31 research outputs found

    Unwarping of Unidirectionally Distorted EPI Images

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    Echo-planar imaging (EPI) is a fast nuclear magnetic resonance imaging (MRI) method. Unfortunately, local magnetic field inhomogeneities induced mainly by the subject's presence cause significant geometrical distortion, predominantly along the phase-encoding direction, which must be undone to allow for meaningful further processing. So far, this aspect has been too often neglected. In this paper, we suggest a new approach using an algorithm specifically developed for the automatic registration of distorted EPI images with corresponding anatomically correct MRI images. We model the deformation field with splines, which gives us a great deal of flexibility, while comprising the affine transform as a special case. The registration criterion is least squares. Interestingly, the complexity of its evaluation does not depend on the resolution of the control grid. The spline model gives us good accuracy thanks to its high approximation order. The short support of splines leads to a fast algorithm. A multiresolution approach yields robustness and additional speed-up. The algorithm was tested on real as well as synthetic data, and the results were compared with a manual method. A wavelet-based Sobolev-type random deformation generator was developed for testing purposes. A blind test indicates that the proposed automatic method is faster, more reliable, and more precise than the manual one

    Unwarping of unidirectionally distorted EPI images

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    Simulation-based evaluation of susceptibility distortion correction methods in diffusion MRI for connectivity analysis

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    Connectivity analysis on diffusion MRI data of the whole-brain suffers from distortions caused by the standard echo-planar imaging acquisition strategies. These images show characteristic geometrical deformations and signal destruction that are an important drawback limiting the success of tractography algorithms. Several retrospective correction techniques are readily available. In this work, we use a digital phantom designed for the evaluation of connectivity pipelines. We subject the phantom to a “theoretically correct” and plausible deformation that resembles the artifact under investigation. We correct data back, with three standard methodologies (namely fieldmap-based, reversed encoding-based, and registration- based). Finally, we rank the methods based on their geometrical accuracy, the dropout compensation, and their impact on the resulting connectivity matrices

    Respiratory Motion Estimation from Slowly Rotating X-Ray Projections

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    As radiotherapy has become increasingly conformal, geometric uncertainties caused by breathing and organ motion have become an important issue. Accurate motion estimates may lead to improved treatment planning and dose calculation in radiation therapy. However, respiratory motion is difficult to study by conventional X-ray CT imaging since object motion causes inconsistent projection views leading to artifacts in reconstructed images. We propose to estimate the parameters of a nonrigid motion model from a set of projection views of the thorax that are acquired using a slowly rotating cone-beam CT scanner, such as a radiotherapy simulator. We use a conventionally reconstructed 3D thorax image, acquired by breath-hold CT, as a reference volume. We represent respiratory motion using a flexible parametric nonrigid motion model based on B-splines. The motion parameters are estimated by optimizing a regularized cost function that includes the squared error between the measured projection views and the reprojections of the deformed reference image. Preliminary 2D simulation results show that there is good agreement between the estimated motion and the true motion.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/85878/1/Fessler197.pd

    Sufficient Condition for Local Invertibility of Spatio-Temporal 4D B-Spline Deformations

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    Recent advances in medical imaging technologies have made 4D image sequences available in clinical routine. As a consequence, image registration techniques are evolving from alignment of pairs of static volumetric images to spatio-temporal registration of dynamic (4D) images. Since the elastic image registration problem is ill-posed, additional prior information or constraints are usually required to regularize the problem. This work proposes to enforce local invertibility (diffeomorphism) of 4D deformations. A novel sufficient condition for local invertibility over continuous space and time is proposed and a practical regularization prior is designed from the theory. The method has been applied to an image registration (motion tracking) of a dynamic 4D CT image sequence. Results show that using proposed regularizer leads to deformations that are more plausible for respiratory motion than the standard approach without additional temporal regularization.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/85901/1/Fessler246.pd

