http://ieeexplore.ieee.org TOC Alert for Publication# 42 2009 November 19 28 11 C1 C4 98 28 11 C2 C2 43 This paper presents an algorithm for fast image synthesis inside deformed volumes. Given the node displacements of a mesh and a reference 3-D image dataset of a predeformed volume, the method first maps the image pixels that need to be synthesized from the deformed configuration to the nominal predeformed configuration, where the pixel intensities are obtained easily through interpolation in the regular-grid structure of the reference voxel volume. This mapping requires the identification of the mesh element enclosing each pixel for every image frame. To accelerate this point location operation, a fast method of projecting the deformed mesh on image pixels is introduced in this paper. The method presented was implemented for ultrasound B-mode image simulation of a synthetic tissue phantom. The phantom deformation as a result of ultrasound probe motion was modeled using the finite element method. Experimental images of the phantom under deformation were then compared with the corresponding synthesized images using sum of squared differences and mutual information metrics. Both this quantitative comparison and a qualitative assessment show that realistic images can be synthesized using the proposed technique. An ultrasound examination system was also implemented to demonstrate that real-time image synthesis with the proposed technique can be successfully integrated into a haptic simulation. ]]> 28 11 1657 1669 1435 in vivo sequences. Synthetic experiments validate the proposed score as measure of motion parameters accuracy; whereas results in in vivo pullbacks show the reliability of the presented methodologies in clinical cases.]]> 28 11 1670 1680 3188 in vivo cross-sectional conductivity image of the human leg with 1.7 mm pixel size using the magnetic resonance electrical impedance tomography (MREIT) technique. After a review of its experimental protocol by an Institutional Review Board (IRB), we performed MREIT imaging experiments of four human subjects using a 3 T MRI scanner. Adopting thin and flexible carbon-hydrogel electrodes with a large surface area and good contact, we could inject as much as 9 mA current in a form of 15 ms pulse into the leg without producing a painful sensation and motion artifact. Sequentially injecting two imaging currents in two different directions, we collected induced magnetic flux density data inside the leg. Scaled conductivity images reconstructed by using the single-step harmonic B _z algorithm well distinguished different parts of the subcutaneous adipose tissue, muscle, crural fascia, intermuscular septum and bone inside the leg. We could observe spurious noise spikes in the outer layer of the bone primarily due to the MR signal void phenomenon there. Around the fat, the chemical shift of about two pixels occurred obscuring the boundary of the fat region. Future work should include a fat correction method incorporated in the MREIT pulse sequence and improvements in radio-frequency coils and image reconstruction algorithms. Further human imaging experiments are planned and being conducted to produce conductivity images from different parts of the human body.]]> 28 11 1681 1687 1931 Dual-energy (DE) X-ray computed tomography (CT) has been found useful in various applications. In medical imaging, one promising application is using low-dose DECT for attenuation correction in positron emission tomography (PET). Existing approaches to sinogram material decomposition ignore noise characteristics and are based on logarithmic transforms, producing noisy component sinogram estimates for low-dose DECT. In this paper, we propose two novel sinogram restoration methods based on statistical models: penalized weighted least square (PWLS) and penalized likelihood (PL), yielding less noisy component sinogram estimates for low-dose DECT than classical methods. The proposed methods consequently provide more precise attenuation correction of the PET emission images than do previous methods for sinogram material decomposition with DECT. We report simulations that compare the proposed techniques and existing approaches. ]]> 28 11 1688 1702 1451 28 11 1703 1707 599 Uncertainties in image registration may be a significant source of errors in anatomy mapping as well as dose accumulation in radiotherapy. It is, therefore, essential to validate the accuracy of image registration. Here, we propose a method to detect areas where mono modal B-spline registration performs well and to distinguish those from areas of the same image, where the registration is likely to be less accurate. It is a stochastic approach to automatically estimate the uncertainty of the resulting displacement vector field. The coefficients resulting from the B-spline registration are subject to moderate and randomly performed variations. A quantity is proposed to characterize the local sensitivity of the similarity measure to these variations. We demonstrate the statistical dependence between the local image registration error and this quantity by