Fast field-cycling NMR of cartilage : a way toward molecular imaging

Peer reviewedPublisher PD

Using an Overall Mass-Transfer Coefficient for Prediction of Drying of Chilean Coigüe

A phenomenological model was used to quantify the drying process of Chilean coigüe (Nothofagus dombeyi). This model is based on an overall mass-transfer coefficient, K, which was determined in four laboratory drying runs. The model suitably described the drying of Chilean coigüe lumber of 19- and 30-mm thickness with K ranging from 0.012 to 0.021 ms-1 at a dry-bulb of 60°C and a wet-bulb of 40°C. A preliminary industrial run under somewhat similar conditions in a 100-m3 industrial kiln with 38-mm-thick lumber showing that the drying process could be represented by a K of 0.008 ms-1. The laboratory-scale values of K can be regarded as ideal from which to compare the performance of the industrial unit

A cross-center smoothness prior for variational Bayesian brain tissue segmentation

Suppose one is faced with the challenge of tissue segmentation in MR images, without annotators at their center to provide labeled training data. One option is to go to another medical center for a trained classifier. Sadly, tissue classifiers do not generalize well across centers due to voxel intensity shifts caused by center-specific acquisition protocols. However, certain aspects of segmentations, such as spatial smoothness, remain relatively consistent and can be learned separately. Here we present a smoothness prior that is fit to segmentations produced at another medical center. This informative prior is presented to an unsupervised Bayesian model. The model clusters the voxel intensities, such that it produces segmentations that are similarly smooth to those of the other medical center. In addition, the unsupervised Bayesian model is extended to a semi-supervised variant, which needs no visual interpretation of clusters into tissues.Comment: 12 pages, 2 figures, 1 table. Accepted to the International Conference on Information Processing in Medical Imaging (2019

Asymmetric Image-Template Registration

Authors Manuscript received: 2010 May 4. 12th International Conference, London, UK, September 20-24, 2009, Proceedings, Part IA natural requirement in pairwise image registration is that the resulting deformation is independent of the order of the images. This constraint is typically achieved via a symmetric cost function and has been shown to reduce the effects of local optima. Consequently, symmetric registration has been successfully applied to pairwise image registration as well as the spatial alignment of individual images with a template. However, recent work has shown that the relationship between an image and a template is fundamentally asymmetric. In this paper, we develop a method that reconciles the practical advantages of symmetric registration with the asymmetric nature of image-template registration by adding a simple correction factor to the symmetric cost function. We instantiate our model within a log-domain diffeomorphic registration framework. Our experiments show exploiting the asymmetry in image-template registration improves alignment in the image coordinates.NAMIC (NIH NIBIB NAMIC U54-EB005149)NAC (NIH NCRR NAC P41- RR13218)mBIRN (NIH NCRR mBIRN U24-RR021382)NIH NINDS (R01-NS051826 Grant)National Science Foundation (U.S.) (CAREER Grant 0642971)NIBIB (R01 EB001550)NIBIB (R01EB006758)NCRR (R01 RR16594-01A1)NCRR (P41-RR14075)NINDS (R01 NS052585-01)Singapore. Agency for Science, Technology and Researc

Joint multi-field T1 quantification for fast field-cycling MRI

Acknowledgment This article is based upon work from COST Action CA15209, supported by COST (European Cooperation in Science and Technology). Oliver Maier is a Recipient of a DOC Fellowship (24966) of the Austrian Academy of Sciences at the Institute of Medical Engineering at TU Graz. The authors would like to acknowledge the NVIDIA Corporation Hardware grant support.Peer reviewedPublisher PD

Multicomponent analysis of T1 relaxation in bovine articular cartilage at low magnetic fields

European Union’s Horizon 2020 Research and Innovation Programme; Grant/Award number 668119 (project “IDentIFY”).Peer reviewedPublisher PD

Synthesis and hyperpolarisation of eNOS substrates for quantification of NO production by 1H NMR spectroscopy

