Filters

2021 - 20222

More filters

20222
Reset filters

Settings

search.filters.applied.f.access: openAccess × End date: 2023 × Start date: 2021 × Start date: 2021 × DDC: 570 × Type: Text × WGL Institute: WIAS ×

Search Results

Now showing 1 - 2 of 2
  • Thumbnail Image
    Item
    Denoising for Improved Parametric MRI of the Kidney: Protocol for Nonlocal Means Filtering
    (Totowa, NJ : Humana Press, 2021) Starke, Ludger; Tabelow, Karsten; Niendorf, Thoralf; Pohlmann, Andreas; Pohlmann, Andreas; Niendorf, Thoralf
    In order to tackle the challenges caused by the variability in estimated MRI parameters (e.g., T2* and T2) due to low SNR a number of strategies can be followed. One approach is postprocessing of the acquired data with a filter. The basic idea is that MR images possess a local spatial structure that is characterized by equal, or at least similar, noise-free signal values in vicinities of a location. Then, local averaging of the signal reduces the noise component of the signal. In contrast, nonlocal means filtering defines the weights for averaging not only within the local vicinity, bur it compares the image intensities between all voxels to define “nonlocal” weights. Furthermore, it generally compares not only single-voxel intensities but small spatial patches of the data to better account for extended similar patterns. Here we describe how to use an open source NLM filter tool to denoise 2D MR image series of the kidney used for parametric mapping of the relaxation times T2* and T2. This chapter is based upon work from the COST Action PARENCHIMA, a community-driven network funded by the European Cooperation in Science and Technology (COST) program of the European Union, which aims to improve the reproducibility and standardization of renal MRI biomarkers.
  • Thumbnail Image
    Item
    Ground reaction forces and external hip joint moments predict in vivo hip contact forces during gait
    (Amsterdam [u.a.] : Elsevier Science, 2022) Alves, Sónia A.; Polzehl, Jörg; Brisson, Nicholas M.; Bender, Alwina; Agres, Alison N.; Damm, Philipp; Duda, Georg N.
    Younger patients increasingly receive total hip arthroplasty (THA) as therapy for end-stage osteoarthritis. To maintain the long-term success of THA in such patients, avoiding extremely high hip loads, i.e., in vivo hip contact force (HCF), is considered essential. However, in vivo HCFs are difficult to determine and their direct measurement is limited to instrumented joint implants. It remains unclear whether external measurements of ground reaction forces (GRFs), a non-invasive, markerless and clinic-friendly measure can estimate in vivo HCFs. Using data from eight patients with instrumented hip implants, this study determined whether GRF time series data, alone or combined with other scalar variables such as hip joint moments (HJMs) and lean muscle volume (LMV), could predict the resultant HCF (rHCF) impulse using a functional linear modeling approach. Overall, single GRF time series data did not predict in vivo rHCF impulses. However, when GRF time series data were combined with LMV of the gluteus medius or sagittal HJM using a functional linear modeling approach, the in vivo rHCF impulse could be predicted from external measures only. Accordingly, this approach can predict in vivo rHCF impulses, and thus provide patients with useful insight regarding their gait behavior to avoid hip joint overloading.