calculating their mutual information. We show the significance of the statistical dependence with an approach based on random redistributions. The proposed method has the potential to divide an image into subregions which differ in the magnitude of their average registration error. ]]> 28 11 1708 1716 774 28 11 1717 1726 697 28 11 1727 1735 1666 28 11 1736 1753 7028 The use of selective internal radiation therapy for treatment of hepatocellular carcinoma and liver metastases using Y-90 labeled microspheres has become an effective and widely used treatment regimen. However, dosimetric evaluations of this treatment are still primitive as uniform distribution models based only on injected activity are often used. This investigation attempts to quantify the effectiveness of several sophisticated patient-specific techniques which utilize the source distribution of Tc-99m MAA simulation studies to perform voxelized dosimetric computations. Among these techniques are complete Monte-Carlo radiation transport computation in patient-specific CT-based voxel phantoms, local energy deposition in patient specific phantoms and kernel transport techniques in water. Each technique was evaluated using three different phantom voxel dimensions and SPECT reconstruction matrix sizes. Dose evaluation results using all methods were compared to the exact solution, obtained using fully 3-D Monte-Carlo simulations with source distribution based not on SPECT data, but on the injected activity and exact boundaries of the anthropomorphic phantom used in the study. The results of this study show that at large voxel sizes and using SPECT reconstructions with a small matrix size (64 $,times,$64), Monte-Carlo and local deposition methods are nearly equivalent. However, using a large SPECT reconstruction matrix (256$,times,$ 256) the local deposition method is significantly more accurate than full 3-D Monte-Carlo transport, and with a negligible computational burden. ]]> 28 11 1754 1758 432 in vivo demonstrate that the method yields spin-density and relaxivity maps that are neither affected by the typical artifacts from TE mixing, nor by streaking artifacts from the incomplete k-space coverage at individual echo times.]]> 28 11 1759 1769 5935 k-space and image-space combination (KICT) algorithm for rigid body motion-induced phase error correction is introduced. KICT estimates the motion-induced phase errors in image space using the self-navigated capability of the variable density spiral trajectory. The correction is then performed in k -space. The algorithm is shown to overcome the problem of aliased phase errors. Further, the algorithm preserves the phase of the imaging object and receiver coils in the corrected k -space data, which is important for parallel imaging applications. After phase error correction, any parallel reconstruction method can be used. The KICT algorithm is tested with both simulated and in vivo data with both multishot single-coil and multishot multicoil acquisitions. We show that KICT correction results in diffusion-weighted - images with higher signal-to-noise ratio (SNR) and fractional anisotropy (FA) maps with better resolved fiber tracts as compared to DPS. In peripheral-gated acquisitions, KICT is comparable to the CG method.]]> 28 11 1770 1780 2333 28 11 1781 1790 1413 Rigid-body point-based registration is frequently used in computer assisted surgery to align corresponding points, or fiducials, in preoperative and intraoperative data. This alignment is mostly achieved by assuming the same homogeneous error distribution for all the points; however, due to the properties of the medical instruments used in measuring the point coordinates, the error distribution might be inhomogeneous and different for each point. In this paper, in an effort to understand the effect of error distribution in the localized points on the performed registration, we derive a closed-form solution relating the error distribution of each point with the performed registration accuracy. The solution uses maximum likelihood estimation to calculate the probability density function of registration error at each fiducial point. Extensive numerical simulations are performed to validated the proposed solution. ]]> 28 11 1791 1801 312 Dynamic cardiac magnetic resonance imaging (MR) and computed tomography (CT) provide cardiologists and cardiac surgeons with high-quality 4-D images for diagnosis and therapy, yet the effective use of these high-quality anatomical models remains a challenge. Ultrasound (US) is a flexible imaging tool, but the US images produced are often difficult to interpret unless they are placed within their proper 3-D anatomical context. The ability to correlate real-time 3-D US volumes (RT3D US) with dynamic MR/CT images would offer a significant contribution to improve the quality of cardiac procedures. In this paper, we present a rapid two-step method for registering RT3D US to high-quality dynamic 3-D MR/CT images of the beating heart. This technique overcomes some major limitations of image registration (such as the correct registration result not necessarily