Hyperpolarization enhances the intensity of the NMR signals of a molecule, whose in vivo metabolic fate can be monitored by MRI with higher sensitivity. SABRE is a hyperpolarization technique that could potentially be used to image nitric oxide (NO) production in vivo. This would be very important, because NO dysregulation is involved in several pathologies, including cardiovascular ones. The nitric oxide synthase (NOS) pathway leads to NO production via conversion of l-arginine into l-citrulline. NO is a free radical gas with a short half-life in vivo (≈5s), therefore direct NO quantification is challenging. An indirect method - based on quantifying conversion of an l-Arg- to l-Cit-derivative by 1H NMR spectroscopy - is herein proposed. A small library of pyridyl containing l-Arg derivatives was designed and synthesised. In vitro tests showed that compounds 4a-j and 11a-c were better or equivalent substrates for the eNOS enzyme (NO2 - production=19-46μM) than native l-Arg (NO2 - production=25μM). Enzymatic conversion of l-Arg to l-Cit derivatives could be monitored by 1H NMR. The maximum hyperpolarization achieved by SABRE reached 870-fold NMR signal enhancement, which opens up exciting future perspectives of using these molecules as hyperpolarized MRI tracers in vivo

Post traumatic brain perfusion SPECT analysis using reconstructed ROI maps of radioactive microsphere derived cerebral blood flow and statistical parametric mapping

<p>Abstract</p> <p>Background</p> <p>Assessment of cerebral blood flow (CBF) by SPECT could be important in the management of patients with severe traumatic brain injury (TBI) because changes in regional CBF can affect outcome by promoting edema formation and intracranial pressure elevation (with cerebral hyperemia), or by causing secondary ischemic injury including post-traumatic stroke. The purpose of this study was to establish an improved method for evaluating regional CBF changes after TBI in piglets.</p> <p>Methods</p> <p>The focal effects of moderate traumatic brain injury (TBI) on cerebral blood flow (CBF) by SPECT cerebral blood perfusion (CBP) imaging in an animal model were investigated by parallelized statistical techniques. Regional CBF was measured by radioactive microspheres and by SPECT 2 hours after injury in sham-operated piglets versus those receiving severe TBI by fluid-percussion injury to the left parietal lobe. Qualitative SPECT CBP accuracy was assessed against reference radioactive microsphere regional CBF measurements by map reconstruction, registration and smoothing. Cerebral hypoperfusion in the test group was identified at the voxel level using statistical parametric mapping (SPM).</p> <p>Results</p> <p>A significant area of hypoperfusion (P < 0.01) was found as a response to the TBI. Statistical mapping of the reference microsphere CBF data confirms a focal decrease found with SPECT and SPM.</p> <p>Conclusion</p> <p>The suitability of SPM for application to the experimental model and ability to provide insight into CBF changes in response to traumatic injury was validated by the SPECT SPM result of a decrease in CBP at the left parietal region injury area of the test group. Further study and correlation of this characteristic lesion with long-term outcomes and auxiliary diagnostic modalities is critical to developing more effective critical care treatment guidelines and automated medical imaging processing techniques.</p

Symmetric Log-Domain Diffeomorphic Registration: A Demons-based Approach

pmid 18979814International audienceModern morphometric studies use non-linear image registration to compare anatomies and perform group analysis. Recently, log-Euclidean approaches have contributed to promote the use of such computational anatomy tools by permitting simple computations of statistics on a rather large class of invertible spatial transformations. In this work, we propose a non-linear registration algorithm perfectly fit for log-Euclidean statistics on diffeomorphisms. Our algorithm works completely in the log-domain, i.e. it uses a stationary velocity field. This implies that we guarantee the invertibility of the deformation and have access to the true inverse transformation. This also means that our output can be directly used for log-Euclidean statistics without relying on the heavy computation of the log of the spatial transformation. As it is often desirable, our algorithm is symmetric with respect to the order of the input images. Furthermore, we use an alternate optimization approach related to Thirion's demons algorithm to provide a fast non-linear registration algorithm. First results show that our algorithm outperforms both the demons algorithm and the recently proposed diffeomorphic demons algorithm in terms of accuracy of the transformation while remaining computationally efficient