    A Simple Penalty that Encourages Local Invertibility and Considers Sliding Effects for Respiratory Motion

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    Nonrigid image registration is a key tool in medical imaging. Because of high degrees of freedom in nonrigid transforms, there have been many efforts to regularize the deformation based on some reasonable assumptions. Especially, motion invertibility and local tissue rigidity have been investigated as reasonable priors in image registration. There have been several papers on exploiting each constraint separately. These constraints are reasonable in respiratory motion estimation because breathing motion is invertible and there are some rigid structures such as bones. Using both constraints seems very attractive in respiratory motion registration since using invertibility prior alone usually causes bone warping in ribs. Using rigidity prior seems natural and straightforward. However, the “sliding effect” near the interface between rib cage and diaphragm makes problem harder because it is not locally invertible. In this area, invertibility and rigidity priors have opposite forces. Recently, we proposed a simple piecewise quadratic penalty that encourages the local invertibility of motions. In this work we relax this penalty function by using a Geman-type function that allows the deformation to be piecewise smooth instead of globally smooth. This allows the deformation to be discontinuous in the area of the interface between rib cage and diaphragm. With some small sacrifice of regularity, we could achieve more realistic discontinuous motion near diaphragm, better data fitting error as well as less bone warping. We applied this Geman-type function penalty only to the x- and y-direction partial derivatives of the z-direction deformation to address the sliding effect. 192 × 128 × 128 3D CT inhale and exhale images of a real patient were used to show the benefits of this new penalty method.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/85922/1/Fessler238.pd

    Fast interpolation operations in non-rigid image registration

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    Much literature on image registration1–3 has worked with purely geometric image deformation models. For such models, interpolation/resampling operations are often the computationally intensive steps when iteratively minimizing the deformation cost function. This article discusses some techniques for efficiently implementing and accelerating these operations. To simplify presentation, we discuss our ideas in the context of 2D imaging. However, the concepts readily generalize to 3D. Our central technique is a table-lookup scheme that makes somewhat liberal use of RAM, but should not strain the resources of modern processors if certain design parameters are appropriately selected. The technique works by preinterpolating and tabulating the grid values of the reference image onto a finer grid along one of the axes of the image. The lookup table can be rapidly constructed using FFTs. Our results show that this technique reduces iterative computation by an order of magnitude. When a minimization algorithm employing coordinate block alternation is used, one can obtain still faster computation by storing certain intermediate quantities as state variables. We refer to this technique as state variable hold-over. When combined with table-lookup, state variable hold-over reduces CPU time by about a factor two, as compared to table-lookup alone.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/85925/1/Fessler207.pd

    Elastic image registration using parametric deformation models

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    The main topic of this thesis is elastic image registration for biomedical applications. We start with an overview and classification of existing registration techniques. We revisit the landmark interpolation which appears in the landmark-based registration techniques and add some generalizations. We develop a general elastic image registration algorithm. It uses a grid of uniform B-splines to describe the deformation. It also uses B-splines for image interpolation. Multiresolution in both image and deformation model spaces yields robustness and speed. First we describe a version of this algorithm targeted at finding unidirectional deformation in EPI magnetic resonance images. Then we present the enhanced and generalized version of this algorithm which is significantly faster and capable of treating multidimensional deformations. We apply this algorithm to the registration of SPECT data and to the motion estimation in ultrasound image sequences. A semi-automatic version of the registration algorithm is capable of accepting expert hints in the form of soft landmark constraints. Much fewer landmarks are needed and the results are far superior compared to pure landmark registration. In the second part of this thesis, we deal with the problem of generalized sampling and variational reconstruction. We explain how to reconstruct an object starting from several measurements using arbitrary linear operators. This comprises the case of traditional as well as generalized sampling. Among all possible reconstructions, we choose the one minimizing an a priori given quadratic variational criterion. We give an overview of the method and present several examples of applications. We also provide the mathematical details of the theory and discuss the choice of the variational criterion to be used
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