiber Tracking With Log-Euclidean Metrics

Publication Year: 2007, Page(s):1472 - 1482
Cited by:  Papers (120)
| | PDF (1558 KB) | HTML

Diffusion tensor magnetic resonance imaging (DT-MRI or DTI) is an imaging modality that is gaining importance in clinical applications. However, in a clinical environment, data have to be acquired rapidly, often at the expense of the image quality. This often results in DTI datasets that are not suitable for complex postprocessing like fiber tracking. We propose a new variational framework to impr... View full abstract»

• ### Diffusion Tensor Analysis With Invariant Gradients and Rotation Tangents

Publication Year: 2007, Page(s):1483 - 1499
Cited by:  Papers (27)
| | PDF (3656 KB) | HTML

Guided by empirically established connections between clinically important tissue properties and diffusion tensor parameters, we introduce a framework for decomposing variations in diffusion tensors into changes in shape and orientation. Tensor shape and orientation both have three degrees-of-freedom, spanned by invariant gradients and rotation tangents, respectively. As an initial demonstration o... View full abstract»

• ### A Computational Framework for the Statistical Analysis of Cardiac Diffusion Tensors: Application to a Small Database of Canine Hearts

Publication Year: 2007, Page(s):1500 - 1514
Cited by:  Papers (58)  |  Patents (4)
| | PDF (1751 KB) | HTML

We propose a unified computational framework to build a statistical atlas of the cardiac fiber architecture from diffusion tensor magnetic resonance images (DT-MRIs). We apply this framework to a small database of nine ex vivo canine hearts. An average cardiac fiber architecture and a measure of its variability are computed using most recent advances in diffusion tensor statistics. This statistica... View full abstract»

• ### Probabilistic Inference on Q-ball Imaging Data

Publication Year: 2007, Page(s):1515 - 1524
Cited by:  Papers (9)
| | PDF (743 KB) | HTML

Diffusion-weighted magnetic resonance imaging (MRI) and especially diffusion tensor imaging (DTI) have proven to be useful for the characterization of the microstructure of brain white matter structures in vivo. However, DTI suffers from a number of limitations in characterizing more complex situations. The most notable problem occurs when multiple fibre bundles are present within a voxel. In this... View full abstract»

• ### A Fuzzy, Nonparametric Segmentation Framework for DTI and MRI Analysis: With Applications to DTI-Tract Extraction

Publication Year: 2007, Page(s):1525 - 1536
Cited by:  Papers (32)
| | PDF (1962 KB) | HTML

This paper presents a novel fuzzy-segmentation method for diffusion tensor (DT) and magnetic resonance (MR) images. Typical fuzzy-segmentation schemes, e.g., those based on fuzzy C means (FCM), incorporate Gaussian class models that are inherently biased towards ellipsoidal clusters characterized by a mean element and a covariance matrix. Tensors in fiber bundles, however, inherently lie on specif... View full abstract»

• ### Tensor Splines for Interpolation and Approximation of DT-MRI With Applications to Segmentation of Isolated Rat Hippocampi

Publication Year: 2007, Page(s):1537 - 1546
Cited by:  Papers (32)
| | PDF (638 KB) | HTML

In this paper, we present novel algorithms for statistically robust interpolation and approximation of diffusion tensors-which are symmetric positive definite (SPD) matrices-and use them in developing a significant extension to an existing probabilistic algorithm for scalar field segmentation, in order to segment diffusion tensor magnetic resonance imaging (DT-MRI) datasets. Using the Riemannian m... View full abstract»

• ### Representing Diffusion MRI in 5-D Simplifies Regularization and Segmentation of White Matter Tracts

Publication Year: 2007, Page(s):1547 - 1554
Cited by:  Papers (11)
| | PDF (566 KB) | HTML

We present a new five-dimensional (5-D) space representation of diffusion magnetic resonance imaging (dMRI) of high angular resolution. This 5-D space is basically a non-Euclidean space of position and orientation in which crossing fiber tracts can be clearly disentangled, that cannot be separated in three-dimensional position space. This new representation provides many possibilities for processi... View full abstract»

• ### A Probabilistic Model-Based Approach to Consistent White Matter Tract Segmentation

Publication Year: 2007, Page(s):1555 - 1561
Cited by:  Papers (35)  |  Patents (1)
| | PDF (333 KB) | HTML