occurring at the maximum of the mutual information (MI) metric) using the MI metric. We demonstrate the effectiveness of our method in a dynamic heart phantom (DHP) study and a human subject study. The achieved mean target registration error of CT+US images in the phantom study is 2.59 mm. Validation using human MR/US volumes shows a target registration error of 1.76 mm. We anticipate that this technique will substantially improve the quality of cardiac diagnosis and therapies. ]]> 28 11 1802 1814 1360 Automated analysis of mammograms requires robust methods for pectoralis segmentation and nipple detection. Locating the nipple is especially important in multiview computer aided detection systems, in which findings are matched across images using the nipple-to-finding distance. Segmenting the pectoralis is a key preprocessing step to avoid false positives when detecting masses due to the similarity of the texture of mammographic parenchyma and the pectoral muscle. A multiatlas algorithm capable of providing very robust initial estimates of the nipple position and pectoral region in digitized mammograms is presented here. Ten full-field digital mammograms, which are easily annotated attributed to their excellent contrast, are robustly registered to the target digitized film-screen mammogram. The annotations are then propagated and fused into a final nipple position and pectoralis segmentation. Compared to other nipple detection methods in the literature, the system proposed here has the advantages that it is more robust and can provide a reliable estimate when the nipple is located outside the image. Our results show that the change in the correlation between nipple-to-finding distances in craniocaudal and mediolateral oblique views is not significant when the detected nipple positions replace the manual annotations. Moreover, the pectoralis segmentation is acceptable and can be used as initialization for a more complex algorithm to optimize the outline locally. A novel aspect of the method is that it is also capable of detecting and segmenting the pectoralis in craniocaudal views. ]]> 28 11 1815 1824 1037 Although it is accepted that linear Granger causality can reveal effective connectivity in functional magnetic resonance imaging (fMRI), the issue of detecting nonlinear connectivity has hitherto not been considered. In this paper, we address kernel Granger causality (KGC) to describe effective connectivity in simulation studies and real fMRI data of a motor imagery task. Based on the theory of reproducing kernel Hilbert spaces, KGC performs linear Granger causality in the feature space of suitable kernel functions, assuming an arbitrary degree of nonlinearity. Our results demonstrate that KGC captures effective couplings not revealed by the linear case. In addition, effective connectivity networks between the supplementary motor area (SMA) as the seed and other brain areas are obtained from KGC. ]]> 28 11 1825 1835 632 Generating 3-D images of the heart during interventional procedures is a significant challenge. In addition to real time fluoroscopy, angiographic C-arm systems can also now be used to generate 3-D/4-D CT images on the same system. One protocol for cardiac CT uses ECG triggered multisweep scans. A 3-D volume of the heart at a particular cardiac phase is then reconstructed by applying Feldkamp (FDK) reconstruction to the projection images with retrospective ECG gating. In this work we introduce a unified framework for heart motion estimation and dynamic cone-beam reconstruction using motion corrections. The benefits of motion correction are 1) increased temporal and spatial resolution by removing cardiac motion which may still exist in the ECG gated data sets and 2) increased signal-to-noise ratio (SNR) by using more projection data than is used in standard ECG gated methods. Three signal-enhanced reconstruction methods are introduced that make use of all of the acquired projection data to generate a 3-D reconstruction of the desired cardiac phase. The first averages all motion corrected back-projections; the second and third perform a weighted averaging according to 1) intensity variations and 2) temporal distance relative to a time resolved and motion corrected reference FDK reconstruction. In a comparison study seven methods are compared: nongated FDK, ECG-gated FDK, ECG-gated, and motion corrected FDK, the three signal-enhanced approaches, and temporally aligned and averaged ECG-gated FDK reconstructions. The quality measures used for comparison are spatial resolution and SNR. Evaluation is performed using phantom data and animal models. We show that data driven and subject-specific motion estimation combined with motion correction can decrease motion-related blurring substantially. Furthermore, SNR can be increased by up to 70% while maintaining spatial resolution at the same level as is provided by the ECG-gated FDK. The presented framework provides exce- llent image quality for cardiac C-arm CT. ]]> 28 11 1836 1849 1880 28 11 1850 1857 1139 28 11 1858 1858 601 28 11 1859 1859 157 28 11 1860 1860 345 28 11 C3 C3 26