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Mehranian A.,University of Geneva | Ay M.R.,Tehran University of Medical Sciences | Rahmim A.,Johns HopkinsUniversity | Zaidi H.,University of Geneva | Zaidi H.,University of Groningen
IEEE Transactions on Nuclear Science | Year: 2013

The presence of metallic implants in the body of patients undergoing X-ray computed tomography (CT) examinations often results in severe streaking artifacts that degrade image quality. In this work, we propose a new metal artifact reduction (MAR) algorithm for 2D fan-beam and 3D cone-beam CT based on the maximum a posteriori (MAP) completion of the projections corrupted by metallic implants. In this algorithm, the prior knowledge obtained from a tissue-classified prior image is exploited in the completion of missing projections and incorporated into a new prior potential function. The prior is especially designed to exploit and promote the sparsity of a residual projection (sinogram) dataset obtained from the subtraction of the unknown target dataset from the projection dataset of the tissue-classified prior image. The MAP completion is formulated as an equality-constrained convex optimization and solved using an accelerated projected gradient algorithm. The performance of the proposed algorithm is compared with two state-of-the-art algorithms, namely 3D triangulated linear interpolation (LI) and normalized metal artifact reduction (NMAR) algorithm using simulated and clinical studies. The simulations targeting artifact reduction in 2D fan-beam and 3D cone-beam CT demonstrate that our algorithm can outperform its counterparts, particularly in cone-beam CT. In the clinical datasets, the performance of the proposed algorithm was subjectively and objectively compared in terms of metal artifact reduction of a sequence of 2D CT slices. The clinical results show that the proposed algorithm effectively reduces metal artifacts without introducing new artifacts due to erroneous interpolation and normalization as in the case of LI and NMAR algorithms. © 1963-2012 IEEE. Source


Su T.A.,Columbia University | Li H.,Columbia University | Zhang V.,Columbia University | Neupane M.,Columbia University | And 8 more authors.
Journal of the American Chemical Society | Year: 2015

While the electrical conductivity of bulk-scale group 14 materials such as diamond carbon, silicon, and germanium is well understood, there is a gap in knowledge regarding the conductivity of these materials at the nano and molecular scales. Filling this gap is important because integrated circuits have shrunk so far that their active regions, which rely so heavily on silicon and germanium, begin to resemble ornate molecules rather than extended solids. Here we unveil a new approach for synthesizing atomically discrete wires of germanium and present the first conductance measurements of molecular germanium using a scanning tunneling microscope-based break-junction (STM-BJ) technique. Our findings show that germanium and silicon wires are nearly identical in conductivity at the molecular scale, and that both are much more conductive than aliphatic carbon. We demonstrate that the strong donor ability of C-Ge I-bonds can be used to raise the energy of the anchor lone pair and increase conductance. Furthermore, the oligogermane wires behave as conductance switches that function through stereoelectronic logic. These devices can be trained to operate with a higher switching factor by repeatedly compressing and elongating the molecular junction. © 2015 American Chemical Society. Source


Dianat S.S.,Johns HopkinsUniversity | Carter H.B.,James Buchanan Brady Urological Institute | Pienta K.J.,James Buchanan Brady Urological Institute | Schaeffer E.M.,James Buchanan Brady Urological Institute | And 6 more authors.
Urology | Year: 2015

Objective To assess the association between magnetic resonance (MR) appearance of prostate cancer on a baseline multiparametric prostate (MP) MR imaging (MRI) and biopsy outcome in men with favorable-risk prostate cancer managed with active surveillance (AS).Materials and Methods Ninety-six consecutive men (mean age, 67.8 years) who had a baseline MP MRI within 1 year of AS enrollment were included in the study. MP MRI results were analyzed to identify men with MR-invisible tumor defined as no signal abnormality on T2-weighted images, no focal restricted diffusion, and no perfusion abnormality on dynamic contrast-enhanced images. Patients with (n = 84) or without (n = 12) MR-visible tumor were compared and the impact of MR-invisibility of tumor on the risk of adverse biopsy pathology based on the Epstein criteria was investigated with a median follow-up of 23 months.Results Adverse biopsy pathology occurred in 36.5% (35 of 96) of patients. There was no significant difference in the fulfillment of AS criteria at enrollment, prostate-specific antigen level or density, prostate volume, and number of biopsies (total or after MRI) between the 2 groups of patients. A total of 8.3% (1 of 12) of men with MR-invisible tumor had adverse biopsy pathology as compared with 40.5% (34 of 84) of men with MR-visible tumors. The MR-invisibility of tumor was associated with a lower risk of adverse biopsy pathology (crude relative risk = 0.35; 95% confidence interval, 0.10-1.25; prostate-specific antigen density-adjusted relative risk = 0.21; 95% confidence interval, 0.03-1.32).Conclusion The MR-invisibility of tumor on MP MRI could be of prognostic significance in monitoring men in AS with potential benefit of tailoring the frequency of surveillance biopsies and reducing the number of unnecessary biopsies. © 2015 Elsevier Inc. Source


Suo Y.,Johns HopkinsUniversity | Zhang J.,Johns HopkinsUniversity | Xiong T.,Johns HopkinsUniversity | Chin P.S.,Johns HopkinsUniversity | And 2 more authors.
IEEE Transactions on Biomedical Circuits and Systems | Year: 2014

Widely utilized in the field of Neuroscience, implantable neural recording devices could capture neuron activities with an acquisition rate on the order of megabytes per second. In order to efficiently transmit neural signals through wireless channels, these devices require compression methods that reduce power consumption. Although recent Compressed Sensing (CS) approaches have successfully demonstrated their power, their full potential is yet to be explored. Built upon our previous on-chip CS implementation, we propose an energy efficient multi-mode CS framework that focuses on improving the off-chip components, including (i) a two-stage sensing strategy, (ii) a sparsifying dictionary directly using data, (iii) enhanced compression performance from Full Signal CS mode and Spike Restoration mode to Spike CS {+} Restoration mode and; (iv) extension of our framework to the Tetrode CS recovery using joint sparsity. This new framework achieves energy efficiency, implementation simplicity and system flexibility simultaneously. Extensive experiments are performed on simulation and real datasets. For our Spike CS {+} Restoration mode, we achieve a compression ratio of 6% with a reconstruction SNDR {>} 10 dB and a classification accuracy {>} 95\hbox{\%} for synthetic datasets. For real datasets, we get a 10% compression ratio with {\sim} 10 dB for Spike CS {+} Restoration mode. © 2007-2012 IEEE. Source

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