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      PET motion correction in context of integrated PET/MR: Current techniques, limitations, and future projections

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          An optimal radial profile order based on the Golden Ratio for time-resolved MRI.

          In dynamic magnetic resonance imaging (MRI) studies, the motion kinetics or the contrast variability are often hard to predict, hampering an appropriate choice of the image update rate or the temporal resolution. A constant azimuthal profile spacing (111.246 degrees), based on the Golden Ratio, is investigated as optimal for image reconstruction from an arbitrary number of profiles in radial MRI. The profile order is evaluated and compared with a uniform profile distribution in terms of signal-to-noise ratio (SNR) and artifact level. The favorable characteristics of such a profile order are exemplified in two applications on healthy volunteers. First, an advanced sliding window reconstruction scheme is applied to dynamic cardiac imaging, with a reconstruction window that can be flexibly adjusted according to the extent of cardiac motion that is acceptable. Second, a contrast-enhancing k-space filter is presented that permits reconstructing an arbitrary number of images at arbitrary time points from one raw data set. The filter was utilized to depict the T1-relaxation in the brain after a single inversion prepulse. While a uniform profile distribution with a constant angle increment is optimal for a fixed and predetermined number of profiles, a profile distribution based on the Golden Ratio proved to be an appropriate solution for an arbitrary number of profiles.
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            Evaluation of registration methods on thoracic CT: the EMPIRE10 challenge.

            EMPIRE10 (Evaluation of Methods for Pulmonary Image REgistration 2010) is a public platform for fair and meaningful comparison of registration algorithms which are applied to a database of intrapatient thoracic CT image pairs. Evaluation of nonrigid registration techniques is a nontrivial task. This is compounded by the fact that researchers typically test only on their own data, which varies widely. For this reason, reliable assessment and comparison of different registration algorithms has been virtually impossible in the past. In this work we present the results of the launch phase of EMPIRE10, which comprised the comprehensive evaluation and comparison of 20 individual algorithms from leading academic and industrial research groups. All algorithms are applied to the same set of 30 thoracic CT pairs. Algorithm settings and parameters are chosen by researchers expert in the configuration of their own method and the evaluation is independent, using the same criteria for all participants. All results are published on the EMPIRE10 website (http://empire10.isi.uu.nl). The challenge remains ongoing and open to new participants. Full results from 24 algorithms have been published at the time of writing. This paper details the organization of the challenge, the data and evaluation methods and the outcome of the initial launch with 20 algorithms. The gain in knowledge and future work are discussed.
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              Rapid Automated Algorithm for Aligning and Reslicing PET Images

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                Author and article information

                Journal
                Medical Physics
                Med. Phys.
                Wiley
                00942405
                December 2017
                December 2017
                October 23 2017
                : 44
                : 12
                : e430-e445
                Affiliations
                [1 ]Australian e-Health Research Centre; CSIRO; Brisbane Australia
                [2 ]Faculty of Medicine; University of Queensland; Brisbane Australia
                [3 ]Department of Radiation Oncology; Royal Brisbane and Women's Hospital; Brisbane Australia
                [4 ]Herston Imaging Research Facility and Specialised PET Services Queensland; Royal Brisbane and Women's Hospital; Brisbane Australia
                Article
                10.1002/mp.12577
                28905393
                eba64c9e-0db9-4964-ab63-e57395d91d5d
                © 2017

                http://doi.wiley.com/10.1002/tdm_license_1.1

                http://onlinelibrary.wiley.com/termsAndConditions#vor

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