@article{AliMontenegro2014,
  author    = {Ali, Quasim and Montenegro, Sergio},
  title     = {A Matlab Implementation of Differential GPS for Low-cost GPS Receivers},
  doi       = {10.12716/1001.08.03.03},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-113618},
  year      = {2014},
  abstract  = {A number of public codes exist for GPS positioning and baseline determination in off-line mode. However, no software code exists for DGPS exploiting correction factors at base stations, without relying on double difference information. In order to accomplish it, a methodology is introduced in MATLAB environment for DGPS using C/A pseudoranges on single frequency L1 only to make it feasible for low-cost GPS receivers. Our base station is at accurately surveyed reference point. Pseudoranges and geometric ranges are compared at base station to compute the correction factors. These correction factors are then handed over to rover for all valid satellites observed during an epoch. The rover takes it into account for its own true position determination for corresponding epoch. In order to validate the proposed algorithm, our rover is also placed at a pre-determined location. The proposed code is an appropriate and simple to use tool for post-processing of GPS raw data for accurate position determination of a rover e.g. Unmanned Aerial Vehicle during post-mission analysis.},
  language  = {en}
}
@article{SchadtIsraelSamnick2021,
  author    = {Schadt, Fabian and Israel, Ina and Samnick, Samuel},
  title     = {Development and Validation of a Semi-Automated, Preclinical, MRI-Template Based PET Image Data Analysis Tool for Rodents},
  series = {Frontiers in Neuroinformatics},
  volume    = {15},
  journal   = {Frontiers in Neuroinformatics},
  issn      = {1662-5196},
  doi       = {10.3389/fninf.2021.639643},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-240289},
  year      = {2021},
  abstract  = {AimIn PET imaging, the different types of radiotracers and accumulations, as well as the diversity of disease patterns, make the analysis of molecular imaging data acquired in vivo challenging. Here, we evaluate and validate a semi-automated MRI template-based data analysis tool that allows preclinical PET images to be aligned to a self-created PET template. Based on the user-defined volume-of-interest (VOI), image data can then be evaluated using three different semi-quantitative parameters: normalized activity, standardized uptake value, and uptake ratio. Materials and MethodsThe nuclear medicine Data Processing Analysis tool (NU_DPA) was implemented in Matlab. Testing and validation of the tool was performed using two types of radiotracers in different kinds of stroke-related brain diseases in rat models. The radiotracers used are 2-[\(^{18}\)F]fluoro-2-deoxyglucose ([\(^{18}\)F]FDG), a metabol\(^{68}\)Ga]Ga-Fucoidan, a target-selective radioligand specifically binding to p-selectin. After manual image import, the NU_DPA tool automatically creates an averaged PET template out of the acquired PET images, to which all PET images are then aligned onto. The added MRI template-based information, resized to the lower PET resolution, defines the VOI and also allows a precise subdivision of the VOI into individual sub-regions. The aligned PET images can then be evaluated semi-quantitatively for all regions defined in the MRI atlas. In addition, a statistical analysis and evaluation of the semi-quantitative parameters can then be performed in the NU_DPA tool. ResultsUsing ischemic stroke data in Wistar rats as an example, the statistical analysis of the tool should be demonstrated. In this [\(^{18}\)F]FDG-PET experiment, three different experimental states were compared: healthy control state, ischemic stroke without electrical stimulation, ischemic stroke with electrical stimulation. Thereby, statistical data evaluation using the NU_DPA tool showed that the glucose metabolism in a photothrombotic lesion can be influenced by electrical stimulation. ConclusionOur NU_DPA tool allows a very flexible data evaluation of small animal PET data in vivo including statistical data evaluation. Using the radiotracers [\(^{18}\)F]FDG and [\(^{68}\)Ga]Ga-Fucoidan, it was shown that the semi-automatic MRI-template based data analysis of the NU_DPA tool is potentially suitable for both metabolic radiotracers as well as target-selective radiotracers.},
  language  = {en}
}