Since the invention of diffusion magnetic resonance imaging (dMRI), currently the only established method for studying white matter connectivity in a clinical environment, there has been a great deal of interest in the effects of various pathologies on the connectivity of the brain. As methods for in vivo tractography have been developed, it has become possible to track and segment specific white ... View full abstract»

• ### Automatic Tractography Segmentation Using a High-Dimensional White Matter Atlas

Publication Year: 2007, Page(s):1562 - 1575
Cited by:  Papers (116)  |  Patents (3)
| | PDF (2042 KB) | HTML

We propose a new white matter atlas creation method that learns a model of the common white matter structures present in a group of subjects. We demonstrate that our atlas creation method, which is based on group spectral clustering of tractography, discovers structures corresponding to expected white matter anatomy such as the corpus callosum, uncinate fasciculus, cingulum bundles, arcuate fascic... View full abstract»

• ### Parsimonious Model Selection for Tissue Segmentation and Classification Applications: A Study Using Simulated and Experimental DTI Data

Publication Year: 2007, Page(s):1576 - 1584
Cited by:  Papers (13)  |  Patents (1)
| | PDF (789 KB) | HTML

One aim of this work is to investigate the feasibility of using a hierarchy of models to describe diffusion tensor magnetic resonance (MR) data in fixed tissue. Parsimonious model selection criteria are used to choose among different models of diffusion within tissue. Using this information, we assess whether we can perform simultaneous tissue segmentation and classification. Both numerical phanto... View full abstract»

• ### High-Dimensional Spatial Normalization of Diffusion Tensor Images Improves the Detection of White Matter Differences: An Example Study Using Amyotrophic Lateral Sclerosis

Publication Year: 2007, Page(s):1585 - 1597
Cited by:  Papers (92)
| | PDF (1091 KB) | HTML

Spatial normalization of diffusion tensor images plays a key role in voxel-based analysis of white matter (WM) group differences. Currently, it has been achieved using low-dimensional registration methods in the large majority of clinical studies. This paper aims to motivate the use of high-dimensional normalization approaches by generating evidence of their impact on the findings of such studies.... View full abstract»

• ### Nonrigid Coregistration of Diffusion Tensor Images Using a Viscous Fluid Model and Mutual Information

Publication Year: 2007, Page(s):1598 - 1612
Cited by:  Papers (71)
| | PDF (1895 KB) | HTML

In this paper, a nonrigid coregistration algorithm based on a viscous fluid model is proposed that has been optimized for diffusion tensor images (DTI), in which image correspondence is measured by the mutual information criterion. Several coregistration strategies are introduced and evaluated both on simulated data and on brain intersubject DTI data. Two tensor reorientation methods have been inc... View full abstract»

• ### IEEE Transactions on Medical Imaging Information for authors

Publication Year: 2007, Page(s): C3
| PDF (27 KB)

## Aims & Scope

IEEE Transactions on Medical Imaging (T-MI) encourages the submission of manuscripts on imaging of body structure, morphology and function, including cell and molecular imaging and all forms of microscopy. The journal publishes original contributions on medical imaging achieved by modalities including ultrasound, x-rays, magnetic resonance, radionuclides, microwaves, and optical methods. Contributions describing novel acquisition techniques, medical image processing and analysis, visualization and performance, pattern recognition, machine learning, and related methods are encouraged. Studies involving highly technical perspectives are most welcome.

The focus of the journal is on unifying the sciences of medicine, biology, and imaging. It emphasizes the common ground where instrumentation, hardware, software, mathematics, physics, biology, and medicine interact through new analysis methods. Strong application papers that describe novel methods are particularly encouraged. Papers describing important applications based on medically adopted and/or established methods without significant innovation in methodology will be directed to other journals.

To qualify for publication, submitted manuscripts must be previously unpublished and must not be under consideration elsewhere. The Editor-in-Chief and an Associate Editor will perform a quick review of each manuscript to evaluate the manuscript in terms of novelty, quality and appropriateness and may return the manuscript immediately if it does not meet minimum standards of quality, originality, and scope. Manuscripts will ONLY be accepted in electronic format through ScholarOne Manuscripts. Please go to the ScholarOne Manuscripts website at http://mc.manuscriptcentral.com/tmi-ieee or to the TMI website http://www.ieee-tmi.org/ to find instructions to electronically submit your manuscript. Do not send original submissions or revisions directly to the Editor-in-Chief or Associate Editors.

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